https://news.mcmedia.cam/feed/Physics MCMedia News RSS Feed - Physics specific feed https://news.mcmedia.cam/rss-info.html MCMedia RSS Generator v1.0 Sun, 17 May 2026 02:10:34 +0000 https://arxiv.org/abs/2603.11045 Fri, 15 May 2026 00:00:00 -0400 arXiv:2603.11045v2 Announce Type: replace-cross Abstract: Inverse problems for stiff parabolic partial differential equations (PDEs), such as the inverse heat conduction problem (IHCP), are severely ill-posed: the forward map rapidly damps high-frequency interior structure before it reaches the boundary. Soft-constrained physics-informed neural networks (PINNs), which embed the PDE as a residual penalty, suffer from gradient pathology in this regime and tend to fit boundary measurements while leaving the interior field essentially untouched. We propose Neural Field Thermal Tomography (NeFTY), a hard-constrained neural field framework for label-free three-dimensional inverse heat conduction. NeFTY represents the unknown diffusivity as a continuous coordinate-based neural network, and at every optimization step passes the candidate field through a differentiable implicit-Euler heat solver with harmonic-mean interface flux, so that the governing PDE holds exactly on the discretization rather than as a soft penalty. Adjoint gradients propagate the surface reconstruction error back to the network weights at solver-level memory cost, making test-time inversion tractable on a single GPU. Across synthetic 3D benchmarks, NeFTY substantially outperforms soft-constrained PINN variants and a voxel-grid baseline on label-free volumetric recovery, and it transfers to real thermography data, surpassing classical signal-processing baselines in both defect segmentation and depth estimation. Additional details at https://cab-lab-princeton.github.io/nefty/ Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2602.18115 Fri, 15 May 2026 00:00:00 -0400 arXiv:2602.18115v2 Announce Type: replace-cross Abstract: This work investigates the geometrical properties of self-gravitating $N$-body systems from the perspective established by Henri Poincar\'e and Albert Einstein concerning the operational nature of measured geometry. Utilizing recent numerical analyses of central configurations--special equilibrium solutions to the Newtonian $N$-body problem--we uncover systematic spatial variations in nearest-neighbor particle separations correlated with the radial distance from the system's center of mass. We argue that these variations reflect a context-dependent, emergent effective geometry shaped by gravitational interactions, in accordance with Poincar\'e's assertion that measured geometry depends on the forces influencing measuring devices, and Einstein's view that rods and clocks define physical geometry through their local dynamics. By revisiting these foundational insights within a modern computational framework, we provide evidence that geometry in self-gravitating Newtonian systems is not a fixed background, but an emergent construct arising from internal physical interactions. Physics/physics.hist-ph_(History_and_Philosophy_of_Physics) https://arxiv.org/abs/2602.11626 Fri, 15 May 2026 00:00:00 -0400 arXiv:2602.11626v2 Announce Type: replace-cross Abstract: Learning solution operators for systems with complex, varying geometries and parametric physical settings is a central challenge in scientific machine learning. In many-query regimes such as design optimization, control and inverse problems, surrogate modeling must generalize across geometries while allowing flexible evaluation at arbitrary spatial locations. In this work, we propose Arbitrary Geometry-encoded Transformer (ArGEnT), a geometry-aware attention-based architecture for operator learning on arbitrary domains. ArGEnT employs Transformer attention mechanisms to encode geometric information directly from point-cloud representations with three variants-self-attention, cross-attention, and hybrid-attention-that incorporates different strategies for incorporating geometric features. By integrating ArGEnT into DeepONet as the trunk network, we develop a surrogate modeling framework capable of learning operator mappings that depend on both geometric and non-geometric inputs without the need to explicitly parametrize geometry as a branch network input. Evaluation on benchmark problems spanning fluid dynamics, solid mechanics and electrochemical systems, we demonstrate significantly improved prediction accuracy and generalization performance compared with the standard DeepONet and other existing geometry-aware saurrogates. In particular, the cross-attention transformer variant enables accurate geometry-conditioned predictions with reduced reliance on signed distance functions. By combining flexible geometry encoding with operator-learning capabilities, ArGEnT provides a scalable surrogate modeling framework for optimization, uncertainty quantification, and data-driven modeling of complex physical systems. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.11253 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.11253v2 Announce Type: replace Abstract: Two-body reduced density matrices (2RDMs) encode the essential two-electron physics of electronic states, but their quartic storage cost poses a major limitation in practical workflows. We investigate a simple protocol to compress both transition and non-transition 2RDMs into a lower-rank representation that preserves their wedge-product structure and physical symmetries under truncation. The resulting decomposition couples Coulomb and exchange channels through a common set of low-rank factors, yielding a more compact rank-sparse representation than single-channel factorizations. For correlated states, the effective rank scales linearly with system size, achieving a $\sim99$\% compression for the coupled-cluster 2RDM of octane while retaining chemical accuracy. We apply this to the recently introduced {\em ab initio} eigenvector continuation workflows, where many-body wave functions are interpolated across nuclear geometries with mean-field cost. Here, 2RDMs between training states act as projectors into a subspace but their memory scaling limits applications to larger systems. The compression scheme reduces the memory cost from quartic to quadratic for a fixed error per electron. Metrics to systematically control the decomposition are investigated, enabling statistically resolved structural, dynamical and spectroscopic observables from nonadiabatic molecular dynamics simulations of photoexcited H$_{28}$ chains, interpolating from compressed near-exact DMRG training data. This establishes these structure-preserving compressed intermediates for practical correlated electronic structure workflows. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2603.22476 Fri, 15 May 2026 00:00:00 -0400 arXiv:2603.22476v2 Announce Type: replace Abstract: Although continuous symmetry theory has attracted increasing attention in modern chemistry, local symmetry remains under-investigated. As a consequence, the relationship between symmetry and chemical behavior is often obscured, limiting the practical use of fuzzy symmetry measures. In this study, we introduce a novel framework for evaluating local symmetry based on electron density localization, and present continuous symmetry representations for several representative molecules. Our approach not only quantitatively captures global symmetry, but also reveals distinctive features of symmetry in a local chemical environment. The related concept, local chirality or chirotopicity, is also discussed. Overall, the proposed local symmetry and chirality measures provide valuable insights into molecular structure and structure-property relationships. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2602.05793 Fri, 15 May 2026 00:00:00 -0400 arXiv:2602.05793v2 Announce Type: replace Abstract: Transition interface sampling (TIS) and replica exchange TIS (RETIS) are powerful methods for computing rates of rare events inaccessible to straightforward molecular dynamics (MD) simulations. Path reweighting extends their output, enabling the evaluation of diverse thermodynamic and kinetic quantities, including reaction prediction metrics, activation barriers, committor functions, and free energies. The recently developed Infinity-RETIS algorithm boosts parallel efficiency through asynchronous replica exchanges in the infinite-swap limit, eliminating the wall-time bottlenecks of conventional RETIS. This approach introduces fractional samples and biased sampling distributions, requiring a generalized path reweighting framework, for which we derive expressions demonstrating how exact dynamic and thermodynamic variables can be computed. We then focus on a special class of free energy surfaces defined by history-dependent conditions, whose values are influenced by kinetic factors such as particle mass and friction, unlike standard unconditional free energy surfaces. Even with suboptimal reaction coordinates, these conditional free energies can reveal kinetically relevant barriers that may be misrepresented by standard unconditional free energies, thereby providing a rigorous and versatile tool for characterizing complex molecular transitions. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2511.07686 Fri, 15 May 2026 00:00:00 -0400 arXiv:2511.07686v2 Announce Type: replace Abstract: Chemical Reaction Neural Networks (CRNNs) have emerged as an interpretable machine learning framework for discovering reaction kinetics directly from data, while strictly adhering to the Arrhenius and mass action laws. However, standard CRNNs cannot represent pressure-dependent or mixture-based rate behavior, which is critical in many combustion and chemical systems and typically requires empirical falloff formulations such as Troe or SRI, or data-based interpolation or polynomial fits such as PLOG or Chebyshev Polynomials. Here, we develop Kolmogorov-Arnold Chemical Reaction Neural Networks (KA-CRNNs) that generalize CRNNs by modeling each kinetic parameter as a learnable function of third-body concentrations using Kolmogorov-Arnold activations. This structure maintains the Arrhenius and mass action interpretability and physical constraints of a vanilla CRNN while enabling assumption-free inference of global and collider-specific pressure effects directly from data. Two proof-of-concept reaction studies are presented to highlight the capability of KA-CRNNs to accurately reproduce pressure-dependent and collider-specific kinetics across a range of temperatures, pressures, and bath gas mixtures, extracting meaningful and generalizable models from sparse training data and significantly outperforming interpolative approaches (2.88x reduction in MSE). The framework establishes a foundation for data-driven discovery of extended kinetic behaviors in complex reacting systems, advancing interpretable and physics-constrained approaches for chemical model inference. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.15073 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.15073v1 Announce Type: cross Abstract: We present an $\mathcal{O}(L^3)$ algorithm for evaluating contracted Clebsch--Gordan tensor products in $\mathrm{O}(3)$-equivariant machine learning potentials at fixed Canonical Polyadic (CP) rank. Mapping the angular integral to a structured Gauss--Legendre and Fourier tensor-product grid decouples the radial channel contractions from the angular transforms. The antisymmetric parity-odd Clebsch--Gordan channels, unreachable by the symmetric pointwise product on a scalar $S^2$ grid, are recovered through the surface-curl pairing $\hat r \cdot [\nabla_{S^2} A \times \nabla_{S^2} B]$, the spherical Poisson bracket, which supplies the $L=1$ angular momentum on the grid while preserving rotational equivariance. The construction extends to parity-aware equivariant message passing in atomic-cluster-expansion-style architectures and is verified by direct numerical quadrature. The full uncontracted Clebsch--Gordan tensor product remains subject to the $\mathcal{O}(L^4)$ output-size lower bound. A benchmark shows wall-clock scaling empirically as $L^2$ across the practical $l_{\max}$ range. For the on-site contraction this is pre-asymptotic, giving way to $L^3$ at large $l_{\max}$. For message passing it is structural and the runtime is memory-bandwidth bound on $L^2$-sized grid tensors. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.15099 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.15099v1 Announce Type: new Abstract: Classifying interactions is key in the physical sciences, and bonding mechanisms in matter-antimatter systems remain particularly enigmatic. Here we focus on a paradigmatic example of positronium hydride (PsH) dimer composed of two protons, two positrons, and four electrons, whose bonding nature has been previously described as either ionic, covalent, or van der Waals-like. Accurate quantum Monte Carlo calculations show that the two positrons occupy a delocalized molecular orbital that envelopes the two hydrogen anions and responds as a collective dipole to an applied electric field. This positronic bonding stems from quantum correlations that resemble a single covalent bond formed between negatively charged pseudo-nuclei, but with a bond strength commensurate with the traditional van der Waals interaction. Our findings suggest that the ability to form delocalized proto-bonds is a more general property of quantum systems, and could be present in a broader class of particles, antiparticles, and quasi-particles interacting with matter. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.14974 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14974v1 Announce Type: new Abstract: Chemistry's rules carry exceptions: the octet rule, Hess's Law, detailed balance, orbital symmetry selection rules, all with disclaimers memorised separately. Their cause: a question from a richer structural level posed in the vocabulary of a simpler one, i.e. level incompleteness. This monograph makes the levels explicit, constructing a canonical tower of nine categorical levels from stoichiometry through thermochemistry, equilibrium, kinetics, electron-pushing mechanisms, stereochemistry, potential energy surfaces, and electronic structure to all-particle quantum mechanics. Each level emerges from pairs of reactions distinct yet indistinguishable at the previous level; the minimal extension resolving each ambiguity is provably unique, certified by a non-trivial cokernel in an automorphism exact sequence, and recovers Feinberg's deficiency theorems as homological corollaries. A perpendicular dimension: every ML model for chemistry (yield predictors, neural kinetic networks, equivariant force fields, learned wavefunctions) is a morphism in the Para-enrichment of one tower level, with equivariance and thermodynamic consistency as universal properties. Three incompleteness results (Eyring, Wegscheider, topological output gaps) apply to the current literature. The framework descends to code: an operational functor from a Para-enriched product of the first four levels into the Kleisli category of the probabilistic sub-monad of Haskell IO, instantiated as a simulator of the Briggs-Rauscher oscillating reaction: the first Kleisli semantics of Gillespie's next-reaction method and first Para application outside ML. The passage to all-particle quantum mechanics, Born-Oppenheimer as the classical limit of a continuous field of C*-algebras, remains the deepest open construction; four candidate conjectures including Woolley-Primas have obstructions the framework makes specific. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.14973 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14973v1 Announce Type: new Abstract: We present THEMol (Torsion, Hessian, Energy of Molecules), a massive open-source collection of quantum mechanical properties tailored for closed-shell organic molecules, with up to 50 heavy atoms. THEMol includes a Hessian subset with more than 3 million relaxed geometries with Hessian matrices, a TorsionScan subset with nearly 100 million constrained relaxed geometries with energies and forces, and relaxation-trajectory subsets (HessianRelax and TorsionScanRelax) that together comprise about 3 billion DFT calculations. The chemical space sampling is comprehensive, spanning twelve essential elements and diverse molecular architectures relevant to drug discovery, electrolytes, ionic liquids, and beyond. The dataset also features exhaustive conformational sampling through the TorsionScan and TorsionScanRelax subsets, including comprehensive in-ring and non-ring torsional scans. Furthermore, it contains an extensive library of Hessian matrices, computed at relaxed geometries, to capture critical second-derivative information of the potential energy landscape. Additionally, we supply electron density-derived atomic multipoles computed via the Minimal Basis Iterative Stockholder partition scheme. Organized into five distinct subsets (Hessian, TorsionScan, HessianRelax, TorsionScanRelax, and MBIS), the data encompasses optimized geometries, relaxation trajectories, and derived molecular properties. We anticipate that this massive and diverse dataset will significantly empower the development of highly accurate and transferable molecular potentials. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.14826 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14826v1 Announce Type: new Abstract: Solid mineral-based particles have been proposed as alternatives to sulfates for climate intervention by stratospheric aerosol injection, as a means for improving optical or chemical characteristics and thereby minimize risks and uncertainties. However, the heterogeneous reactivity of solid particles with stratospheric trace gases, and possible implications to the ozone layer, is currently not fully constrained, particularly at stratospheric concentrations. We present a systematic comparative study of the uptake of HNO3, HCl, and NO2 on calcite, alumina, crystalline silica (quartz), and amorphous silica, using complementary Knudsen cell and flow reactor techniques. We find that NO2 uptake is weak on all surfaces, with estimated removal timescales indicating negligible impact on stratospheric nitrogen chemistry. Conversely, HCl uptake is substantial, with a pronounced concentration dependence consistent with surface site limited Langmuir adsorption. Extracting adsorption isotherms, we find that HCl surface coverage at stratospheric concentrations differs by four orders of magnitude between the surfaces, with calcite adsorbing the most and amorphous silica the least, suggesting a dominant role of surface acid-base character. Using HCl surface coverage as a proxy for ClONO2 reactive uptake, we estimate that amorphous silica could deplete substantially less ozone than calcite or alumina under equivalent injection scenarios. We find a marked difference between crystalline and amorphous silica, underscoring the sensitivity of heterogeneous chemistry to surface microstructure and the importance of selecting particles with low-reactivity surfaces in addition to considering bulk characteristics. Our findings motivate the development of particles with surfaces tailored for minimizing SAI risks and uncertainties, including minimal reactivity with stratospheric gases and background sulfate aerosols. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.14617 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14617v1 Announce Type: new Abstract: Full-dimensional reactive potential energy surfaces (PESs) for the OCS$^+$ cation are constructed to describe S$^+$ loss in the electronic ground state and seven low-lying electronically excited states. High-level \textit{ab initio} reference energies were computed at the MRCI+Q/aug-cc-pVTZ level and were used to generate PESs employing reproducing kernel Hilbert space representations (RKHS). The PESs accurately reproduce the measured dissociation limits to CO(X$^1\Sigma^+$)+S$^+$ in different electronic states. The topology of the PESs reveals multiple linear and T-shaped minima, pronounced angular anisotropy, and state-crossing manifolds. Exploratory quasi-classical trajectory simulations on selected PESs confirm numerical stability and energy conservation, illustrating the suitability of the surfaces for dynamical applications. The present work represents the most comprehensive characterization to date of the lowest PESs of OCS$^+$ and provides a reliable foundation for future studies of the photodissociation of OCS$^+$ and the chem-ionization dynamics of OCS. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.14611 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14611v1 Announce Type: new Abstract: We present a flexible, automated, and basis-set insensitive domain-based charge-transfer (CT) decomposition framework that can be combined with any CI-type excited-state wavefunction. Our approach is not based on excited-state densities and allows the excited-state character to be dissected into local and domain-based CT excitations and measures the individual contributions to each excited state. To guarantee a broad applicability, we introduce two domain-accumulation strategies to translate hole-particle substitutions to domain-domain excitations: a strict domain partitioning and a weighted approach suitable for small molecules and a large number of domains. The performance of both schemes is assessed for inter- and intramolecular CT excitations and various basis sets using EOM-CCSD and its simplified counterpart EOM-pCCD+S. Most importantly, the CT character is, to a large extent, basis-set independent, and both domain-accumulation schemes give consistent results. Overall, our framework provides a robust CT analysis and a domain resolution of the excitation character for a variety of computational setups and excited-state models. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.14608 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14608v1 Announce Type: new Abstract: In this paper, we study the effective rank of the canonical polyadic decomposition applied to the electron repulsion integrals, ubiquitous in quantum chemistry. We demonstrate, both mathematically and numerically, that in general the effective rank of this decomposition cannot grow linearly as a function of the system size. Moreover, we derive a lower bound for the effective rank in the form $\propto N_{\mathrm{AO}}^2/\log_2^7 N_{\mathrm{AO}}$, where $N_{\mathrm{AO}}$ is the number of atomic orbitals in the molecule, under mild conditions imposed on the decomposition threshold $\epsilon$. As a result, while a subquadratic growth of the CPD rank is not excluded, a linear relationship between the rank and $N_{\mathrm{AO}}$ cannot hold universally. The implications of these findings for the use of the canonical polyadic format to represent electron repulsion integrals in quantum chemistry are analyzed. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.14584 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14584v1 Announce Type: new Abstract: Implicit solvent models are widely used to decrease the number of solvent degrees of freedom and enable the calculation of solvation energetics without water molecules. However, its accuracy often falls short compared to explicit models. Recent advancements in neural potentials have shown promise in drug discovery, but transferability remains a persistent challenge. Here, we introduce the Protein Hydration Neural Network (PHNN), an implicit solvent model that extends analytical continuum solvation by learning transferable corrections to model parameters instead of applying post hoc adjustments to final energies. The model is explicitly designed to maximize data efficiency by leveraging physical priors embedded in the data. We demonstrate that PHNN improves accuracy relative to traditional analytical methods and maintains predictive accuracy on out-of-domain protein systems. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.14287 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14287v1 Announce Type: new Abstract: Conical intersections play central roles in photoinduced reactions. However, comprehensive conical-intersection datasets that could advance our understanding of excited-state reaction processes remain scarce. To address this gap, we constructed a quantum chemistry dataset containing ground-state and conical-intersection structures of small molecules (up to ten heavy atoms: C, N, O, F). Ground-state geometries were optimized at the semi-empirical OM2 level, with single-point energies calculated at the OM2/MRCI level. Conical-intersection geometries and energies were also computed at the OM2/MRCI level. This dataset is designed to enable a deep integration of photochemistry with machine learning, bridging the gap between photochemical insight and data-driven approaches. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.13927 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.13927v1 Announce Type: cross Abstract: The striking variety of macroscopic morphologies displayed by bacterial colonies depends on microscopic environmental and behavioural details in a manner that is currently not well understood. A surprising example is sibling inhibition, whereby isogenic bacterial colonies spreading in soft agar hydrogels tend to avoid each other and form sharp demarcation lines when growing nearby. Here we investigate this effect with the common pathogen \textit{Pseudomonas aeruginosa}, by combining quantitative density measurements with a minimal biophysical model. Our results show that the phenomenon does not depend on gel compression, lethal inhibition or quorum sensing-dependent cell communication. Instead, colony separation is driven by localised nutrient depletion through a dynamic feedback between growth and motility. The model, which is calibrated using experimental data, captures key observations including the dependence of inhibition strength on the initial nutrient concentration. This work establishes nutrient availability and non-lethal motility inhibition as central factors underlying sibling inhibition, providing a generalisable framework for microbial spatial dynamics with implications for understanding bacterial interactions in tissues, soils and engineered microbiomes. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2512.12882 Fri, 15 May 2026 00:00:00 -0400 arXiv:2512.12882v4 Announce Type: replace Abstract: We calculate the parity non-conserving (PNC) electric-dipole ($E1$) transition amplitudes for the $5s - 6s$ and $5s - 4d_{3/2}$ transitions in Rb and Sr$^+$. Our results include both the nuclear-spin-independent and nuclear-spin-dependent contributions, with particular emphasis on the potential effects of a hypothetical additional $Z'$-boson. We highlight possible advantages of using light atoms in searches for such new interaction. The ratio of the contribution of a low mass $Z'$-boson to the contribution of the Standard model $Z$ -boson to PNC effects increases rapidly (faster than $1/Z^2$) with decreasing nuclear charge $Z$. Another advantage is that theoretical interpretations of experiments in lighter systems may be carried out with a higher accuracy than that in Cs, Ba$^+$, Fr and Ra$^+$. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2107.11229 Fri, 15 May 2026 00:00:00 -0400 arXiv:2107.11229v2 Announce Type: replace Abstract: We report a measurement of the radiative lifetime of the $^2F_{7/2}$ level of $^{171}$Yb$^+$ that is coupled to the $^2S_{1/2}$ ground state via an electric octupole transition.The radiative lifetime is determined to be $9.96(50)\times 10^7$~s, corresponding to 3.16(16) years. The result reduces the relative uncertainty in this exceptionally long excited state lifetime by one order of magnitude with respect to previous experimental estimates. Our method is based on the coherent excitation of the corresponding transition and avoids limitations through competing decay processes. The explicit dependence on the laser intensity is eliminated by simultaneously measuring the resonant Rabi frequency and the induced quadratic Stark shift. Combining the result with information on the dynamic differential polarizability permits a calculation of the transition matrix element to infer the radiative lifetime. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.15087 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.15087v1 Announce Type: cross Abstract: Nondestructive detection of single-electron motion is crucial for quantum information processing with electrons trapped in Paul traps. The standard approach in Penning traps is to detect the image current induced on the trap electrodes by the electron's oscillatory motion. However, applying this approach in Paul traps for single electrons is currently hindered by motional frequency fluctuations arising from trap anharmonicities and instabilities in the rf trapping field. In this work, we propose a robust detection scheme exploiting the transient dynamics of parametric driving to overcome these limitations. Distinct from traditional steady-state approaches, our method focuses on the transient regime to break the temporal constraints imposed by steady-state assumptions, thereby enabling fast readout. We show that a controlled ramp of the parametric drive effectively locks the frequency of the electron motion in the transient regime, rendering the signal highly resilient to realistic experimental noise and inherent micromotion. This work paves the way for the experimental realization of nondestructive detection of single-electron motion in Paul traps. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.14529 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14529v1 Announce Type: cross Abstract: Rydberg atomic electrometry leverages the extreme sensitivity of highly excited atoms for calibration-free electric field measurements. The technique uses a non-metallic vapor cell to link properties of an RF field to a spectroscopic readout in the optical domain. Most demonstrations have so far focused on detecting linearly-polarized fields, for which the induced splitting of dressed atomic levels is rotationally invariant. Here we report on Rydberg atomic measurements of RF fields in a general state of polarization (SOP) which we map onto the Poincar\'{e} sphere through spectroscopic fingerprints. For a Stokes vector circumnavigating a Poincar\'e sphere meridian, we witness a continuous transformation of the atomic eigenenergy spectrum. Because the relative positions of eigenenergies are locked in place by quantization of angular momentum, the framework is universal and calibration free. We provide a specific demonstration in rubidium, which generalizes to all systems with a single valence electron. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.14279 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14279v1 Announce Type: cross Abstract: Atom interferometers represent a promising approach for gravitational wave detection in the decihertz frequency band, complementary to existing light-based detectors. The South Pole offers unique advantages for such experiments: exceptionally low seismic noise, established infrastructure for large scientific projects, and a location that strengthens gravitational wave source localization through global triangulation. Here we discuss the scientific case and practical considerations for deploying a long-baseline atom interferometer at the South Pole, which has the potential to expand the global network of gravitational wave detectors while enabling precision tests of fundamental physics. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.14188 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14188v1 Announce Type: cross Abstract: What does a book look like to a quantum computer? This paper takes eight classical works of the Renaissance and its late-antique inheritance -- from Augustine to Galileo -- and runs each through a neutral-atom quantum processor. The bridge is graphs: each textual unit becomes an atom, and graph edges are physical blockade constraints for engineered exact unit-disk designs, or a 2D approximation to the semantic graph for natural texts. Three contributions follow. First, we introduce rigidity rho, a metric for how unique a book's structural backbone is -- distinguishing Marguerite de Navarre's Heptameron (rigid, twelve-nouvelle hard core) from Boethius (fully fungible, every chapter substitutable). Second, we invert the pipeline: rather than extracting a graph from existing prose, we pick a target graph the hardware encodes natively, and write a book whose structure matches it. The twenty-nine texts written this way, collected under the name QOuLiPo, extend the OuLiPo tradition to graph-topological constraints and, together with the eight natural texts, form a benchmark distribution against which neutral-atom hardware can be tracked as it scales. Third, we run both natural and engineered texts on Pasqal's FRESNEL processor up to one hundred atoms; engineered texts reach high approximation ratios, the cleanest instances returning the exact backbone. A cloud-accessible quantum machine plus an agentic coding environment now lets a single investigator run this pipeline end-to-end. What is reported is an application layer, not a speedup -- humanistic instances ready to load onto neutral-atom processors as they scale, already complementing classical text analysis. The Digital Humanities community has a stake in building familiarity with this hardware now: the engineered-corpus design choices made today fix the benchmark distribution future hardware will be measured against. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.14181 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14181v1 Announce Type: cross Abstract: We investigate the suppression of matter-wave Talbot interference under environmentally induced decoherence. The system is modeled as an atomic beam diffracted by a periodic grating, whose transverse dynamics is described within the paraxial approximation. Environmental coupling is introduced through an effective open-system model that exponentially damps spatial coherences between diffracted components, allowing a continuous interpolation between the coherent Talbot regime and the incoherent far-field diffraction limit. Besides the usual intensity and transverse-momentum distributions, we analyze the local probability flow associated with the diffracted matter wave. The corresponding Bohmian, or hydrodynamic, representation is used here as a diagnostic tool fully equivalent to the standard quantum description, with no additional assumptions beyond the probability current of the paraxial wave field. In the present Talbot geometry, this analysis shows how decoherence progressively suppresses the carpet structure and smooths the transverse-momentum distribution, while the flow may remain organized into channels determined by the grating periodicity. The results illustrate, in a periodic matter-wave Talbot geometry, that the loss of visible interference and the loss of dynamical pathway separation need not occur simultaneously. In particular, flux-channel structures can persist in parameter regimes where multi-slit interference features have already been strongly reduced. This distinction provides a local characterization of decoherence in matter-wave Talbot interferometry and complements previous trajectory-based analyses of coherence loss in simpler interference and confined geometries. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.15121 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.15121v1 Announce Type: new Abstract: The possibility of laser cooling and the presence of closely spaced rovibrational doublets make polyatomic molecules an attractive platform for the $\mathcal{P}$, $\mathcal{T}$-violation searches. We study the spectrum of the lowest rovibrational state of the AcOCH$_3+$ symmetric top molecule. The electronic structure full-electron computation was performed within a relativistic coupled cluster method with double and perturbative triple excitations. The rovibrational wavefunctions are obtained using a coupled channel technique, taking into account all rovibrational effects and anharmonicities of the potential. As a result, the vibrational frequencies, as well as the values of the electric dipole moments for the rovibrational states, were computed. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.14993 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14993v1 Announce Type: new Abstract: Rydberg atoms provide a powerful platform for exploring strongly interacting quantum systems, both in free space and in structured electromagnetic environments, with growing applications in quantum technology. Accurately modeling their single-atom properties and mutual interactions is essential for interpreting experiments and designing new architectures. We present a unified theoretical framework for Rydberg atoms and their interactions based on multi-channel quantum defect theory (MQDT) and static electromagnetic Green's tensors. MQDT provides a precise description of Rydberg states of divalent atoms such as strontium and ytterbium, while the Green's tensor formalism provides a general and flexible approach for calculating interactions between two Rydberg atoms in arbitrary geometries, including modifications induced by nearby surfaces. We implement this framework in an updated version of the open-source PairInteraction software [Weber et al., J.~Phys.~B~50 (2017)]. The implementation leverages high-performance libraries and achieves speedups of one order of magnitude for pair-potential calculations compared to prior software. We demonstrate the capabilities of the framework through example applications to divalent atoms and show excellent agreement with experimental data for an exemplary Stark map of $^{174}$Yb. The modular software architecture enables the community to extend it further. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2603.24320 Fri, 15 May 2026 00:00:00 -0400 arXiv:2603.24320v3 Announce Type: replace-cross Abstract: Control over crystallographic orientation in metal-organic framework (MOF) thin films is crucial for exploiting their anisotropic properties in sensing, catalysis, and separation. Achieving reproducible, highly oriented films remains challenging, especially for mixed-linker, pillared-layered frameworks. Here we present an automated, spin-assisted layer-by-layer liquid-phase epitaxy (LbL-LPE) strategy that enables rapid, ambient-condition fabrication of highly oriented, mixed-linker MOF thin films, demonstrated for Zn2BDC2DABCO (BDC = terephthalate, DABCO = 1,4-diazabicyclo[2.2.2]octane). Correlative process monitoring by grazing-incidence wide-angle X-ray scattering (GIWAXS), grazing-angle infrared (GI-IR) and UV-Vis spectroscopy, contact-angle measurements, scanning electron microscopy (SEM), and time-of-flight secondary ion mass spectrometry (ToF-SIMS) ensure formation of uniform films with exceptional out-of-plane (001) orientation (degree of orientation >85%, Hermans parameter ~0.95) and excellent reproducibility. This strategy enables highly reproducible, high-throughput fabrication of orientation-controlled MOF thin films, providing a generalizable alternative to conventional LbL approaches. By enabling reproducible and entirely automated fabrication of highly anisotropic architectures, this work establishes a platform for integrating oriented MOFs into next-generation optoelectronic, sensing, and membrane devices where directional transport and ordered pore alignment are essential. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.15123 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.15123v1 Announce Type: new Abstract: Efficient and selective excitation of lattice vibrations is central to controlling energy flow at the nanoscale, yet remains challenging under conventional optical excitation. Here, we introduce a mid-infrared-assisted phonon amplification approach, termed MIRAPA, that enables efficient energy injection directly into vibrational bonds. Using surface-enhanced resonant Raman scattering in few-layer $\mathrm{MoS_2}$, we exploit strong exciton--phonon coupling to monitor phonon populations. When mid-infrared (MIR) light is introduced, it couples directly to out-of-plane lattice vibrations, leading to room-temperature phonon amplification exceeding $80\%$. Crucially, MIRAPA bypasses electronic excitation pathways, allowing the MIR power density to be nearly $300\times$ lower than that required for visible excitation to achieve comparable enhancement. The resulting phonon modulation is robust, persisting over more than $2800$ on/off cycles and exceeding $15$ hours of continuous-wave laser illumination without degradation. Quantitative analysis yields an effective noise-equivalent power of approximately $0.3\,\mathrm{nW}/\sqrt{\mathrm{Hz}}$ for MIR detection, highlighting the sensitivity of the approach. By combining vibrational selectivity, low-power operation, and long-term stability, MIRAPA provides a robust platform for probing and amplifying phonons in two-dimensional semiconductors. These results open new opportunities for nanoscale vibrational sensing, mid-infrared detection, and phonon-based coherent devices, including routes toward phonon lasing. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.14942 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14942v1 Announce Type: new Abstract: The use of mobile robotics in radioactive source seeking has become an important part of modern radiation-safety practices, supporting timely mitigation of contamination risks and helping protect public health. However, measuring radiation is often time-consuming, rendering traditional gradient-based source-seeking methods less effective due to lower sample efficiency. This paper proposes a sample-efficient Bayesian-Optimisation source-seeking strategy that utilises a heteroscedastic Gaussian process surrogate to balance exploration and exploitation. Excessive inter-sample travel is discouraged through a movement switching cost. The strategy is shown to generate sublinear regret in the source-seeking task, while simulations demonstrate its effectiveness in localising radioactive sources. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.14316 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14316v1 Announce Type: new Abstract: Superconducting nanowire single-photon detectors (SNSPDs) have demonstrated timing jitter in the few-picosecond regime, yet their timing resolution deteriorates substantially under high-count-rate operation. Existing interpretations mainly attribute this degradation to deterministic waveform distortions, such as multiphoton responses and pulse pile-up, yet the experimentally observed jitter broadening at high count rates cannot be fully accounted for within this picture. Here, we show that stochastic baseline fluctuations arising from finite-memory readout dynamics constitute an intrinsic source of the count-rate-dependent timing jitter in SNSPD systems. For stochastically arriving photons, overlapping recovery responses accumulate in the readout chain and generate statistically fluctuating baselines, which are converted into timing uncertainty through threshold-based timing extraction. We develop a stochastic-process framework that quantitatively connects photon statistics, readout dynamics, and timing jitter. The framework predicts characteristic scaling behaviors, including a nonmonotonic dependence of baseline fluctuations under pulsed excitation with a maximum near half of the repetition frequency. These predictions are quantitatively verified through systematic variations of count rate, circuit time constant, and detector dynamical properties. Our results identify stochastic baseline dynamics as a fundamental mechanism limiting timing resolution in high-count-rate SNSPD operation and provide a general framework for optimizing finite-memory high-speed photon-counting systems. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.03646 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.03646v3 Announce Type: replace-cross Abstract: Turbophoresis in inhomogeneous turbulent flows leads to the formation of large-scale nonuniform particle number density distributions of inertial particles. This effect is associated with an effective drift velocity directed toward regions of lower turbulence intensity and proportional to the particle Stokes time and the spatial gradient of the turbulence intensity. In the present study, turbophoretic transport is experimentally investigated in air flows generated by one-grid and two-grid oscillating turbulence systems. The flow velocity field and particle spatial distribution are measured using Particle Image Velocimetry. To isolate the effect of particle accumulation due to turbophoresis from that associated with mean fluid flow, the measured particle number density of inertial particles is normalized by the corresponding distribution obtained for noninertial tracer particles under identical flow conditions. The measurements show preferential accumulation of inertial particles in regions of lower turbulence intensity, consistent with the expected behavior of turbophoretic transport. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2601.21151 Fri, 15 May 2026 00:00:00 -0400 arXiv:2601.21151v2 Announce Type: replace-cross Abstract: Recent machine-learning approaches to weather forecasting often employ a monolithic architecture in which distinct physical mechanisms-advection (long-range transport), diffusion-like mixing, thermodynamic processes, and forcing-are represented implicitly within a single large network. This is particularly problematic for advection, where long-range transport typically requires expensive global interaction mechanisms or deep stacks of local convolutional layers. To mitigate this, we present PARADIS, a physics-inspired global weather prediction model that enforces inductive biases on network behavior through a functional decomposition into advection, diffusion, and reaction blocks acting on latent variables. We implement advection through a Neural Semi-Lagrangian operator that performs trajectory-based transport via differentiable interpolation on the sphere, enabling end-to-end learning of both the latent modes to be transported and their characteristic trajectories. Diffusion-like processes are modeled by depthwise-separable spatial mixing, whereas local source terms and vertical interactions are handled via pointwise channel interactions, yielding a physically structured operator decomposition. Evaluated on ERA5 benchmarks, PARADIS achieves competitive deterministic forecast skill, with particularly strong short-lead performance, while preserving substantially better spectral fidelity and forecast activity during medium-range rollouts. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2512.14898 Fri, 15 May 2026 00:00:00 -0400 arXiv:2512.14898v2 Announce Type: replace Abstract: Long Short-Term Memory (LSTM) models are trained to predict forecast errors for the High-Resolution Rapid Refresh (HRRR) model using the New York State Mesonet and Oklahoma State Mesonet near-surface weather observations as ground truth. When evaluated using mean-absolute-error and percent improvement relative to the HRRR, LSTMs predict precipitation error most accurately, providing, on average, a 48% improvement relative to the HRRR forecast, followed by wind error, providing, on average, a 15% improvement, and then temperature error, providing, on average, a 25% improvement. Precipitation errors exhibit an asymmetry, with overforecast precipitation detected more accurately than underforecast, while wind error predictions are consistent across over- and underforecast predictions. Temperature error predictions are relatively accurate but smoother, with respect to variance, than true observations. This paper describes an overview of LSTM performance with the expressed intent of providing forecasters with real-time predictions of forecast error at the point of use within the New York State and Oklahoma State Mesonets. In practice, the predicted errors can be used to adjust deterministic HRRR forecasts at the point of use, identify locations and variables with elevated uncertainty, and provide supplemental guidance for high-impact decision-making. This research demonstrates the potential of LSTM-based machine learning models to provide actionable, location-specific predictions of forecast error for high-resolution operational numerical weather prediction (NWP) systems. However, model performance is variable-dependent, and the approach relies on the availability of dense mesonet observations, which may limit applicability in data-sparse regions. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.14317 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14317v1 Announce Type: cross Abstract: Extreme precipitation causes severe societal and economic damage, and weather control has long been discussed as a potential mitigation strategy. However, to the best of our knowledge, perturbation-based interventions for weather control using data-driven weather forecasting models have not yet been explored. While adversarial attacks also generate perturbations that alter forecasts, they aim to exploit model artifacts and do not account for physical plausibility. In this paper, we propose a gradient-based guidance framework for precipitation-reduction interventions through diffusion sampling in diffusion-based weather forecasting models. Instead of directly perturbing atmospheric states, our method steers the diffusion sampling trajectory, enabling precipitation reduction while maintaining consistency with the atmospheric distribution. To assess physical plausibility, we evaluate from three perspectives: (i) vertical and variable-wise perturbation profiles, (ii) latent-space trajectory deviation, and (iii) cross-model transferability. Experiments on extreme precipitation events from WeatherBench2 demonstrate that our method achieves effective precipitation reduction while yielding more physically plausible interventions than adversarial perturbations. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.14947 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14947v1 Announce Type: new Abstract: Stratospheric aerosol injection (SAI) is a solar radiation modification technique, proposed as an interim measure to offset warming while greenhouse gas (GHG) emissions are reduced. This paper discusses a possible SAI implementation route - an alternative to sulfate aerosols formed in situ - based on engineered solid particles having dedicated properties such as size, composition, surface chemistry, and traceable origin, supporting safety, controllability, and functionality needed for SAI systems. These engineered properties also open up options for any future multi-state coordination of SAI through two technical building blocks: (1) the SAI-induced radiative forcing (SRF) - the magnitude of the cooling effect attributable specifically to the SAI layer - as an operator-independent quantity, derivable from direct aerosol-layer measurements; and (2) particle traceability through identifying signatures embedded at production. Both could feed into a shared, publicly accessible monitoring database open to independent interrogation, addressing several governance challenges by anchoring compliance assessments in measurable parameters. Drawing on precedents from the Montreal Protocol, IAEA safeguards, and other regimes, we show that shared technical metrics have historically enabled multi-state cooperation, and we argue the same could apply to SAI. We describe a phased pathway in which the technical capabilities and coordination practices that would use them are developed and tested together, at scales orders of magnitude below operational deployment. To be clear - we regard SAI deployment as premature; the conditions under which it might be considered have not been met. The paper does not propose a governance framework; rather, it identifies technical infrastructure that could support a wide range of such frameworks. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.14426 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14426v1 Announce Type: new Abstract: Reliable precipitation monitoring is essential for disaster risk reduction, water resources management, and agricultural decision-making. Multi-source satellite observations, particularly the combination of geostationary infrared and passive microwave measurements, have become a primary means of precipitation detection. Traditional multi-source satellite precipitation estimation methods remain computationally inefficient, and many deep learning methods lack the flexibility to incorporate new sensors without retraining the full model. Here we introduce PRISMA (Precipitation Inference from Satellite Modalities via generAtive modeling), a plug-and-play latent generative framework for multi-sensor precipitation estimation. PRISMA learns an unconditional precipitation prior from IMERG Final fields and constrains it through independently trained, sensor-specific conditional branches, allowing new observation sources to be incorporated without retraining the generative backbone. Applied to FY-4B AGRI infrared and GPM GMI microwave observations, PRISMA improves Critical Success Index by up to 40.3% and reduces root-mean-square error by 22.6% relative to infrared-only estimation within microwave swaths, while also improving probabilistic skill and maintaining an average inference time of about 37 s. Independent rain-gauge validation across China confirms consistent gains, and typhoon case studies show that microwave conditioning restores eyewall and spiral rainband structures, reducing storm-core mean absolute error by up to 42.3%. PRISMA thus provides an extensible and efficient framework for multi-sensor precipitation estimation. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.12558 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.12558v2 Announce Type: replace Abstract: Objective. Hypoxic tumor subvolumes resist radiation through elevated oxygen enhancement ratios (OER), yet no computational OER model is simultaneously particle-specific, mechanistically grounded, and fast enough for voxel-scale treatment planning. We present the VOxel-Aware Oxygen Model (VOxA) to address all three requirements. Approach. An Oxygen Model (OM) encodes particle-specific LET-OER dependence through dual sigmoidal transitions constrained to increase monotonically with atomic number Z, combined with Michaelis-Menten oxygen kinetics. A Voxel-Aware (VA) extension resolves per-DSB local energy heterogeneity via a calibrated particle-specific sensitivity parameter. Calibrated on 233 OER observations from 29 sources across 10 particle types (LET = 0.2-654 keV/um); DSB coordinates from TOPAS-nBio simulations. Main results. The OM achieves $R^2 = 0.719$ and MAE = 0.300 retention OER units; theoretical OER maximum 3.32 (2.4% from measurement), bootstrap median 3.37 [3.18, 4.09]. The composite $K_{\rm fix} + K_{\rm repair} = 2.82$ mmHg is tightly constrained despite high collinearity (r = 0.935). On the Furusawa heavy-ion subset, VOxA achieves 28.4% lower survival OER MAE than the clinical standard (63.1% on helium, 24.0% on carbon) and reproduces He < C < Ne Z-ordering that universal models cannot capture. The VA extension passes 18 tests confirming sample-size-invariant within-nucleus coefficient of variation of the per-DSB retention probability. VOxA evaluates in under $10^{-3}$ ms per voxel, more than $10^6$ times faster than Monte Carlo chemistry. Significance. VOxA is the first particle-specific OER model to reproduce Z-ordering analytically at clinical planning speed, validated on the largest OER calibration dataset for this model class. Committed-break coordinates at whole-nuclear scale provide the input for inter-break topological analysis and hypoxic LET painting. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.14218 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14218v1 Announce Type: cross Abstract: The key problem facing ChatGPT-like AI's use across society is that its behavior can shift, unnoticed, from desirable to undesirable -- encouraging self-harm, extremist acts, financial losses, or costly medical and military mistakes -- and no one can yet predict when. Shifts persist in even the newest AI models despite remarkable progress in AI modeling, post-training alignment and safeguards. Here we show that a vector generalization of fusion-fission group dynamics observed in living and active-matter systems drives -- and can forecast -- future shifts in the AI's behavior. The shift condition, which is also derivable mathematically, results from group-level competition between the conversation-so-far (C) and the desirable (B) and undesirable (D) basin dynamics which can be estimated in advance for a given application. It is neither model-specific nor driven by stochastic sampling. We validate it across six independent tests, including: 90 percent correct across seven AI models spanning two orders of magnitude in parameter count (124M-12B); production-scale persistence across ten frontier chatbots; and a priori time-stamped prediction eleven months before the Stanford 'Delusional Spirals' corpus appeared, and independently confirmed by that corpus of 207,443 human-AI exchanges. Because it sits architecturally below the current safety stack, the same formula provides a real-time warning signal that current alignment does not supply, portable across current and future ChatGPT-like AI architectures and instantiable in application domains where competing response classes can be defined. Physics/physics.soc-ph_(Physics_and_Society) https://arxiv.org/abs/2601.18895 Fri, 15 May 2026 00:00:00 -0400 arXiv:2601.18895v4 Announce Type: replace Abstract: People often express opinions that differ from their privately held views, a phenomenon known in economy as preference falsification. Expressed-private opinion (EPO) models capture this by assigning each agent two dynamical variables: a private (internal) and an expressed (external) opinion. Within the nonlinear $q$-voter model, two EPO variants have been studied so far: with and without self-anticonformity. In both formulations, agents update private and expressed binary opinions, one after another and at the same rate, which has led to two update schemes studied previously: AT (act then think), in which an agent first updates its expressed and then its private opinion, and TA (think then act), in which the order is reversed. To eliminate this ad hoc distinction and quantify the interplay between private and expressed opinions, we introduce the $\alpha$-EPO $q$-voter model with asynchronous updating -- in each elementary step, an agent updates its private opinion with probability $\alpha$ or its expressed opinion with complementary probability $1-\alpha$. We derive mean-field theory and, for the first time for EPO $q$-voter dynamics, a pair approximation, and validate them with Monte Carlo simulations on artificial and real organizational networks. Comparing the two model variants, we show that the collective outcome controlled by $\alpha$ strongly depends on self-anticonformity: with self-anticonformity the results are robust to $\alpha$, whereas without it $\alpha$ shifts the agreement-disagreement threshold and can change the type of phase transition. In the mean-field limit this change occurs only for $q=3$, but the pair approximation reveals an additional low-connectivity regime in which both $\alpha$ and the average degree $k$ control the emergence and width of hysteresis also for larger influence groups. Physics/physics.soc-ph_(Physics_and_Society) https://arxiv.org/abs/2605.13979 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.13979v1 Announce Type: new Abstract: Quantum machine learning (QML) aims to accelerate machine learning tasks by exploiting quantum computation. Previous work studied a QML algorithm for selecting sparse subnetworks from large shallow neural networks. Instead of directly solving an optimization problem over a large-scale network, this algorithm constructs a sparse subnetwork by sampling hidden nodes from an optimized probability distribution defined using the ridgelet transform. The quantum algorithm performs this sampling in time $O(D)$ in the data dimension $D$, whereas a naive classical implementation relies on handling exponentially many candidate nodes and hence takes $\exp[O(D)]$ time. In this work, we construct and analyze a quantum-inspired fully classical algorithm for the same sampling task. We show that our algorithm runs in time $O(\operatorname{poly}(D))$, thereby removing the exponential dependence on $D$ from the previous classical approach. Numerical simulations show that the proposed sampler achieves empirical risk comparable to exact sampling from the optimized distribution and substantially lower than sampling from the non-optimized uniform distribution, while also exhibiting exponentially improved runtime scaling compared with the conventional classical implementation. These successful dequantization results show that sparse subnetwork selection via optimized sampling can be achieved classically with polynomial data-dimension scaling on conventional computers without quantum hardware, providing an alternative to the existing quantum algorithm. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.13980 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.13980v1 Announce Type: new Abstract: Solving non-linear Diophantine systems lies at the mathematical core of integer optimization and cryptography. While the general unbounded problem is undecidable, even over bounded integer domains it remains classically intractable in the worst case. In this work, we introduce a fully reversible quantum algorithmic framework tailored to solve arbitrary polynomial Diophantine equations over bounded integer domains. The core of our approach is the explicit, gate-level synthesis of an evaluation oracle for amplitude amplification. By coherently evaluating polynomial constraints via in-place two's complement arithmetic and routing operations into a single recycled accumulator, this garbage-free strategy achieves a compact and scalable synthesis of the underlying non-linear arithmetic. Through analytical derivations and empirical circuit simulations, we prove that the overall spatial complexity is bounded by $q = \mathcal{O}((n + d^2)\log_2 N)$ logical qubits for $n$ variables, maximum degree $d$, and interval length $N$. The non-Clifford Toffoli depth is upper-bounded by $\mathcal{O}(q^2)$. This structural scaling exponent remains invariant to the variable count, modulated linearly only by the coefficients' Hamming weights. By moving beyond abstract black-box assumptions, this explicit architectural synthesis guarantees that the necessary quantum arithmetic acts as a bounded polynomial overhead. This ensures a quadratic speedup over classical exhaustive search, whether retrieving a unique assignment or dynamically enumerating an unknown number of solutions. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14001 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14001v1 Announce Type: new Abstract: Quantum computing has demonstrated its potential to solve various optimization problems, including drone scheduling, which is important not only for drone delivery but also for logistics in general. However, one of the main obstacles is that practical drone scheduling settings typically require quantum resources that current hardware cannot provide. Therefore, in this work, we introduce a new Quantum Optimization via Coordinate Descent (QUACOD) approach to address this problem under the constraint of a limited number of available qubits. By leveraging coordinate descent, QUACOD decomposes the original high-complexity problem into multiple subproblems, which are then solved using quantum optimization. In our experiments, QUACOD outperforms the state-of-the-art (SOTA) quantum-based drone scheduling method not only in optimized drone completion times but also in scalability, handling up to 5 times more drones and 35 times more routes. In addition, QUACOD demonstrates that hardware-efficient circuits are effective for optimization problems. Together, these contributions advance quantum computing toward practical applications in the noisy intermediate-scale quantum (NISQ) era. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14042 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14042v1 Announce Type: new Abstract: Achieving practical quantum advantage on fault-tolerant quantum computers (FTQC) is fundamentally constrained by the substantial spatial and temporal overheads required to map logical operations onto physical hardware. Existing compilation approaches typically adopt coarse-grained, slice-based abstractions that overlook fine-grained microarchitectural effects, such as routing contention, leading to inefficient resource utilization and limited alignment between algorithm structure and hardware capabilities. This work presents a microarchitecture-aware compilation approach that integrates algorithmic structure directly with lattice surgery (LS) execution. By leveraging the commutativity of C-Phase operations, the method transforms inherently sequential gate sequences into concurrent multi-target interactions, effectively removing artificial dependencies and exposing significant instruction-level parallelism. To enable this, we design a dynamic, event-driven scheduling strategy that accurately models spatial layout and routing constraints, allowing operations to overlap in time while minimizing contention. Through improved coordination of computation and communication, this approach substantially reduces idle resources and achieves up to a 59.7$\times$ reduction in execution time compared to standard baselines. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14096 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14096v1 Announce Type: new Abstract: We introduce a framework where light-matter transitions, rather than states, are the primary dynamical objects. Successive compositions of elementary transitions yield multiphoton processes with compact diagrammatic bookkeeping of resonant and off-resonant pathways. This approach enables transparent derivations of effective high-order Hamiltonians in the dispersive regime, foundational to quantum-information applications. Applied to the paradigmatic Jaynes-Cummings model, our framework reveals a photon-number-independent intrinsic Rabi frequency and persistent polaritonic hybridization in the dispersive regime, unifying resonant and dispersive limits. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14100 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14100v1 Announce Type: new Abstract: We propose an adiabatic-elimination formalism in the dispersive regime based on a transition-centric perturbation theory. The perturbative expansion is recast into a diagrammatic framework, while adiabatic elimination is implemented through controlled projections onto transition subspaces. Our approach applies systematically at arbitrary perturbation order, and is suited to multilevel systems and multiple qubits in both cavity and waveguide quantum electrodynamics. It ultimately enables the explicit construction of effective higher-order Hamiltonians while bypassing important limitations of existing techniques, thereby providing a practical toolbox for multiphoton processes in the dispersive regime. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14256 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14256v1 Announce Type: new Abstract: We study distributed inner product estimation for $n$-qubit states using local randomized measurements, for which rigorous worst-case guarantees are less understood. We first reduce the minimax kernel optimization to Hamming-distance kernels. Within this class, unbiasedness fixes a unique kernel. For this kernel under local Clifford sampling, we prove a sharp fourth-moment bound using the single-qubit Clifford commutant. This yields worst-case sample complexity $\mathcal{O}(\sqrt{4.5^n})$, attained by identical pure product stabilizer states. For the same kernel under local Haar sampling, we prove a local twirling identity that compares its fourth moment with the Clifford fourth moment. This gives the same rigorous upper bound as in the Clifford case, but the comparison is lossy. This motivates the conjectured sharper Haar scaling $\mathcal{O}(\sqrt{3.6^n})$ attained by product states, and verify it for several important classes of states. We also show that independent single-qubit Pauli shadows have worst-case scaling $\mathcal{O}(\sqrt{7.5^n})$ for large $n$. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14293 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14293v1 Announce Type: new Abstract: Periodically driven quantum many-body systems can spontaneously break discrete time-translation symmetry, realizing discrete time crystals. To date, both experimental and theoretical efforts have largely focused on the simplest case of spontaneous period-doubling in $\mathbb{Z}_2$ discrete time crystals realized with qubits. This owes, in part, to the challenge of stabilizing eigenstate order in higher discrete symmetry ($\mathbb{Z}_n$) time crystals, due to the presence of richer domain wall physics. Here, we demonstrate the realization of a $\mathbb{Z}_3$ discrete time crystal by implementing a Floquet chiral clock model in a chain of 15 superconducting qutrits. Unlike the conventional Ising setting, our system features a tunable chiral angle that governs domain-wall dynamics, spectral degeneracies, and crucially, the stability of time-crystalline order. Using disordered nearest-neighbor chiral interactions, we observe robust subharmonic period tripling that persists across a wide range of drive strengths and is independent of initial state. Finally, we highlight the special role that chirality plays in our $\mathbb{Z}_3$ discrete time crystal -- in its absence, the system's Floquet dynamics exhibit a marked initial state dependence governed by domain wall degeneracies. Our results establish native qudit hardware as a powerful platform to access a broader landscape of non-equilibrium phases. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14299 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14299v1 Announce Type: new Abstract: Complex numbers play an indispensable role in quantum mechanics and quantum information, as validated by both theoretical analysis and experimental verification. Since quantum information processing inherently relies on quantum channels, the resource theory for quantum channels is equally fundamental to that for quantum states. In this paper, we propose two frameworks for quantifying the imaginarity of Gaussian channels. The first framework regards all real superchannels as free superchannels. Within this setting, we introduce two concrete imaginarity measures for Gaussian channels: I_s^GC based on existing imaginarity measures of Gaussian states, and I_d^GC derived directly from the intrinsic parameters of Gaussian channels, which enjoys high computational simplicity. The second framework adopts only a proper subset of real superchannels as free superchannels. Under this framework, we put forward another imaginarity measure I_c^GC , which is fully determined by the inherent parameters of Gaussian channels and features continuity as well as tractable computation. As a practical application, we employ I_c^GC to investigate the dynamical behavior of Quantum Brownian Motion Gaussian channels throughout the entire evolutionary process. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14314 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14314v1 Announce Type: new Abstract: Frequency modes of light are one of the most promising platforms that provide access to high-dimensional quantum states amongst different photonic degrees of freedom capable of high-dimensionality, enabling robust, error-tolerant, and scalable quantum optical information systems. We demonstrate engineering of precisely controlled two-photon high-dimensional states entangled in frequency through time-domain Fourier optical synthesis. We generate and convert a continuous broadband frequency-entangled state into a large range of discrete frequency bins suitable for ITU standards, with spacings ranging from 12.5 GHz to 750 GHz, and observe spectral anticorrelations over 38 frequency bins, including intra-bin pure states at a 100 GHz bin spacing. We characterize the full quantum state dimensionality via Schmidt decomposition and observe lower bounds on the frequency-binned Hilbert-space dimensionalities of at least 289, formed by two entangled qudits with dimension 17. Furthermore, we demonstrate quantum nonlocality via frequency correlations in a transmission experiment over a campus-scale two-node fiber network. This work represents a crucial step towards building a versatile and relatively simple way of generating precisely controlled high-dimensional spectral qudits, with the potential of harnessing in wavelength-multiplexed quantum networks, high-dimensional information processing, and communication of quantum states specifically, and fiber-optic quantum remote sensing. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14325 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14325v1 Announce Type: new Abstract: As quantum computers become available through multi-tenant cloud platforms, ensuring privacy against adversaries sharing the same quantum processing unit becomes critical. We introduce and explore \emph{covert quantum computing}, a new concept that ensures an adversary with access to all other quantum computational units (QCUs) of a quantum computer cannot detect computation on the subset that they cannot access. Analogous to covert communication, we employ information theory. However, since here the adversary controls the systems used for detection, we require a richer framework for covertness analysis that accounts for the use of quantum memories and adaptive operations. Thus, we adopt the \emph{quantum-strategy} framework used in quantum game theory and memory channel discrimination. Current quantum computers use planar graph circuit layouts and typically assume nearest-neighbor crosstalk. We derive discrete isoperimetric inequalities to show that, for an $n$-qubit circuit under this model, only $\mathcal{O}(\sqrt{n})$ border qubits provide detection information to the adversary. We then explore this scaling law on IQM's 54-qubit \emph{Emerald} processor and IBM's 156-qubit \emph{ibm\_fez} machine employing the Heron 2 architecture. We implement Ramsey experiments on qubits not used in computation, and detect nearest-neighbor crosstalk, as expected. However, we also observe long-range coupling effects beyond the border qubits, revealing a side channel that the adversary can exploit. We hypothesize that this long-range crosstalk is induced by leakage from the drive and control lines. Beyond weakening covertness, it exposes co-tenants to both adversarial and unintended crosstalk and degrades circuits that span spatially distributed qubits, motivating further work on spatial isolation and crosstalk characterization. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14338 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14338v1 Announce Type: new Abstract: Adaptive quantum Fisher information (QFI) estimation requires a stopping rule that distinguishes accuracy from apparent numerical stability. For Krylov-shadow QFI estimators, finite Krylov order $K$ produces truncation bias, while finite sample budget $M$ produces finite-$M$ sampling-side error. We show that a width-only empirical stopping rule, based on interval width and local Krylov stability, can declare convergence at small $(K,M)$ even when the post hoc error exceeds the requested tolerance; we call this event a \emph{false stop}. The mechanism is a narrow empirical interval centered on a biased low-$K$ estimate. We give a two-component stopping analysis that separates the Krylov and sampling terms, and we implement a guarded rule that permits a success declaration only after minimum thresholds in $K$ and $M$ and a persistence condition are satisfied. On a five-level dephasing benchmark at $n=4$ qubits, the guarded rule suppresses the false success declarations produced by the width-only empirical rule, whose false-stop rates range from $0.16$ to $0.68$ across the tested noise levels. Under the main fixed resource limit, the guarded rule refuses to make success declarations rather than accepting biased low-$K$ estimates; a separate true-relative-tolerance sampling-budget sequence then shows that, after Krylov and sampling recalibration, the same decision principle can make success declarations without observed false stops. These results show that stopping reliability is a distinct design requirement for adaptive QFI estimation: sampling precision at fixed $K$ does not by itself establish that Krylov truncation bias is controlled. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14356 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14356v1 Announce Type: new Abstract: Matrix product states (MPS) are a standard tensor-network representation for ground states of one-dimensional quantum many-body systems, and they underpin widely used simulation tools such as DMRG. However, while quantum model checking has been developed mainly for quantum programs and communication protocols (with properties expressed along a time axis), there is still no comparable framework for systematically verifying \emph{spatial} and \emph{size-dependent} properties of physical many-body states, where the key parameter is the system size. This paper takes a step toward bridging the gap. We propose \emph{Linear Chain Logic} (LCL), a spatial logic designed to specify physically meaningful properties of periodic MPS families as the system size grows, such as nontriviality on rings and large-size asymptotic patterns. Our approach builds on a simple but powerful connection: every periodic MPS naturally induces a completely positive map (a quantum operation) on its virtual space, so many quantitative features of the MPS can be analysed through the repeated application of the operation. Using this perspective, we derive an effective procedure to compute the inner products of an MPS at a given size and to support richer LCL specifications, without relying on brute-force state expansion. We then develop approximate model-checking algorithms that combine sound bounding with asymptotic structural analysis, enabling scalable reasoning about large system sizes. Experiments on representative MPS families illustrate that our method can automatically verify nontriviality and detect asymptotic spatial regimes in a way that complements traditional numerical techniques. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14378 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14378v1 Announce Type: new Abstract: Recently, the technique of counterdiabatic driving, which provides an effective strategy for accelerating adiabatic quantum evolution, has been widely applied in the preparation of many-body quantum states. In this work, we propose a theoretical scheme for the efficient preparation of Dicke states in a system of non-interacting two-level atoms. Our approach leverages the one-axis twisting (OAT) interaction to generate non-classical correlations and combines it with time-dependent external fields to achieve precise control over the dynamics of the system. By employing rapid adiabatic passage (RAP), it demonstrates how the system can be steered from an initial coherent spin state to a target Dicke state with high fidelity [S. C. Carrasco, M. H. Goerz, S. A. Malinovskaya, V. Vuleti\'c, W. P. Schleich, and V. S. Malinovsky, Phys. Rev. Lett. \textbf{132}, 153603 (2024)]. To further optimize the preparation process, we introduce counterdiabatic driving (CD), which suppresses non-adiabatic transitions. Numerical simulations confirm that our scheme can achieve high-fidelity Dicke states for a moderate number of particles. Our results provide a scalable and experimentally feasible approach to prepare Dicke states, with potential applications in quantum metrology, quantum communication, and quantum information processing. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14394 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14394v1 Announce Type: new Abstract: Cavity-magnon systems, combining magnons and photons, offer a versatile platform for studying quantum entanglement and advancing quantum information science. In this work, we propose a scheme for generating nonreciprocal magnon-magnon entanglement in a hybrid system consisting of two yttrium iron garnet spheres coupled to a spinning whispering-gallery-mode cavity. By leveraging the magnon Kerr nonlinearity and the Sagnac effect arising from the cavity rotation, we show that the entanglement can be substantially enhanced, and the resulting entanglement exhibits pronounced nonreciprocal characteristics. Furthermore, our scheme demonstrates that the entanglement remains robust against thermal noise and persists at bath temperatures up to 100 mK. This work underscores the potential of spinning cavity-magnon systems as a versatile platform for realizing nonreciprocal quantum devices and facilitating the development of quantum technologies. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14395 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14395v1 Announce Type: new Abstract: We show that standard multi-path interferometry, using only pairwise visibility measurements, provides an operational route to tests of preparation noncontextuality. Under ideal symmetric conditions, interference visibility directly encodes state overlaps, without requiring tomography or SWAP tests. For three paths, any jointly diagonalizable (coherence-free) description must satisfy ${V}_{12}^2+{V}_{23}^2-{V}_{13}^2\le 1$, where ${V}_{ij}$ are two-path visibilities. Pure qubit detector states violate this bound, achieving a maximal value of $5/4$. We generalize to arbitrary $n$-path interferometers and derive the tight qubit bound $S_n^{\max}=n\cos^2(\pi/2n)-1$ for all $n\ge3$, achieved by coplanar pure qubit states with uniform angular separation $\pi/n$. A robustness analysis yields explicit experimental thresholds. Under the operational equivalences used in overlap-based generalized noncontextuality frameworks, violations of these visibility inequalities also witness preparation contextuality. For $n$-cycle inequalities, only the pairwise visibilities appearing in the cycle need to be measured. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14484 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14484v1 Announce Type: new Abstract: Mode-pairing quantum key distribution (MP-QKD) protocol achieves performance beyond the repeaterless rate-transmittance bound and exhibits excellent practicality by avoiding the requirement for difficult global phase locking. However, the source side of MP-QKD still relies on the assumption of continuous phase randomization, an experimentally infeasible requirement in practice. Therefore, the practical security of the protocol cannot be fully guaranteed. In this work, we propose a discrete-phase-randomized mode-pairing quantum key distribution (DPR-MP-QKD) protocol and analyze the basis-dependence of the source side. Then, we introduce a concrete discrete version of the decoy state method that ensures the security of the DPR-MP-QKD protocol. Finally, simulation results indicate that as the number of discrete phases increases, the key rate performance of DPR-MP-QKD progressively approaches that of the continuous case, with convergence achieved at approximately 14 discrete phases. Moreover, our approach drastically lowers the demand for randomness. While conventional continuous phase randomization demands an unlimited supply of random bits, we show that merely a few bits (e.g., 4) are adequate. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14515 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14515v1 Announce Type: new Abstract: Entanglement can hide in two fundamentally different ways. First, multi-copy correlations can carry information that no single-copy measurement on an unknown state is able to access. Second, bound entangled states possess a positive partial transpose, which makes them invisible to the Peres-Horodecki criterion and all moment inequalities that depend on it. Here we show that the moment difference between the partial transpose and purity decomposes exactly as a chirality-chirality correlator, where the relevant operator is the scalar spin chirality -- the same quantity that governs chiral spin liquids and the topological Hall effect. This decomposition identifies the specific physical structure that multi-copy entanglement detection probes. Using the same controlled-SWAP circuits, we develop a multi-channel spectral classifier for bound entanglement. The classifier combines realignment spectral features with chirality corrections and achieves 99.9% recall at zero false positives across all three known 3x3 bound entangled families, compared with ~40% for the CCNR criterion alone. We also introduce a marginal-noise construction that produces CCNR-invisible bound entangled states, which the classifier detects but which remain invisible to all single-parameter criteria. We validate our approach experimentally on three IBM Quantum processors and demonstrate negativity reconstruction with mean errors of 0.002-0.027, chirality detection for pure and mixed entangled states, and bound entanglement detection across two structurally distinct families (Horodecki and chessboard) on a single gate-based superconducting processor. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14523 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14523v1 Announce Type: new Abstract: Speech emotion recognition (SER) remains fragile in real-world conditions because emotional cues are subtle, speaker-dependent, and easily confounded by recording variability, while high-performing deep models typically rely on large and carefully curated training sets. Quantum machine learning offers an alternative way to introduce nonlinear correlation modeling with compact modules, yet existing quantum SER studies remain limited and the impact of circuit structure is not well understood. This paper presents HQTN-SER, a hybrid quantum-classical framework that investigates how quantum tensor network connectivity can support SER under small-qubit settings. HQTN-SER introduces (i) an MPS-inspired quantum tensor network module that enforces structured interactions to model correlations in speech representations with a small number of trainable parameters, and (ii) a fusion strategy that combines quantum measurement features with a learned classical latent embedding for end-to-end emotion classification. We evaluate HQTN-SER on three public benchmarks (RAVDESS, SAVEE, and MDER) under a unified preprocessing and training protocol. The proposed model achieves consistent performance across datasets, RAVDESS = 80.12%, SAVEE = 78.26% and MDER = 73.51% accuracy, with stable convergence and low qubit counts, showing that tensor network structure can be an effective and hardware-aware design choice for quantum-assisted SER. The results provide a reproducible baseline and clarify when structured quantum modules can add value to affective computing today. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.14538 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14538v1 Announce Type: new Abstract: Wigner's thought experiment illustrates quantum theory's measurement problem by considering an observer who measures a quantum system inside a sealed lab, modeled unitarily by an outsider. Recent extensions of this thought experiment, referred to as extended Wigner's friend arguments, question how different observers can reason consistently about each other in quantum setups, and challenge the absoluteness of the outcome value obtained by the friend under a notion of locality. In this work, we present an argument against the absoluteness of free choices under the same notion of locality, using an extended Wigner's friend scenario based on the Pusey--Barrett--Rudolph theorem. Similar arguments based on other contextuality or nonlocality models are possible. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2601.10661 Fri, 15 May 2026 00:00:00 -0400 arXiv:2601.10661v2 Announce Type: replace Abstract: In this paper, we propose improved wall-treatment strategies for meshfree methods applied to turbulent flows. The goal is to enhance wall-function handling in simulations of high-Reynolds-number turbulent flows and to understand the performance of turbulence models within these frameworks. While wall-function techniques are well established for mesh-based methods, their implementation in meshfree methods faces unique challenges. The main difficulties arise from scattered point distributions and dynamic point movement in Lagrangian frameworks. To address these issues, we evaluate a baseline closest-neighbor approach alongside two novel techniques: the nearest-band neighbor (NBN) method and the shifted boundary (SB) method. The NBN method enforces wall functions on a band of interior points, helping to maintain uniform point selection. On the other hand, the SB method virtually moves boundary points to a fixed wall-normal distance, eliminating the spatial noise associated with point movement. We evaluate these methods using turbulence closures: Spalart--Allmaras, $k-\varepsilon$, and $k-\omega$ turbulence models. These methods are validated on 1D Couette flow, a turbulent flat plate, and a 3D NACA 0012 airfoil at high Reynolds numbers. Results demonstrate that both novel methods outperform the standard closest-neighbor approach on flat geometries. For flat plates, the SB method provides stability and perfectly smooth $y^+$ distributions. However, when applied to a curved NACA 0012 profile, the NBN method proves to be robust and flexible. In contrast, the SB method exhibits setbacks in numerical diffusion and premature flow separation on curved geometries. This is due to uncorrected normal-vector shifting and adverse pressure gradients. This work establishes the NBN method as a reliable, robust foundation for simulating turbulent flows over practical geometries using meshfree methods. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2512.09587 Fri, 15 May 2026 00:00:00 -0400 arXiv:2512.09587v2 Announce Type: replace Abstract: High-fidelity lattice-Boltzmann very-large-eddy simulations are performed to describe the noise dissipation mechanisms in a single cavity acoustic liner subjected to grazing turbulent flow at a centreline Mach number of 0.3 and plane acoustic waves. The study examines the effects of sound pressure level (ranging from 130 to 160 dB) and source frequency, as well as of the direction of acoustic-wave propagation relative to the grazing flow. The acoustic energy dissipation mechanisms are the viscous losses within the shear layer forming along the internal walls of the orifice and the vortex-shedding. The latter is quantified through Howe's energy corollary. In the absence of grazing flow, acoustic energy is dissipated almost equally during both inflow and outflow phases, with vortex shedding dominating at high SPL and viscous losses at low SPL. The introduction of a grazing flow alters the flow topology; in particular, the shear layer past the orifice generates a quasi-steady vortex that confines the acoustic-induced flow to the downstream half of the orifice. This topological change alters the two noise dissipation mechanisms: viscous losses increase at low SPL because the grazing flow pushes the fluid toward the downstream lip of the orifice; vortex shedding becomes phase dependent, dissipating acoustic energy during the inflow phase and generating acoustic energy during the outflow phase. This explains why the net acoustic dissipation decreases in the presence of grazing flow, highlighting the crucial role of near-wall flow topology on liner performances. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2511.18820 Fri, 15 May 2026 00:00:00 -0400 arXiv:2511.18820v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have shown promise for solving partial differential equations, yet their success in simulating incompressible flows at high Reynolds numbers remains limited. Existing approaches rely on auxiliary labeled data, supervised pretraining, or reference solutions, and no purely unsupervised method comparable to conventional finite-difference or finite-volume solvers has been demonstrated. We attribute this gap to the absence of a mechanism for enforcing the divergence-free constraint and boundary conditions to strict tolerances. To address this, we adopt the physics- and equality-constrained artificial neural network (PECANN) framework with a conditionally adaptive augmented Lagrangian method (CA-ALM), and introduce a pressure-Poisson-based objective. The residual of the pressure Poisson equation is minimized subject to the momentum and continuity equations and boundary conditions on the primitive variables as equality constraints, with CA-ALM enforcing all constraints tightly. For advection-dominated, high-Reynolds-number flows, we further propose an adaptive vanishing entropy viscosity that stabilizes early training without influencing the converged solution. A baseline that instead uses the momentum residual as the objective proves ineffective under the same machinery, underscoring the critical role of the pressure-Poisson objective. The method is assessed on lid-driven cavity flow up to $Re=7{,}500$, three-dimensional unsteady Beltrami flow, and steady and unsteady flow past a circular cylinder with general inflow-outflow boundary conditions, including an ablation study identifying admissible outlet conditions -- all without labeled data or supervised pretraining. Notably, it captures the spontaneous onset of periodic vortex shedding in unsteady cylinder flow without external perturbations, starting from a randomly initialized network. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.14789 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14789v1 Announce Type: new Abstract: Fully compressible numerical simulations of two-dimensional laminar lean hydrogen-air premixed flames have been performed, with the flame front subjected to acoustic forcing through the specification of a monopole-type sound source at the inflow. Simulations have been performed for acoustic frequencies ranging from 35~kHz to 500~kHz at two equivalence ratios, $\phi = 0.4$ and $\phi = 0.7$. During the flame-acoustic interaction, the flame evolves from an initially weakly stretched state to exponential perturbation growth, wrinkle interaction, and the formation of non-linear cellular structures, with distinct linear and non-linear stages identified from Fourier mode analysis. The instability dynamics depend strongly on both forcing frequency and equivalence ratio. In the case of $\phi=0.4$, the flame behaviour is strongly influenced by thermodiffusive instability, with a characteristic sequence of uniform cells, cell splitting, and cell merging. For $\phi=0.7$, weaker thermodiffusive effects result in a response more strongly governed by hydrodynamic instability and large-scale wrinkle growth. At low forcing frequencies, flame corrugations remain relatively uniform, whereas at high frequencies the flame front becomes increasingly modulated and develops envelope-like structures, which can be interpreted as the interaction between an intrinsic standing cellular mode and the imposed acoustic disturbance. In the linear growth regime, the density-weighted displacement speed, $S_d^*$, shows a linear correlation with total stretch rate, $K$, for all forcing frequencies. While in the non-linear growth regime, two distinct branches appear, corresponding to weakly stretched flame segments and strongly negatively curved segments associated with flame pinch-off. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.14505 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14505v1 Announce Type: new Abstract: The rigorous simulation of stratified turbulence remains challenging due to pronounced flow anisotropy, suppressed vertical transport, and high sensitivity to numerical dissipation. This study systematically evaluates the predictive capability of the lattice Boltzmann method (LBM) for a three-dimensional stratified Taylor--Green vortex. Within a double-distribution-function framework under the Boussinesq approximation, we examine the influence of stencil configurations, forcing formulations, and spatial resolutions up to $256^3$, with validation against spectral DNS benchmarks. The results demonstrate that the D3Q27$\times$19 configuration achieves an optimal balance between numerical accuracy and computational efficiency, accurately reproducing the temporal evolution of kinetic and potential energies as well as the characteristic double-peak dissipation structure. Grid-sensitivity analysis further reveals that potential energy and fine-scale turbulent structures are significantly more resolution-dependent than kinetic energy, requiring a minimum resolution of $256^3$ for quantitative convergence. Moreover, under strongly stratified conditions, the velocity-shift forcing schemes outperform discrete source-term approaches, reducing the overall error by approximately 45.54\%. Overall, this work provides practical guidelines for high-fidelity LBM simulations of stratified turbulence and highlights that the coordinated selection of stencil isotropy, spatial resolution, and force discretization is essential for accurately capturing energy cascade and mixing dynamics. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2510.22182 Fri, 15 May 2026 00:00:00 -0400 arXiv:2510.22182v3 Announce Type: replace Abstract: The phase offset between surface charge modulation and geometric undulations in a corrugated nanochannel provides a tunable mechanism for rectified, diode-like ion transport under purely pressure-driven conditions: reversing the applied pressure gradient selectively activates transport of opposite ionic species, generating a net ionic current whose sign and magnitude are set by the charge-geometry alignment. Fully coupled Poisson-Nernst-Planck-Stokes simulations reveal the underlying two-regime structure: at low driving force (Regime I), throughput is suppressed below the Poiseuille limit by a localized streaming potential that pins counterions within the electric double layer; above a threshold pressure (Regime II), the mechanical force overcomes electrostatic resistance, producing an abrupt, orders-of-magnitude rise in mean velocity. Electroosmotically driven flow undergoes a qualitatively similar but smoother transition. Peak charge selectivity is achieved at near-complete electric double layer overlap and driving forces just below the Regime I-Regime II transition. Random walk particle tracking confirms selective rectification and quantifies the dependence of ion dispersion on surface charge placement across both regimes. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2508.21802 Fri, 15 May 2026 00:00:00 -0400 arXiv:2508.21802v2 Announce Type: replace Abstract: Accurate real-time forecasting of cryogenic tank behavior is essential for the safe and efficient operation of propulsion and storage systems in future deep-space missions. While cryogenic fluid management (CFM) systems increasingly require autonomous capabilities, conventional simulation methods remain hindered by high computational cost, model imperfections, and sensitivity to unanticipated boundary condition changes. To address these limitations, this study proposes an Adaptive Real-Time Forecasting Framework for Cryogenic Propellant Management in Space Systems, featuring a lightweight, non-intrusive method named ARCTIC (Adaptive Real-time Cryogenic Tank Inference and Correction). ARCTIC integrates real-time sensor data with precomputed nodal simulations through a data-driven correction layer that dynamically refines forecast accuracy without modifying the underlying model. Two updating mechanisms, auto-calibration and observation and correction, enable continuous adaptation to evolving system states and transient disturbances. The method is first assessed through synthetic scenarios representing self-pressurization, sloshing, and periodic operations, then validated using experimental data from NASA's Multipurpose Hydrogen Test Bed and K-Site facilities. Results demonstrate that ARCTIC significantly improves forecast accuracy under model imperfections, data noise, and boundary fluctuations, offering a robust real-time forecasting capability to support autonomous CFM operations. The framework's compatibility with existing simulation tools and its low computational overhead make it especially suited for onboard implementation in space systems requiring predictive autonomy. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.12393 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.12393v1 Announce Type: cross Abstract: We show how dynamical equations for liquid films and drops on uneven surfaces, including contact line dynamics and evaporation/condensation effects, may be formulated as a variational dynamics, generated via Onsager's variational principle. The theory applies in the isothermal overdamped-dynamics limit. We apply this general approach to obtain several well-known results on contact line dynamics and to study drops pinning and sliding on inclined corrugated surfaces. This approach constructs the dynamical equations starting from the free energy of the system and therefore has the advantage that it naturally incorporates the correct equilibrium properties. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.14951 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14951v1 Announce Type: new Abstract: Proton Exchange Membrane Fuel Cell (PEMFC) is widely recognized for its cleanliness and high efficiency, but is still facing challenges in cold environments. At low temperatures, the formation of ice and repeated freezing/thawing cycles may cause cell performance reduction and irreversible degradation. The cathode flow field of PEMFCs has a significant effect on the performance. In contrast to the conventional ``channel-ridge'' flow field, the metal foam has the advantages of excellent pre-distribution of gases and water drainage, which make it a promising candidate for the cold start. This paper examines the cold start of PEMFCs with metal foam flow field (MFFF) and serpentine flow field (SFF), and the influence of constant current mode, constant voltage mode, and ramping current mode is investigated experimentally through performance test and electrochemical characterization. The results show that lowering the voltage and increasing the current can enhance the cold-start performance of fuel cells. The MFFF fuel cell has superior cold start performance compared to the SFF fuel cell under the constant voltage mode of 0.3 V. Furthermore, the variable current mode is developed by considering the distinct properties of heat and water production during various phases, and the results indicate that increasing the current density at the unsaturated stage leads to an elevated rate of heat production and a reduced rate of water production, which can improve the cold start of PEMFCs. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.14690 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14690v1 Announce Type: new Abstract: The rapid growth of artificial intelligence, coupled with the slowing of Moore's law, is straining computing infrastructure, as CMOS electronics face inherent limits in bandwidth, energy efficiency, and parallelism. Integrated photonic computing encodes and processes information using the phase, amplitude, spatial modes, wavelength channels, and polarisation of guided optical fields, offering a scalable and energy-efficient route beyond charge-based signalling. Here, we review on-chip photonic computing, emphasising the progression from low-dimensional to high-dimensional architectures. At the foundational level, low-dimensional approaches manipulate the phase and amplitude of guided light through Mach-Zehnder interferometers, diffractive structures, microring resonators, and absorptive elements, forming a programmable basis for optical matrix-vector multiplication. Crucially, high-dimensional architectures exploit spatial modes and wavelength channels to carry multiple independent data streams through a single waveguide, achieving higher throughput with moderate hardware overhead. Practical deployment, however, demands more than device innovation. We examine how system-level techniques, from time-wavelength interleaving to hardware-aware training, address energy efficiency, precision, and algorithm-hardware co-design. Five challenges nevertheless remain: electro-optic conversion efficiency, computing parallelism, spatial integration, reconfigurability, and robustness. We highlight emerging topological structures, such as optical skyrmions, as a promising route to fault-tolerant, topologically protected encoding that exploits the largely untapped polarisation degree of freedom. We argue that, by embracing the higher dimensionality of light, photonic computing can offer not merely an incremental improvement but a new paradigm for high-performance, energy-efficient information processing. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14676 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14676v1 Announce Type: new Abstract: Dielectric metasurfaces have introduced a new paradigm for substance detection by exploiting their resonant properties to enhance light-matter interaction. This enhancement can be used for sensing either through refractive index changes or through absorption-based mechanisms. Most works focus on high-quality factor resonators, aiming to increase field confinement in the vicinity of the resonant structure to improve sensitivity. In this work, we explore an alternative approach based on low-quality factor, fully dielectric metasurfaces, with engineered modes to enhance near-field concentration. We investigate different topologies that, despite their low-quality factors, achieve sensitivity and detection performance beyond what is typically reported for low-Q structures in the literature. This improvement is enabled by near-field engineering of the evanescent modes, allowing us to control the spatial distribution of the electromagnetic field and maximize its overlap with the analyte. Our results show that careful mode engineering provides a powerful strategy to boost sensing performance without relying on ultra-high-Q resonances. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14653 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14653v1 Announce Type: new Abstract: Synchronization is a pervasive collective phenomenon underlying the firing of neurons, the beating of the heart, and the coherent emission of lasers. Across these systems, dissipation plays an organizing role, suppressing microscopic differences and steering coupled units toward a common macroscopic order. Here we harness engineered non-Hermitian dissipation to synchronize light directly in the optical domain. Implementing non Hermitian transition matrices on a silicon photonic processor, we drive arbitrary multimode optical fields toward a unique collective state with equal modal intensities and a globally locked phase, a process we call dissipation-induced phase synchronization. The synchronization rate and total optical power throughput are independently programmable, enabling control over the dissipative dynamics without compromising reconfigurability. These results recast dissipation as a functional resource and open a route to reconfigurable on-chip synchronization for classical and quantum photonic technologies. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14614 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14614v1 Announce Type: new Abstract: Fluctuations of nonequilibrium localized waves are shaped not only by direct stochastic forcing but also by deterministic transfer among coupled collective degrees of freedom. We develop a pathway-resolved stochastic collective-coordinate theory that makes this transfer explicit for stationary driven-dissipative solitons of the generalized Lugiato--Lefever equation with Raman response. The reduction yields a refined stationary phase-locking relation, providing a fixed point for the subsequent stochastic theory. Projecting field-level fluctuations onto four soliton coordinates: amplitude, frequency shift, temporal position, and global phase, yields a reduced Langevin model and, after linearization about a stable stationary state, an analytic power-spectral-density matrix. This framework separates direct stochastic injection from deterministic inter-coordinate conversion and thereby resolves how each observable spectrum is assembled from distinct internal fluctuation pathways. It shows that timing jitter is governed primarily by Gordon--Haus-type frequency-to-timing conversion, while phase noise is often dominated by amplitude-to-phase transfer rather than by direct phase diffusion. Raman response opens additional cascaded pathways, and the low-detuning hump in the intensity and phase spectra is traced to the driven response of an underdamped amplitude--phase subsystem preceding the breathing instability. Comparisons with stochastic simulations of both the reduced model and the full generalized Lugiato--Lefever equation show good agreement throughout most of the stable stationary single-soliton regime, with systematic deviations mainly near the Hopf boundary. The theory provides a general route for connecting internal fluctuation-transfer mechanisms of dissipative solitons to measurable noise observables. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14595 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14595v1 Announce Type: new Abstract: Measurements of positional coordinates and dimensions - whether by human vision or optical instrumentation - are fundamental to safety, industrial productivity, manufacturing quality/accuracy, and scientific discovery. The ultimate precision of such measurements is governed by the Fisher information conveyed from an object to a detector through the optical field, and strategies for enhancing measurement performance often focus on reducing detector noise and/or refining estimation algorithms. Building on the emerging understanding of Fisher information as a physical quantity that propagates through space in a wave-like fashion, we demonstrate that substantial gains in precision can also be made by engineering the electromagnetic environment of a measurement target to optimise the generation and transmission of Fisher information. Using nanowire position metrology based on light scattering at a wavelength {\lambda} = 640 nm as an architype system, we achieve a multifold enhancement in localisation precision, reaching beyond {\lambda}/10,000. Our results establish target environment engineering as a powerful and broadly applicable strategy for advancing measurement and sensing performance across platforms ranging from optical characterisation of micro- and nano-objects to microwave radars and optical LiDAR navigation systems. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14592 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14592v1 Announce Type: new Abstract: Nanoscale quantum light sources are essential building blocks for integrated quantum photonic systems. Here, we report a wavelength-scale entangled-photon source based on van der Waals-engineered NbOBr$_2$, and benchmark its performance for telecom-wavelength quantum light generation. By exploiting the material's second-order nonlinearity, we generate quantum-correlated photon pairs via spontaneous parametric down-conversion. We then use a 90$^{\circ}$ twisted stacking to induce quantum interference in photon-pair generation, yielding polarization-entangled photons. This approach enables tunability of the quantum optical state via control of the excitation laser polarization. We experimentally obtain entanglement fidelities exceeding 95% for Bell states, along with a high coincidence-to-accidental ratio of $\sim$335, and a brightness approximately one order of magnitude higher than recently reported telecom sources based on transition metal dichalcogenide (TMD) 2D materials. These results establish twisted van der Waals engineering as a powerful platform for highly tunable, high-brightness quantum light sources at telecom wavelengths. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14585 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14585v1 Announce Type: new Abstract: We introduce a modular silicon-photonic Fabry-Perot resonator lattice based on cascaded tunable Sagnac loop reflectors. Each SLR is controlled by a single directional-coupler cross-coupling coefficient, enabling modular control of the effective lattice hoppings. As a representative example, alternating two SLR types maps the lattice onto the Su-Schrieffer-Heeger model in the weak-coupling limit. We derive the Bloch dispersion via a transfer-matrix formulation and obtain an effective tight-binding Hamiltonian in the weak-coupling limit. S-parameter simulations of a 20-site lattice show an isolated midgap resonance with edge-localized power profiles in the topological phase, and disorder tests show robustness against symmetry-preserving hopping perturbations. Our results establish SLR-based FP lattices as a complementary platform for on-chip topological photonics. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14481 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14481v1 Announce Type: new Abstract: Digital backpropagation (DBP) is one of the most effective techniques for compensating nonlinear distortions in coherent optical fiber communication systems. However, its practical application to wideband transmission remains limited by high computational complexity caused by large channel memory and the requirement for fine spatial discretization. In this work, we propose a subband-based learned digital backpropagation (SbL-DBP) framework for wideband optical transmission systems. The received signal is decomposed into multiple subbands, enabling independent frequency-domain compensation of the chromatic dispersion with reduced effective channel memory and lower computational complexity. Nonlinear intra- and inter-subband interactions are addressed in the time domain using a trainable multi-input multi-output filtering structure. The parameters of the proposed framework are jointly optimized using end-to-end gradient-based learning. In addition, sparsification techniques are employed to remove insignificant coefficients and further reduce computational complexity. Numerical simulations of an 11$\times$40~Gbaud WDM RRC-16QAM 20$\times$100 km transmission system demonstrate that the proposed method provides a superior performance--complexity trade-off compared to conventional DBP and enhanced DBP. In the low- and medium-complexity regimes, SbL-DBP provides higher signal-to-noise ratio gains while requiring fewer propagation steps. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14468 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14468v1 Announce Type: new Abstract: Solid-state Spatial Light Modulators (SLMs) are fundamentally limited in their ability to achieve high spatial complexity and high temporal bandwidth simultaneously. High-speed, low-energy modulation requires sub-wavelength active mode volumes, and sophisticated spatial wavefront engineering necessitates an ultra-fine pixel pitch. While small pixels can simultaneously solve both, in conventional architectures, the dense 2D electrical routing required for such pixels creates an insurmountable physical bottleneck. This results in a compromise between the SLM refresh rate, number of pixels and the field of view. Here, we demonstrate a hybrid architecture that overcomes this limit by spatially decoupling the electrical modulation plane from the optical output plane. By integrating a metasurface doublet with a photonic integrated circuit (PIC)-based optical phased array (OPA), we achieve independent 2D electrical control over each phase-element while simultaneously realizing a three-fold reduction in effective pixel pitch. This decoupling allows us to maintain the small active volume required for high-speed operation, while circumventing the routing constraints of dense spatial array of emitters. We utilize this platform to demonstrate tunable varifocal lensing, 2D beam steering, and 2D holography. Our work provides a scalable foundation for next-generation solid-state SLMs that simultaneously offer high speed, low power consumption, and large field of view. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14466 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14466v1 Announce Type: new Abstract: This paper presents a novel method for measuring the Poynting vector characteristics of monochromatic electromagnetic waves. We outline a specific design for such a meter and provide experimental data to validate the approach. For testing purposes, we utilized vortex beams with both linear and circular polarization. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14441 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14441v1 Announce Type: new Abstract: Optical Skyrmions have recently garnered much interest providing a potential avenue for high capacity, robust topological information transfer. Typically, Skyrmions are derived from the coupling of just two degrees of freedom (DoFs) limiting their versatility. In this work we realize spatio-spectral Skyrmions derived from the non-separability between three DoFs: wavelength, space and polarization. A compact and simple technique is used to generate the spatio-spectral vector beams (SSVB) carrying the desired Skyrmionic structure, offering simple pathways for complex Skyrmionic beam design. The topological structure, witnessed through a map between the spatio-spectral plane and the Poincar\'e sphere, exhibits an additional tunable $k\pi$ parameter thereby enhancing the number of controllable DoFs. Our three DoF construction allows us to propose a novel topological multiplexing strategy that independently encodes different Skyrmion numbers at different radii of the field. We experimentally demonstrate the practicality of this approach by transmitting and receiving three distinct Skyrmion numbers encoded into a single topological field, for the first form of mode division multiplexing with Skyrmion topology. This work opens up new avenues for dense information encoding using multiple topological channels encoded in a single light field. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14412 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14412v1 Announce Type: new Abstract: We propose a bilayer all-dielectric PhC for controlling Janus bound states in the continuum (BIC) and optical chirality through symmetry-selective perturbations. Starting from a symmetry-protected $\Gamma$-point BIC, we use interlayer displacement as one geometric control knob to generate different topological charges in the upward radiation and downward radiation channels. A subsequent diagonal in-plane displacement reconstructs the polarization topology around the BIC and generates a Janus-chiral BIC with strong handedness selectivity. In contrast, other in-plane perturbations generate chiral quasi-BICs with finite radiative coupling, for which the circular dichroism (CD) and resonance wavelength can be continuously tuned. We further show that material conductivity provides an additional dissipative degree of freedom for actively modulating the chiral response, with a switchable CD exceeding 0.89. Near-field optical-chirality distributions and multipole decompositions reveal that the chiral response originates from a symmetry-induced imbalance of local optical handedness and a spin-selective magnetic-dipole resonance. These results reveal the topological relationship between Janus radiation, polarization singularities and intrinsic chirality, thus paving a scalable route toward reconfigurable high-$Q$ chiral photonics. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14268 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14268v1 Announce Type: new Abstract: Photonic time crystals are electromagnetic media with periodically time-varying parameters, enabling momentum band gaps, parametric amplification, and frequency conversion beyond what is possible in time-invariant systems. So far, they have been explored mainly in single-mode systems, which limits the range of accessible physical phenomena. Here, we introduce an impenetrable metasurface waveguide as a multimode time-varying platform supporting both guided surface modes and higher-order guided volume modes. We show that temporal modulation in this platform gives rise not only to conventional intramodal band gaps associated with same-branch coupling, but also to tilted intermodal band gaps originating from coupling between different guided-mode branches. Unlike intramodal band gaps, these intermodal band gaps are not restricted to half the modulation frequency and can enable directional wave amplification, where the amplified field carries energy along the waveguide even inside the band gap. We further show that the modulation phase difference provides an effective symmetry-control parameter: by exploiting temporal glide symmetry, one can selectively suppress or enhance gap opening for interactions between modes of the same or different symmetry. These results establish a versatile multimode platform for photonic time crystals, offering one of the simplest and most experimentally accessible routes to tilted band gaps compared with volumetric dispersive PTC implementations and, more broadly, opening new opportunities for time-varying electromagnetic systems. Physics/physics.optics_(Optics) https://arxiv.org/abs/2604.21307 Fri, 15 May 2026 00:00:00 -0400 arXiv:2604.21307v2 Announce Type: replace Abstract: We report results from a 13-liter purified liquid argon test stand at Wellesley College. The system includes a single-pass liquid-phase purification column, a double-gridded purity monitor to assess the electron lifetime, and a slow control and data acquisition system. Initial measurements demonstrate an O$_2$-equivalent impurity concentration of 0.25 ppb, corresponding to an electron lifetime of 1.5 ms at a drift field of 500 V/cm. This test stand supports ongoing detector R&D on charge and light readout technologies for future large-scale liquid argon time projection chambers, such as Q-Pix and other cold electronics systems, as part of a facility at Wellesley College for fundamental studies of LArTPC readouts. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2601.17163 Fri, 15 May 2026 00:00:00 -0400 arXiv:2601.17163v4 Announce Type: replace Abstract: A size-extensive, converging, black-box, ab initio coupled-cluster ($\Delta$CC) ansatz is introduced that computes the energies and wave functions of stationary states from any degenerate or nondegenerate Slater-determinant references with any numbers of $\alpha$- and $\beta$-spin electrons, any patterns of orbital occupancy, any spin multiplicities, and any spatial symmetries. For a nondegenerate reference, it reduces to the single-reference coupled-cluster ansatz. For a degenerate multireference, it is a natural coupled-cluster extension of degenerate Rayleigh-Schr\"{o}dinger perturbation ($\Delta$MP) theory. For ionized and electron-attached references, it can be viewed as a coupled-cluster Green's function, although the present theory is convergent toward the full-configuration-interaction (FCI) limits, while Feynman-Dyson many-body Green's function (MBGF) theory generally is not. Additionally, a new state-universal multireference coupled-cluster theory for general model spaces is developed by slightly modifying the $\Delta$CC ansatz. This quasidegenerate coupled-cluster (QCC) theory is size-extensive, converging, but not black-box, which is expected to be well suited for strong correlation. Determinant-based, general-order algorithms of $\Delta$CC and QCC theories are implemented, which are compared with configuration-interaction (CI) and equation-of-motion coupled-cluster (EOM-CC) theories through octuple excitations and with $\Delta$MP and MBGF theories up to the nineteenth order. For transition energies, the order of performance is: QCC $\approx$ $\Delta$CC $>$ EOM-CC $>$ CI at the same excitation order or QCC $\approx$ $\Delta$CC $>$ $\Delta$MP $>$ MBGF at the same cost scaling. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.15057 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.15057v1 Announce Type: new Abstract: We investigate numerically the time evolution of velocity and magnetic field fluctuations in a coronal loop, focusing on the dynamics due to both phase mixing and turbulent cascade. The intensity, doppler velocity and non-thermal broadening are synthesized from numerical results in order to establish if the upcoming Multi-slit Solar Explorer (MUSE) mission could reveal the presence of those phenomena in the solar corona through its unprecedented high-resolution spectroscopic observations. The loop is represented by a cylindrical pressure-balanced magnetic structure with a transverse density and magnetic field inhomogeneity. The initial perturbation is a superposition of a torsional Alfv\'en wave and a transverse turbulent component with different tunable weights. In order to reconstruct plasma emission features we calculate moments of the Fe IX 171 \AA\ spectral line. 2D maps obtained by integrating the emission along the assumed line of sight are calculated for the emission intensity $I_0$, the Doppler shift $I_1$ and the non-thermal broadening $I_2$, for several values of the model parameters. Finally, we simulate MUSE spectrograph by considering a resolution of $312$ km $\times$ $312$ km. We observe how intensity maps show the formation of longitudinal threads. The generation of small-scale fluctuations mainly takes place in the inhomogeneity region at the loop boundary, where the effects of phase mixing and non-thermal broadening are stronger. 1D power spectra of intensity and Doppler shift maps are calculated and compared with the corresponding spectra of density and line-of-sight velocity component. The agreement observed between the spectral indexes of the intensity power spectra at MUSE resolution and the one computed from the full 3D density field indicates that spectra of $I_0$ can be used to infer information on the spectrum of density inside a loop. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.14939 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14939v1 Announce Type: new Abstract: Reliable position and shape control in tokamak plasmas requires accurate real-time regulation of several strongly coupled shape parameters. The control vectors that disentangle these couplings, referred to as \textit{virtual circuits} (VCs), enable independent shape parameter control for a specific Grad--Shafranov (GS) equilibrium. Numerical calculation of VCs is not currently feasible in real time, therefore VCs are usually computed prior to each experiment, using a small number of reference GS equilibria sampled along the desired scenario trajectory, with each VC used to control the plasma within a preset time interval. While effective near the reference equilibrium, this approach can lead to degraded performance as the plasma departs from the reference equilibrium and/or from the desired trajectory, and it complicates the design of robust control strategies for rapidly evolving plasma configurations. In this paper, we construct neural-network-based emulators of plasma shape parameters from which VCs can be derived, to provide the MAST Upgrade (MAST-U) plasma control system with state-aware VCs in real-time. To do this, we develop an extensive library of over a million simulated GS equilibria, covering a substantial portion of the MAST-U operational space. These emulators provide differentiable functions whose gradients can be rapidly computed, enabling the derivation of accurate VCs for real-time shape control. We perform extensive verification of the emulated VCs by testing whether they disentangle the control problem. The neural-network-based approach delivers high accuracy and orthogonality across a diverse range of equilibria. This work establishes the physical validity of emulated VCs as a scalable and general alternative to schedules of precomputed VCs. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.14129 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14129v1 Announce Type: new Abstract: Merging direct and indirect-drive has long been viewed as an optimal hybrid laser-fusion scheme that combines the uniformity of x rays with the efficiency of direct illumination. We present the first integrated 2D simulations of hybrid shock drive (HSD) targets for the OMEGA laser. The HSD scheme [L. Ceurvorst et al., Phys. Rev. E 101 063207 (2020)] uses x rays from a thin Au-coated x-ray converter outer shell to drive the initial shock into a standard direct-drive capsule. Direct illumination is used to implode the target after the first shock. The design effectively suppresses laser-imprint seeding of hydrodynamic instabilities, maintaining shell integrity during the implosion. This scheme will enable fielding low-adiabat, high-convergence implosions on OMEGA with expected performance greatly exceeding those of current designs. HSD targets are projected to significantly enhance fusion yields, potentially increasing the record Lawson parameter by $\sim$85\% on OMEGA while effectively eliminating the requirement for laser smoothing. These results position HSD as a robust platform for high-performance implosions, paving the way for advanced high-gain inertial fusion energy targets. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.15139 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.15139v1 Announce Type: new Abstract: A silicon microring resonator with an anisotropic beryllium sulfide (BeS) cladding is proposed for polarization-selective detection of exhaled-breath volatile organic compound biomarkers. The anisotropic dielectric response of BeS enables the transverse-electric (TE) and transverse-magnetic (TM) modes to probe orthogonal components of the cladding permittivity tensor, generating two independent optical observables from a single device. Five clinically relevant biomarkers are investigated: acetone, isoprene, 4-hydroxyhexenal, 2-propenal, and benzene. First-principles optical constants are incorporated into three-dimensional finite-difference time-domain simulations to evaluate the sensing response. The TE mode exhibits a uniform resonance shift of 0.263 nm across all analytes and serves as a concentration reference channel, while the TM mode produces analyte-specific shifts ranging from 0.200 to 0.426 nm. A unique TM amplitude inversion is observed for benzene, enabling additional discrimination. The resulting dual-polarization response forms a two-dimensional optical fingerprint that distinguishes all five biomarkers without requiring a sensor array or multiple functionalized resonators. The device achieves quality factors of 4520 and 3151 for the TE and TM modes, respectively, with sensitivities up to 6.5 nm/RIU, figures of merit up to 14.9 RIU^-1, and detection limits as low as 1.5 mRIU. Cross-sensitivity analysis further shows that CO2 and H2O produce negative TM resonance shifts, separating interferents from target biomarkers in the fingerprint plane. The proposed platform demonstrates a compact route toward array-free photonic breath analysis using intrinsic cladding anisotropy. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.15065 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.15065v1 Announce Type: new Abstract: Actively tunable nanophotonic platforms that control light-matter interactions enable reconfigurable optical systems and programmable photonic integrated circuits. Hydrostatic pressure provides a noninvasive and material-agnostic mechanism for modulating the refractive index and resonance conditions without introducing free carriers or structural damage. Here, we demonstrate multiple pressure-dependent functionalities in silicon nitride nanostructures, including resonance tuning, refractive index modulation, and polarization state conversion. Applying a pressure of up to 5 GPa, we observe a Fabry-P\'erot resonance shift of up to 30 nm and a relative refractive index decrease of up to 4%. Based on the results, we design and examine, to the best of our knowledge, the first extreme-pressure-tunable, polarization-converting metasurface, which tunes the ellipticity and orientation angle of the output light. These findings establish pressure-controllable silicon nitride as a viable platform for reconfigurable photonics and extreme-environment nanophotonic systems, including deep-ocean exploration, planetary interiors, and space applications. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14992 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14992v1 Announce Type: new Abstract: Scintillators convert ionizing radiation into visible photons, enabling applications from cosmic ray detection to medical imaging. Two independent strategies for improving scintillator performance via nanoscale patterning have recently been demonstrated: engineering material properties to enhance absorption of ionizing radiation and integrating nanophotonic structures to enhance the spontaneous emission rate ("nanophotonic scintillators"). Here, we propose a nanophotonic scintillator that simultaneously enhances both the initial energy conversion and the spontaneous emission rate, by periodically stacking a fast-emitting scintillator and a visible-light-transparent material with strong X-ray attenuation ("stopping layer") to form a one-dimensional (1D) photonic crystal (PhC) scintillator. Photoelectric absorption in the stopping layer increases the number of photoelectrons that deposit energy in neighboring scintillator layers and contribute to scintillation. At the same time, the spontaneous emission rate is enhanced by the nanophotonic structuring itself. We design a 1D PhC comprising an organic scintillator and indium tin oxide (ITO) as the stopping layer and numerically simulate the enhancement in scintillation yield and decay rate. The total detected light output is enhanced by up to a factor of 700 compared to a bulk organic scintillator of equal thickness. We further investigate a 1D PhC structure integrating inorganic and organic scintillators for time-of-flight positron emission tomography (TOF-PET): replacing the non-scintillating stopping layer with an inorganic scintillator further increases the light yield, and the coincidence time resolution (CTR) is enhanced up to 3.5 times compared to a bulk inorganic scintillator of equal thickness. Our work presents a unified approach to improve key scintillation parameters within a single nanophotonic structure. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14959 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14959v1 Announce Type: new Abstract: Physical Unclonable Functions (PUFs) are hardware security primitives whose inherent physical complexity can be exploited for secure authentication and cryptographic key generation. Silicon photonic devices, owing to their suitability for quantum and artificial intelligence applications alongside standard CMOS fabrication processes, constitute a highly promising substrate for integrated multifunctional PUFs. Despite the advanced security guarantees offered by quantum cryptographic protocols and the central role of silicon photonics in quantum technologies, quantum readout strategies based on single-photon states for photonic PUFs remain largely unexplored. In this work, we experimentally demonstrate a silicon nitride (SiN) programmable photonic Mach Zehnder interferometer mesh that implements a unitary transformation and operates as a PUF, whose secret physical signature arises from uncontrollable waveguide variations during fabrication. Using experimentally derived parameters from the SiN integrated mesh, we further introduce and numerically evaluate a quantum readout protocol that combines single-photon states with PUFs. Maximally mixed quantum states are employed to conceal the underlying unitary transformation from passive eavesdropping. Security against adversaries possessing devices fabricated under similar conditions is assessed, with authentication performance quantified through Monte Carlo analysis of the false acceptance and false rejection rates as a function of the number of detected events and corrected errors. The results indicate exceptional performance with equal error rates as low as 10 to the minus 14, highlighting the potential of quantum secure PUFs for high security authentication applications. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14829 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14829v1 Announce Type: new Abstract: Single-photon detection possibility is a fundamental requirement for quantum technologies, including communication, computing and sensing. To achieve scalability and practical deployment, increasing attention is being directed toward integration of detectors with photonic integrated circuits, which offer compactness and compatibility with mass production. Superconducting nanowire single-photon detectors have emerged as the leading solution, combining near-unity efficiency, high temporal performance and the ability to be embedded across a wide range of photonic material platforms. In this review we trace the development of integrated superconducting nanowire single-photon detectors from early demonstrations to recent advances, outlining the progress in device architectures, material engineering and integration strategies. We also discuss performance benchmarks, emerging alternative designs, the future opportunities and challenges for this rapidly evolving field. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.14825 Fri, 15 May 2026 00:00:00 -0400 arXiv:2605.14825v1 Announce Type: new Abstract: Statistical properties of light produced in spontaneous Raman scattering on an ensemble of molecules indicate the quantum nature of this phenomenon. The scattered light is non-classical and has high non-classical intensity correlations between Stokes and anti-Stokes components. The temporal coherence of this light is well investigated, while many questions related to spatial coherence remain open. Recent experiments reveal two peculiar features of the spatial coherence of the Stokes and anti-Stokes light. First, the intensity correlations between Stokes and anti-Stokes light remain non-classical even for macroscopic samples containing many molecules. Second, these correlations decrease when signal propagates through a multi-mode optical fiber: the more propagating fiber modes at Stokes and anti-Stokes frequencies the less the correlations. Moreover, the second-order autocorrelation function of Stokes and anti-Stokes light also decreases with the number of propagating modes in multi-mode fiber. In this paper, we build a model of spontaneous Raman scattering correlations of light produced by an ensemble of molecules and propagating through weakly guiding optical fiber that quantitatively explains all these observations. We show that spacial orthogonality of the fiber modes makes the light propagating through these modes uncorrelated in the standard detection scheme. This leads to suppression of non-classical intensity correlations of the total field in the multi-mode fiber. We find the degree of non-classical correlations on fiber parameters. The obtained results pave the way for engineering of non-classical Stokes -- anti-Stokes correlations. Physics/physics.optics_(Optics) https://arxiv.org/abs/2602.03518 Thu, 14 May 2026 00:00:00 -0400 arXiv:2602.03518v2 Announce Type: replace-cross Abstract: We numerically investigate wake dynamics in a superfluid flowing past a penetrable obstacle. Unlike an impenetrable object, a penetrable obstacle does not fully deplete the density. We define an effective diameter $D_{\rm eff}$ from the Mach-1 contour of the time-averaged irrotational flow around the obstacle, which delineates the local supersonic region where quantized vortices nucleate. Using this flow-defined length scale, we construct a superfluid Reynolds number $Re_{\rm s} = (v_0 - v_c) D_{\rm eff}/ (\hbar/ m)$, where $v_0$ is the flow speed, $v_c$ is the critical velocity, and m is the particle mass. We show that $Re_{\rm s}$ organizes the wake dynamics across obstacle sizes and strengths: the transition from dipole-row emission to alternating vortex cluster shedding occurs at $Re_{\rm s}$ around 2, and both the Strouhal number and the drag coefficient collapse onto universal curves when plotted as functions of $Re_{\rm s}$. These results extend the concept of dynamic similarity in superfluid flows to penetrable obstacles and demonstrate that the dynamically relevant length scale is determined by the supersonic region rather than by the geometric obstacle size. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2510.15733 Thu, 14 May 2026 00:00:00 -0400 arXiv:2510.15733v5 Announce Type: replace Abstract: We propose a Hybrid High-Order (HHO) formulation of the incompressible Navier-Stokes equations with variable density that provides exact conservation of volume and, accordingly, pure advection of the density variable. The spatial discretization relies on hybrid velocity-density-pressure spaces and the temporal discretization is based on Explicit Singly Diagonal Implicit Runge-Kutta (ESDIRK) methods. The formulation possesses some attractive features that can be fruitfully exploited for the simulation of mixtures of immiscible incompressible fluids, namely: conservation of volume enforced cell-by-cell up to machine precision, pressure-robustness, ability to preserve density bounds at low-order, robustness in the convection dominated regime, weak imposition of boundary conditions, implicit high-order accurate time stepping, reduced memory footprint thanks to static condensation, possibility to exploit inherited $p$-multilevel solution strategies to improve the performance of iterative solvers. After addressing stability at the discrete level, numerical validation is performed showcasing spatial and temporal convergence rates. To conclude, we tackle the Rayleigh-Taylor instability at different Atwood and Reynolds numbers focusing on mesh independence capabilities. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.05875 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.05875v2 Announce Type: replace-cross Abstract: Cephalopod pulsed-jet locomotion is not a single isolated expulsion event, but a coordinated cycle involving jet expulsion, passive gliding, and mantle refilling. Inspired by this cycle-resolved biological strategy, this paper presents a cephalopod-inspired pulsed-jet robot with a rigid-soft hybrid origami mantle that enables large, actively driven, and geometry-guided body deformation. The proposed mantle integrates rigid folding panels with a compliant silicone framework, allowing a 75% effective cavity-volume reduction during expulsion and reducing the projected cross-sectional drag area by approximately 75.7% in the contracted gliding configuration. Using this platform, we formulate a cycle-resolved framework to separately investigate how expelled volume, glide duration, and refill pathway influence whole-cycle locomotion performance. Experiments show that the robot reaches a peak speed of approximately 0.5 m/s (3.8 BL/s) and an average speed exceeding 0.2 m/s (1.5 BL/s) within the first jetting cycle. The results further demonstrate the roles of high expelled-volume-ratio contraction in speed generation, reduced-drag-area gliding under different glide durations, and mantle-aperture-inspired passive inlet valves in assisting refill. This work provides both a robotic implementation of actively deformable cephalopod-like jet propulsion and a unified experimental platform for studying expulsion-gliding-refilling dynamics in pulsed-jet locomotion. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.06607 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.06607v3 Announce Type: replace Abstract: Recent LLM-based agents have closed substantial portions of the scientific discovery loop in software-only machine-learning research, in chemistry, and in biology. Extending the same loop to high-fidelity physical simulators is harder, because solver completion does not imply physical validity and many failure modes appear only in field-level imagery rather than in solver logs. We present AI CFD Scientist, an open-source AI scientist for computational fluid dynamics (CFD) that, to our knowledge, is the first to span literature-grounded ideation, validated execution, vision-based physics verification, source-code modification, and figure-grounded writing within a single inspectable workflow. Three coupled pathways cover parameter sweeps within a fixed solver, case-local C++ library compilation for new physical models, and open-ended hypothesis search against a reference comparator, all running on OpenFOAM through Foam-Agent. At the center of the framework is a vision-language physics-verification gate that inspects rendered flow fields before any result is accepted, rerun, or written into a manuscript. On five tasks under a shared GPT-5.5 backbone, AI CFD Scientist autonomously discovers a Spalart-Allmaras runtime correction that reduces lower-wall Cf RMSE against DNS by 7.89% on the periodic hill at Reh=5600; under matched LLM cost, two strong general AI-scientist baselines (ARIS, DeepScientist) execute partial CFD workflows but lack the domain-specific validity gates needed to convert runs into defensible scientific claims; and a controlled planted-failure ablation shows that the vision-language gate detects 14 of 16 silent failures missed by solver-level checks. Code, prompts, and run artifacts are released at https://github.com/csml-rpi/cfd-scientist. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2603.07151 Thu, 14 May 2026 00:00:00 -0400 arXiv:2603.07151v3 Announce Type: replace Abstract: Computational Fluid Dynamics (CFD) is an important approach for analyzing flow phenomena and predicting engineering-relevant quantities. The governing physics is formulated as partial differential equations(PDEs) and solved numerically on computational grids. Physics-informed neural networks(PINNs) have emerged as a popular optimization-based approach for solving PDEs, but they often suffer from ill-conditioned objectives and the high cost of automatic differentiation. Optimization-based discretizations such as ODIL mitigate several PINN drawbacks by optimizing discrete variables directly, yet accuracy and efficiency remain limited on body-fitted geometries and for time-dependent problems. This paper proposes FDTO, a finite-difference time-stepping loss-optimization solver that defines physics losses from discrete residuals. FDTO couples curvilinear coordinate transforms with body-fitted structured grids and decomposes long-horizon evolution into sequential, well-conditioned subproblems consistent with time marching. The method is primarily evaluated on incompressible Navier-Stokes flows, including lid-driven cavity benchmarks, external airfoil aerodynamics (lift/drag consistency), and a cylinder case on a multi-block structured mesh with cross-block coherent solutions. Additional validations on diffusion and flow-mixing problems further demonstrate generality. Compared with representative PINN-based solvers, FDTO reduces GPU memory by about 82.6% on the lid-driven cavity case and achieves 3-5 times lower relative error on the flow-mixing problem. These results indicate that FDTO enables accurate, stable, and memory-efficient discrete-loss optimization for incompressible-flow solutions, while remaining applicable to other PDE models. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2602.21860 Thu, 14 May 2026 00:00:00 -0400 arXiv:2602.21860v2 Announce Type: replace Abstract: We investigate the influence of the Prandtl number ($Pr$) on penetrative internally heated convection (IHC) in both non-rotating and rotating regimes using three-dimensional direct numerical simulations. By varying $Pr$ between 0.1 and 100, we show that the global mean temperature $\langle \overline{T} \rangle$ is not very sensitive to $Pr$, and is primarily controlled by the dynamics of the unstably stratified top boundary layer. In contrast, the Prandtl number dictates the behavior of the lower, stably stratified region and affects the vertical convective heat flux $\langle \overline{wT} \rangle$. In the non-rotating case, low $Pr$ fluids exhibit a ``symmetry recovery'' where turbulent stirring agitates the stable layer, whereas high $Pr$ fluids transition toward a ``dead zone'' of suppressed fluctuations. Under rotation, we find that $\langle \overline{wT} \rangle$ is enhanced across all Prandtl numbers, though global cooling efficiency, measured by the reduction in $\langle \overline{T} \rangle$, is only improved for $Pr\ge1$ due to the emergence of Ekman pumping. These results demonstrate that while IHC shares some scaling similarities with Rayleigh-B\'enard convection at the top boundary, the internal stratification creates a unique sensitivity to $Pr$ that is critical for understanding heat transport in planetary and stellar interiors. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.13552 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13552v1 Announce Type: new Abstract: Marangoni condensation - where surface tension gradients induce instabilities that lead to condensate film breakup into discrete droplets - has traditionally been thought of being restricted to 'positive' binary mixtures, where the less volatile component has higher surface tension. 'Negative' mixtures were expected to exhibit stable filmwise condensation. Here, we demonstrate unexpected spontaneous Marangoni-driven pseudo-dropwise condensation in 'negative' water-ethylene glycol and water-triethylene glycol mixtures. Strong thermo-diffusion in these dilute mixtures enables preferential glycol enrichment in colder condensate film regions during condensation, generating surface tension gradients that trigger film breakup, leading to over 6x wettability-independent heat transfer enhancement compared to filmwise condensation. Our work challenges the conventional framework that restricts Marangoni condensation to 'positive' mixtures - a superficial classification that oversimplifies the underlying interfacial mechanisms that can trigger robust Marangoni condensation, offering new pathways for enhancing phase change heat transfer in industrial applications without the need for expensive and degradation-prone surface coatings. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.13195 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13195v1 Announce Type: new Abstract: The work considers a fully turbulent flow with heat transfer in a channel half-filled with an array of cubes based on the work of Breugem and Boersma (2005) and Chandesris et al. (2013), at $\mathrm{Re}_\mathrm{bulk} = 5485$ and three different Prandtl numbers, $\mathrm{Pr} = 0.71, 0.1, 0.05$. The temperature is modelled as a passive scalar and two different boundary condition configurations are simulated. The influence of the Prandtl number on the mean temperature, its variance and the terms of the temperature budget is highlighted, including the analysis of the distribution and relative importance of the turbulent heat transfer, molecular diffusion, tortuosity and Brinkman terms near the porous-fluid interface. The latter two has been found to be insignificant for the highest $\mathrm{Pr}$. A set of terms, typically neglected during the upscaling procedure (related to the Taylor expansion of the filtered variables), is analysed for the first time for the turbulent heat transfer at the porous-fluid interface, and are found to be significant at low $\mathrm{Pr}$. The upscaled fields are evaluated with three different kernels forming cellular average, linear (i.e., tent kernel), quadratic and cubic, and the influence of the chosen filter is additionally studied. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.12696 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12696v1 Announce Type: new Abstract: We present time-resolved pore-scale experiments in which CO2-saturated brine was injected into a water-wet Ketton limestone sample containing residual hydrocarbon under reservoir conditions (8 MPa, 50 {\deg}C) and monitored by 4D X-ray microtomography. Equivalent pore-network models were extracted at each scan time to track pore geometry, topology, and fluid occupancy, while fluid-fluid and fluid-rock interfacial areas and the effective reaction rate were determined from segmented images. The dissolution rate is non-monotonic in time and proceeds through three regimes, consistent with a shifting balance between hydrocarbon swelling and ganglion mobilisation, which control advective access to reactive surfaces. In the initial advection-dominated regime, pore-throat widening leads to ganglia mobilisation and efficient acidic brine delivery to reactive surfaces. The second, dissolution-inhibited regime is marked by up to two orders of magnitude reduction in effective reaction rate. Pore-network analysis shows that swollen hydrocarbon ganglia persistently occupy the largest throats throughout this regime. This occupancy is associated with a reorganisation of the advective flow field into preferential flow paths and stagnant zones. We interpret the rate suppression as primarily reflecting a path-dependent loss of advective access to reactive surfaces, with subordinate contributions from localised H+ depletion near ganglia and reduced near-wall mass transfer in widened flow paths. The inhibited state persists until hydrocarbon is displaced from the largest throats, after which, in the third stage, advective access improves and rock dissolution accelerates. These results show that the effective dissolution rate in residual-hydrocarbon-bearing carbonate depends dynamically on the competition between hydrocarbon swelling and ganglion mobilisation, governing advective access to surfaces. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.12723 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12723v1 Announce Type: new Abstract: We examine the structure of Direct Simulation Monte Carlo (DSMC)-resolved internal compression layers in rarefied micro-nozzle flows and show that their apparent parametric complexity is largely a registration and finite-thickness scaling effect. A density-gradient diagnostic identifies the compression-layer station \(x_s\), while a jump-based thickness \(\delta_j=\Delta\rho/\max|\partial\rho/\partial x|\) defines a shock-centered coordinate \(\xi_j=(x-x_s)/\delta_j\). In physical coordinates, the leading proper orthogonal decomposition (POD) mode of the centerline density profiles captures only \(83.33\%\) of the fluctuation energy, whereas the jump-scaled coordinate increases this value to \(98.33\%\). A two-dimensional shock-window POD further confirms that this compactness is not a centerline artifact: in the registered \((\xi_j,\eta)\) frame, the first density mode captures \(94.98\%\) and the first two modes capture \(99.05\%\) of the fluctuation energy. The same region is identified by density-gradient and gradient-length Knudsen-number diagnostics, linking the reduced representation to localized short-gradient-length rarefaction rather than to shock motion alone. We then use this structure as an inductive bias in a shock-aligned Fusion--Deep Operator Network (DeepONet) surrogate for density, velocity components, temperature, Mach number, and pressure. For held-out back-pressure cases, density, temperature, and pressure errors remain below \(6.8\%\), \(4.3\%\), and \(6.8\%\), respectively, and the hardest case reduces the shock-window mean error from \(9.75\%\)--\(22.27\%\) for standard baselines to \(4.51\%\). The results show that improved prediction follows from the reduced shock-centered structure of the DSMC fields rather than from network capacity alone. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.13065 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13065v1 Announce Type: new Abstract: This paper presents the design of a rapid cycling synchrotron (RCS) featuring a longitudinal localized kick driven fast extraction system for three-dimensional (3D) pencil beam scanning (PBS) proton FLASH delivery. The extraction method is designed to accommodate a novel scanning scheme that addresses the stringent requirement for substantially shorter delivery time compared to current solutions, where the scanning layer is parallel to the proton beam direction. In this method, the kicker pulse waveform is applied selectively to specific longitudinal segments of the proton bunch. For each scanning spot, the functional region of the kicker along the longitudinal direction is dynamically adjusted based on real-time beam longitudinal line density measured by a beam current monitor. The corresponding region-determination algorithm is provided. We analyze the spot dose accuracy and the beam loss at the septum, indentifying increased particle longitudinal line density will reduce spot dose accuracy and increase beam loss. A total number of particles of $2\times10^{10}$ can satisfy the requirements of spot dose accuracy and the beam loss due to the septum is less than 1%. The extraction system comprises a stripline kicker, an electric septum (ESe), and a magnetic septum (MSe), imposing specific requirements on the RCS lattice design. The RCS is carefully designed to meet these constraints, and the parameters of the extraction elements are detailed. By integrating a novel scanning scheme with a specially designed RCS and fast extraction method, this work demonstrates the feasibility of achieving 3D PBS proton FLASH delivery. Physics/physics.acc-ph_(Accelerator_Physics) https://arxiv.org/abs/2605.13506 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13506v1 Announce Type: new Abstract: Polymers and composite materials play an essential role in accelerator and detectors technology, with varying roles that range from electrical insulation and structural support to thermal management. This paper provides a general review of their key properties and classifications, including behaviour under demanding service conditions such as cryogenic operation and high radiation exposure. The paper addresses polymeric materials - their mechanical, thermal, and viscoelastic behaviour, and the effects of crystallinity and additives - alongside composite families, focusing on the characteristics of the matrix and the types of reinforcement. CERN case studies illustrate how both polymers and composites present opportunities and challenges in material selection. Examples include adhesives and structural composites for detectors, reinforced alloys for collimators, and insulation for Nb$_3$Sn superconducting magnets, all emphasising the need to optimise material properties and interfaces to ensure the long-term reliability of components in accelerator facilities. Physics/physics.acc-ph_(Accelerator_Physics) https://arxiv.org/abs/2605.13752 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13752v1 Announce Type: new Abstract: High-resolution longitudinal phase-space (LPS) diagnostics are essential for X-ray free-electron lasers and advanced accelerators. Conventional radio-frequency transverse deflecting structures (TDSs) provide direct femtosecond-scale LPS measurements, but their substantial RF-power and infrastructure requirements strongly limit their deployment at multi-GeV beam energies. Here, we propose a beam-driven transverse deflecting structure in which a leading driver bunch, separated by one RF bucket from the beam of interest, excites long-lived transverse wakefields in a resonant cavity array. The scheme combines the linear longitudinal-to-transverse mapping of an active TDS with the simplicity of a passive wakefield device. A delayed witness bunch interacts near the transverse wake zero-crossing and therefore experiences an approximately linear streak. Electromagnetic simulations of the resonant structure, combined with start-to-end beam-dynamics simulations based on European XFEL parameters at a final beam energy of 14 GeV, demonstrate a temporal resolution of $\sim1.6$~fs for a 500~pC driver beam, with a clear scaling toward the sub-femtosecond regime at higher charge. Physics/physics.acc-ph_(Accelerator_Physics) https://arxiv.org/abs/2605.11968 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.11968v2 Announce Type: replace Abstract: Modern Earth System Models (ESMs) operate on horizontal scales far larger than typical cloud features, requiring stochastic subcolumn generators to represent subgrid horizontal and vertical cloud variability. Traditional physically-based generators often rely on analytical cloud overlap paradigms, such as exponential-random decorrelation, which can struggle to capture the complex, anti-correlated behavior of non-contiguous cloud layers. In this study, we introduce a novel two-stage machine learning subcolumn generator for the GEOS atmospheric model, utilizing a Conditional Variational Autoencoder combined with a Generative Adversarial Network (CVAE-GAN) and a U-Net architecture. Trained on a merged CloudSat-CALIPSO height-resolved cloud optical depth dataset, the ML generator creates 56 stochastic subcolumns representing cloud occurrence and optical depth profiles. Evaluated against the established R\"{a}is\"{a}nen, the ML approach accurately reproduces bimodal cloud overlap distributions, significantly reduces biases in grid-mean statistics, and halves the root-mean-square error in ISCCP-style cloud-top pressure and optical thickness joint histograms. The improvements brought by our deep generative models translate into more accurate offline radiative transfer calculations, reducing the global-mean shortwave top-of-atmosphere cloud radiative effect bias by a factor of three. Provided that the generator can be accelerated on CPUs, this offers a practical pathway to reduce structural errors at the cloud-radiation interface. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2603.10305 Thu, 14 May 2026 00:00:00 -0400 arXiv:2603.10305v3 Announce Type: replace-cross Abstract: Machine learning models can represent climate processes that are nonlocal in horizontal space, height, and time, often by combining information across these dimensions in highly nonlinear ways. While this can improve predictive skill, it makes learned relationships difficult to interpret and prone to overfitting as the extent of nonlocal information grows. We address this challenge by introducing data-driven integration kernels, a framework that adds structure to nonlocal operator learning by explicitly separating nonlocal information aggregation from local nonlinear prediction. Each spatiotemporal predictor field is first integrated using learnable kernels (defined as continuous weighting functions over horizontal space, height, and/or time), after which a local nonlinear mapping is applied only to the resulting kernel-integrated features and optional local inputs. This design confines nonlinear interactions to a small set of integrated features and makes each kernel directly interpretable as a weighting pattern that reveals which horizontal locations, vertical levels, and past timesteps contribute most to the prediction. We demonstrate the framework for South Asian monsoon precipitation using a hierarchy of neural network models with increasing structure, including baseline, nonparametric kernel, and parametric kernel models. Across this hierarchy, kernel models achieve near-baseline performance with far fewer trainable parameters, indicating that much of the relevant nonlocal information can be captured through a small set of interpretable integrations when appropriate structural constraints are imposed. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2604.16429 Thu, 14 May 2026 00:00:00 -0400 arXiv:2604.16429v2 Announce Type: replace-cross Abstract: We introduce Mosaic, a probabilistic weather forecasting model that addresses two distinct failure modes of spectral degradation in ML-based weather prediction: (1) spectral damping caused by deterministic training against ensemble means; and (2) aliasing artifacts caused by compressive encoding onto a coarse latent grid. Mosaic generates ensemble members through learned functional perturbations and operates on native-resolution grids via mesh-aligned block-sparse attention, a hardware-aligned mechanism that captures long-range dependencies at linear cost by sharing keys and values across spatially adjacent queries. At 1.5{\deg} resolution with 214M parameters, Mosaic matches or outperforms models trained on 6$\times$ finer resolution on key variables and achieves state-of-the-art results among 1.5{\deg} models, producing well-calibrated ensembles whose individual members exhibit near-perfect spectral alignment across all resolved frequencies. A 24-member, 10-day forecast takes under 12\,s on a single H100~GPU. Code is available at https://github.com/maxxxzdn/mosaic. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.12727 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12727v1 Announce Type: cross Abstract: Second-order Moller-Plesset perturbation theory (MP2) provides accurate correlation energies for periodic systems but suffers from finite-size errors (FSEs) that have inverse volume scaling due to the Coulomb kernel singularity in reciprocal space. This error scaling limits the routine applicability of MP2 to real materials, requiring prohibitively dense k-point meshes for convergence toward the thermodynamic limit (TDL). We introduce MP2 singularity subtraction (MP2SS), a systematic approach that applies the singularity subtraction strategy to reduce MP2 FSEs. The method employs auxiliary functions and fitting procedures that consider both the singularities present at the origin in reciprocal space and also the discontinuities in the MP2 structure factor that arise from finite k-point sampling. We present three possible MP2SS configurations (Gaussian, exponential, and tuned) which use different combinations of decay functions and demonstrate their performance for gapped systems. All MP2SS configurations consistently achieve millihartree accuracy for correlation energies at coarser k-point meshes than with no correction. Our results establish singularity subtraction as a powerful and flexible approach for mitigating finite-size errors in periodic correlation methods and provide a foundation for extending the technique to higher-order perturbation theories and other post-SCF methods. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.12781 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12781v1 Announce Type: cross Abstract: Closed-form expressions for all matrix elements required for variational calculation of the electronic structure of periodic solids have been derived using a basis of explicitly correlated Gaussians (ECGs). Periodic basis functions are constructed by summing shifted correlated Gaussians over all composite lattice translations, where a generalized unfolding theorem reduces the resulting double lattice sum to a single sum through a unified computational framework for overlap, kinetic energy, and Coulomb potential operators. The formalism has been validated through application to an infinite one-dimensional hydrogen chain, where the ground-state energy per atom computed in the thermodynamic limit is shown to agree with finite-chain results extrapolated by other many-body methods. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.12823 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12823v1 Announce Type: cross Abstract: Coarse-grained (CG) molecular dynamics enables simulations of atomic systems such as biomolecules at timescales inaccessible to all-atom (AA) methods, but existing CG neural potentials trained via force matching capture only the gradient of the free-energy surface, leaving its curvature unconstrained. We introduce a framework that augments force matching with stochastic Hessian-vector product (HVP) matching, instilling second-order curvature information into CG potentials without constructing the full Hessian. We derive a decomposition of the target CG Hessian into a model-independent projected AA Hessian, precomputed once before training, and a model-dependent covariance correction computed online at negligible cost. We construct an unbiased stochastic estimator of the Hessian-matching objective by using random probe vectors. We evaluate our method by comparing against force matching on a benchmark of nine fast-folding proteins unseen during training. HVP matching outperforms plain force matching on 8 of 9 proteins on slow-mode metrics, with reductions of up to 85% in the Kullback--Leibler divergence between the CG and reference distributions along the slowest collective mode of the largest protein. Our results demonstrate that higher-order physical supervision is a practical path to more accurate and transferable CG potentials for biomolecular simulation. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.13826 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13826v1 Announce Type: cross Abstract: Scientific machine learning reports predictive performance. It does not report whether the same prediction would survive a different draw of training data. Across $9$ chemistry benchmarks, two classifiers trained on independent bootstraps of the same training set agree on aggregate accuracy to within $1.3\text{--}4.2$ percentage points but disagree on the class label of $8.0\text{--}21.8\%$ of test molecules. We call this gap \emph{cross-sample prediction churn}. The standard parameter-side techniques (deep ensembles, MC dropout, stochastic weight averaging) do not reduce this gap; two data-side methods do. The first is $K$-bootstrap bagging, which cuts the rate $40\text{--}54\%$ on every dataset at no accuracy cost ($K{\times}$-ERM compute). The second is \emph{twin-bootstrap}, our proposal: two networks trained jointly on independent bootstraps with a sym-KL consistency loss between their predictions, which at matched $2{\times}$-ERM compute reduces churn a further median $45\%$ beyond bagging-$K{=}2$. Cross-sample prediction churn deserves a column alongside predictive performance in scientific-ML benchmark reports, because without it the parameter-side and data-side methods are indistinguishable on the metric they actually differ on. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2601.00131 Thu, 14 May 2026 00:00:00 -0400 arXiv:2601.00131v2 Announce Type: replace Abstract: Practical applications of fragment embedding and closely related local correlation methods critically depend on a judicious choice of a low-level theory to define the local embedding subspace and to capture long-range electrostatic and correlation effects outside the embedding region. Second-order M{\o}ller-Plesset perturbation theory (MP2) is by far the most widely used correlated low-level theory; however, its applicability becomes questionable in systems where MP2 is known to fail either quantitatively or qualitatively. In this work, we present the random phase approximation (RPA) as a promising alternative low-level theory to MP2 within the local natural orbital-based coupled-cluster (LNO-CC) framework. We demonstrate that RPA-based LNO-CC closely matches the performance of its MP2-based counterpart for systems with sizable energy gaps, while delivering significantly faster convergence toward the canonical coupled-cluster limit for metallic systems, particularly as the thermodynamic limit is approached. These results highlight the critical role of the low-level theory in fragment embedding and local correlation methods and identify RPA as a compelling alternative to the commonly used MP2. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2602.12382 Thu, 14 May 2026 00:00:00 -0400 arXiv:2602.12382v2 Announce Type: replace Abstract: We report a $k$-point extension of the second-order co-iterative augmented Hessian (CIAH) algorithm, termed $k$-CIAH, for Pipek-Mezey (PM) localization of Wannier functions (WFs). By exploiting an efficient evaluation of the Hessian-vector product, $k$-CIAH achieves $O(N_k^2 n^3)$ scaling in both CPU time and memory, matching that of previously reported first-order $k$-space approaches while improving upon the $O(N_k^3 n^3)$ scaling of $\Gamma$-point CIAH, where $N_k$ denotes the number of $k$-points sampling the first Brillouin zone and $n$ characterizes the unit-cell size. Benchmark calculations on a diverse set of solids -- including insulators, semiconductors, metals, and surfaces -- demonstrate the fast and robust convergence of $k$-CIAH-based PMWF optimization, which yields an overall computational efficiency approximately 2-3--fold higher than first-order $k$-space methods and orders of magnitude higher than $\Gamma$-point CIAH for localizing 1000-5000 orbitals. The quality of the resulting PMWFs is further validated by accurate electronic band structures obtained via PMWF-based Wannier interpolation. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2603.15788 Thu, 14 May 2026 00:00:00 -0400 arXiv:2603.15788v2 Announce Type: replace Abstract: This work is the second in the series "On the performance of QTP functionals applied to second-order response properties." In the first paper (J. Chem. Phys. 162, 054105, 2025), we demonstrated the good performance of Quantum Theory Project functionals in predicting static perturbed second-order properties, such as static polarizabilities, nuclear magnetic resonance (NMR) spin-spin coupling constants, and NMR chemical shifts. In the present study, we focus on frequency-dependent properties, namely dynamic polarizabilities and C$_6$ dispersion coefficients. For completeness, a total of 25 exchange-correlation (XC) functionals were investigated. Dynamic polarizabilities were evaluated at five different perturbation wavelengths: 632.99 nm, 594.10 nm, 543.52 nm, 514.50 nm, and 325.13 nm. This property was also computed using HF and EOM-CCSD. In general, EOM-CCSD results are very close to those obtained with linear-response CC3, except at the highest frequency. Among Kohn-Sham calculations, TPSS0 and QTP01 showed the best overall performance for dynamic polarizabilities. We also assessed how well QTP functionals reproduce the pole structure of the CO molecule. For the C$_6$ dispersion coefficients, calculations were performed using the Casimir-Polder equation. The best overall performance was obtained with O3LYP; however, the first eleven ranked functionals show very similar accuracy. Within the QTP family, QTP01 and LC-QTP provide the best results for C$_6$ coefficients. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10311 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.10311v2 Announce Type: replace Abstract: We investigate microhydration effects on the three low-lying {\pi}* shape resonances of thymine using the Resonance via Pad\'e approach in combination with the DLPNO-EA-EOM-CCSD method. For isolated thymine, the calculated resonance positions are benchmarked against projected CAP-EA-EOM-CCSD calculations and compared with available theoretical and experimental data. Upon hydration, the 1{\pi}* and 2{\pi}* resonances undergo systematic stabilization accompanied by significant increases in their lifetimes, whereas the 3{\pi}* resonance exhibits a more complex behavior. In particular, the lifetime of the lowest resonance increases from 39 fs in isolated thymine to 110 fs in the thymine(H2O)3 cluster. Detailed analysis reveals that the observed resonance shifts arise from competing contributions involving hydrogen bonding, electrostatic interactions, microsolvation-induced geometric distortion, and finite-basis-set effects. Ghost-atom calculations demonstrate that diffuse basis functions associated with nearby water molecules contribute appreciably to the apparent stabilization, while explicit inclusion of water molecules leads to genuine physical stabilization of the resonance states. Furthermore, calculations on multiple conformers of the monohydrated cluster show that resonance positions and lifetimes depend strongly on the local hydrogen-bonding arrangement and microsolvation geometry. These findings demonstrate that resonance stabilization in microhydrated nucleobases is governed by a subtle interplay between geometry, basis-set effects, and intermolecular interactions. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10312 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.10312v2 Announce Type: replace-cross Abstract: Evaluating high-dimensional integrals via deep hierarchical recurrences is a dominant cost in quantum chemistry. While CPUs manage these efficiently, GPUs suffer a critical mismatch: limited per-thread memory is quickly overwhelmed by an explosion of simultaneously live intermediate variables. As recurrence scales, this forces massive data spilling to global memory, collapsing performance into a severe memory-bound regime. We present FusionRCG, a framework that jointly optimizes computation graph structure and GPU memory mapping. Exploiting the inherent topological flexibility of recurrence graphs, using electron repulsion integrals as an example, we contribute: (1) liveness-aware graph orchestration to minimize peak live intermediates; (2) algebraic dimensionality reduction via stepwise Cartesian-to-spherical fusion, shrinking intermediate footprints by up to $7.7\times$; and (3) an adaptive multi-tier kernel architecture routing graphs across the memory hierarchy. Evaluated on NVIDIA A100 GPUs, FusionRCG achieves up to $3.09\times$ end-to-end SCF speedup over GPU4PySCF and maintains $75\%$ parallel efficiency at 64~GPUs, successfully rescuing these workloads from memory-bound limits. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10363 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.10363v2 Announce Type: replace-cross Abstract: Locality-driven integration is a pervasive computational pattern in quantum chemistry, arising whenever spatially localized basis functions interact through numerical quadrature or integral screening. The dominant matrix multiplications in these tasks exhibit dynamic, structured sparsity driven by spatial locality, posing significant challenges for both dense batched kernels and generic sparse formats on GPUs. We present KerneLDI, a GPU-oriented framework that addresses this regime by co-designing data layout, screening logic, and matrix-computation operators to realize block-structured matrix multiplication for locality-driven integration. KerneLDI reorganizes operand matrices into a unified block-filtered representation that retains only spatially relevant blocks, and executes the resulting contractions with customized dense block multipliers that adapt proven dense-matmul optimizations to retained block pairs. We develop and evaluate KerneLDI on exchange--correlation (EXC) integration in Kohn--Sham density functional theory, a representative and computationally critical instance of this pattern. Across diverse molecular systems, KerneLDI preserves numerical accuracy while delivering up to 10$\times$ speedup for EXC evaluation over a dense GPU baseline, scales favorably with increasing system size and multi-GPU parallelism, accelerates end-to-end self-consistent field calculations, and yields nearly 6$\times$ throughput improvement for ab initio molecular dynamics. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2509.19929 Thu, 14 May 2026 00:00:00 -0400 arXiv:2509.19929v4 Announce Type: replace-cross Abstract: Uncertainty Quantification (UQ) is paramount for inference in engineering. A common inference task is to recover full-field information of physical systems from a small number of noisy observations, a usually highly ill-posed problem. Sharing information from multiple distinct yet related physical systems can alleviate this ill-posedness. Critically, engineering systems often have complicated variable geometries prohibiting the use of standard multi-system Bayesian UQ. In this work, we introduce Geometric Autoencoders for Bayesian Inversion (GABI), a framework for learning geometry-aware generative models of physical responses that serve as highly informative geometry-conditioned priors for Bayesian inversion. Following a ''learn first, observe later'' paradigm, GABI distills information from large datasets of systems with varying geometries, without requiring knowledge of governing PDEs, boundary conditions, or observation processes, into a rich latent prior. At inference time, this prior is seamlessly combined with the likelihood of a specific observation process, yielding a geometry-adapted posterior distribution. Our proposed framework is architecture-agnostic. A creative use of Approximate Bayesian Computation (ABC) sampling yields an efficient implementation that utilizes modern GPU hardware. We test our method on: steady-state heat over rectangular domains; Reynolds-Averaged Navier-Stokes (RANS) flow around airfoils; Helmholtz resonance and source localization on 3D car bodies; RANS airflow over terrain. We find: the predictive accuracy to be comparable to deterministic supervised learning approaches in the restricted setting where supervised learning is applicable; UQ to be well calibrated and robust on challenging problems with complex geometries. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2602.13094 Thu, 14 May 2026 00:00:00 -0400 arXiv:2602.13094v2 Announce Type: replace-cross Abstract: We present a quantum reservoir computing (QRC) framework based on a small-scale quantum system comprising at most six interacting qubits, designed for nonlinear financial time-series forecasting. We apply the model to predict future daily closing trading volumes of 20 quantum-sector publicly traded companies over the period from April 11, 2020, to April 11, 2025, as well as minute-by-minute trading volumes during out-of-market hours on July 7, 2025. Our analysis identifies optimal reservoir parameters that yield stock trend (up/down) classification accuracies exceeding $86 \%$. Importantly, the QRC model is platform-agnostic and can be realized across diverse physical implementations of qubits, including superconducting circuits and trapped ions. These results demonstrate the expressive power and robustness of small-scale quantum reservoirs for modeling complex temporal correlations in financial data, highlighting their potential applicability to real-world forecasting tasks on near-term quantum hardware. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.12757 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12757v1 Announce Type: new Abstract: Generative AI is rapidly reshaping STEM higher education. Not only are our educational practices changing, but how we think about educational transformation must adapt. Existing models of institutional change in STEM, aimed at interactive engagement, have largely followed an adoption logic: relatively stable, well-researched educational practices are evaluated and then scaled. These assumptions do not hold for generative AI, which is an arrival technology -- entering classrooms before a sufficient pedagogical evidence base could form. Building on recent decades of work on STEM institutional change, we propose a framework identifying six dimensions along which prior change models must be reconsidered in light of AI: three concerning the tools at the center of reform (the tool's evidence base, rate of change, and scope), and three concerning the people involved in change (faculty, change agents, and students). For each dimension, we examine how AI-era assumptions differ from those underlying prior interactive engagement reforms and derive design implications, including: privileging humble and local inquiries; organizing reform around pedagogical approaches rather than specific tools; repositioning change agents as facilitators of collective inquiry; and engaging students as partners in reform. Collectively, the six dimensions and design implications constitute a new framework for adapting change models to support institutions under conditions of genuine uncertainty. Finally, we illustrate how the framework may be applied through a brief case-study of a faculty workshop series carried out in a university physics department to support instructors adapting to this modern AI era. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2604.26056 Thu, 14 May 2026 00:00:00 -0400 arXiv:2604.26056v3 Announce Type: replace Abstract: We propose a pedagogical, rationalized MKS-based convention for electromagnetic quantities designed to reduce cognitive load in undergraduate undergraduate electromagnetism. By setting vacuum constants to $\varepsilon_0 = \mu_0 = 1/c$, we preserve the familiar structure of Maxwell's equations while making the role of the speed of light explicit. In this convention, electrical units are expressed directly in terms of mechanical units (e.g.\ $[\mathrm{nuA}] = \sqrt{\mathrm{J/s}}$), effectively reducing the number of independent base units. A striking pedagogical consequence is that electrical resistance becomes dimensionless, capacitance and inductance acquire units of time, and radiation pressure reduces to $|\mathbf{E}\times \mathbf{B}|$, greatly simplifying dimensional analysis for circuits and fields. We introduce corresponding non-SI units (\textit{nu}-units), provide conversion relations to SI, and demonstrate the potential utility of this system through comparative ``before/after'' derivations of the wave equation, electromagnetic energy density, radiation pressure, and the Bohr atom. Preliminary empirical support is provided by student attitude surveys administered to $N_1 = 46$ and $N_2 = 39$ students in an undergraduate physics course, which showed a statistically significant improvement in the perceived clarity of the wave equation derivation after exposure to the nu-system ($p = 0.005$, Mann--Whitney $U$ test), and a majority preference for the dimensionless-resistance feature. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2605.13199 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13199v1 Announce Type: new Abstract: Accurate Time-of-Flight (TOF) measurement with sub-100 picosecond resolution is a critical requirement for particle identification in future high-energy physics experiments, such as the Belle II $K_{L}$ and Muon (KLM) detector upgrade. Achieving this precision with large-area Silicon Photomultipliers (SiPMs) is challenging due to the inherent junction capacitance, which degrades signal rise time. In this work, we developed and evaluated a high-time-resolution cosmic ray detector based on plastic scintillators and customized SiPM arrays. To optimize the readout for block-shaped scintillators, we systematically compared different sensor topologies. We demonstrate that a multi-face readout topology, utilizing low-capacitance 4-series (4S) SiPM modules coupled to four faces of the scintillator, achieves an excellent coincidence time resolution of approximately 68 ps, outperforming the $\sim$100 ps resolution of the concentrated 4-series 3-parallel (4S3P) hybrid topology. Furthermore, to validate the system's practical performance, we successfully measured well-known cosmic ray observables, specifically the relativistic muon velocity via TOF reconstruction. These results highlight the potential of the multi-face 4S configuration as a high-precision solution for future TOF detector upgrades. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2605.13216 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13216v1 Announce Type: new Abstract: A silicon carbide PIN detector was fabricated and its radiation tolerance under Ta heavy ion irradiation of 2370 MeV was evaluated. Its electrical properties, charge collection performance and time resolution of $\beta$-particles ($^{90}$Sr) are reported. The leakage currents for unirradiated and irradiated 4H-SiC PIN detectors are $1.47 \times 10^{-10}$~A @ 300 V and 1.49~$\times$ 10$^{-10}$A@ 300 V. The effective doping concentrations for unirradiated and irradiated 4H-SiC PIN detectors are $6.23\times 10^{13}$~cm$^{-3}$ and $6.13\times 10^{13}$~cm$^{-3}$. The irradiated detector exhibits good electrical performance and stable device architecture. The 4H-SiC PIN detector exhibits a charge collection efficiency (CCE) of 99.24\% under Ta Heavy Ion Irradiation. The time resolutions of the detector before and after irradiation are 40 ps and 45 ps, respectively. Experimental results indicate that the CCE and time resolution performance exhibit good stability before and after irradiation. These results demonstrate stable performance under Ta heavy ion irradiation, highlighting the detectors potential for radiation-hard applications in high-energy physics, space missions, and nuclear reactor monitoring. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2605.13281 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13281v1 Announce Type: new Abstract: We report on the development of 3D silicon sensors at the University of Science and Technology of China (USTC). The sensor involves columnar electrodes (5 um in diameter) of both doping types, etched from the same wafer side. The p+ electrodes pass through the epitaxial wafer, whereas the n+ electrodes stop at a short distance from the opposite side of the epitaxial wafer. With respect to previous generations of 3D sensors, they feature an ultra-thin active substrate (50 um) and a small pixel size of 50 um x 50 um or 25 um x 25 um. This R&D project aims to establish a sensor technology to simultaneously measure position and time information at the single-pixel level. The first run with one merged wafer layout has been completed. The design, fabrication, and characterization of the sensors are reported in this paper. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2605.13572 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13572v1 Announce Type: new Abstract: The Belle II experiment, operating at the asymmetric SuperKEKB $e^+e^-$ collider, is preparing an upgrade of its vertex detector to cope with an increased luminosity of $6 \times 10^{35}$ cm$^{-2}$s$^{-1}$. The upgraded vertex detector (VTX) will consist of five or six layers of depleted monolithic active pixel sensors (DMAPS), with a total material budget of approximately $3\%$ $X/X_0$. The OBELIX chip, derived from the TJ-Monopix2 sensor and fabricated using Tower Semiconductor 180 nm CMOS technology, is being developed for this upgrade. It features a 33 $\mu$m pixel pitch with a time-stamping binning of $50-100$ ns, along with a dedicated digital periphery compatible with the Belle II trigger system, supporting rates up to 30 kHz. The sensor is designed to operate under the high background conditions expected at the target luminosity, with radiation tolerance up to $5 \times 10^{14}$ $n_{eq}$/cm$^2$ and 100 Mrad, while targeting a power density of about 200 mW/cm$^2$. This corresponds to hit rates up to 120 MHz/cm$^2$. Beam test and irradiation studies of TJ-Monopix2 demonstrate that the operating sensor temperature should stay below $40^\circ$C after irradiation up to $5 \times 10^{14}$ $n_{eq}$/cm$^2$. This report reviews the proposed VTX concept, sensor performance, and ongoing R$\&$D activities. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2605.12538 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12538v1 Announce Type: cross Abstract: We provide a versatile plateform to investigate wave-particle duality. This photonic waveguide network implements quantum (wave) graphs as proposed in the seminal paper by Kottos \& Smilansky [PRL \textbf{85} 968 (2000)]. We experimentally demonstrated that the spectral statistics of a mixing (i.e. strongly chaotic) graph follows the predictions of random matrix theory, contrary to an ergodic (i.e. less chaotic) graph, in agreement with the Bohigas-Giannoni-Schmit conjecture [PRL \textbf{52} 1 (1984)]. This plateform also gives access to the wavefunction patterns, which are expected to verify the quantum ergodicity theorem. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2605.13599 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13599v1 Announce Type: cross Abstract: We present a fast time-domain simulator for optical cavities capable of reproducing non-linear dynamical regimes arising from ring-down effect during resonance crossings at high mirror velocities. The model is based on a recursive formulation of the intracavity electric field as a sum over round trips, preserving the cavity memory while maintaining high computational efficiency. The simulator is designed to achieve three main goals. First, the boundary conditions of the cavity can be modified at each simulation step, allowing arbitrary time-dependent variations of both mirror positions and input electric field. Second, the sampling frequency can be flexibly chosen by the user, however, it is internally adjusted before effectively executing the simulation to remain consistent with the cavity round-trip structure. Finally, high computational efficiency was obtained by avoiding the repeated evaluation of the full electric field history. The framework is validated through comparison with experimental data from the Virgo interferometer during a mechanical excitation experiment, showing good agreement in non-adiabatic regimes. Due to its efficiency and flexibility, the simulator provides a versatile tool for time-domain studies of optical resonators and future applications in real-time control and reinforcement-learning-based lock acquisition. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2510.07792 Thu, 14 May 2026 00:00:00 -0400 arXiv:2510.07792v2 Announce Type: replace Abstract: The BeEST experiment is searching for sub-MeV sterile neutrinos by measuring nuclear recoil energies from the decay of $^7$Be implanted into superconducting tunnel junction (STJ) sensors. The recoil spectra are affected by interactions between the radioactive implants and the sensor materials. We are therefore developing aluminum-based STJs (Al-STJs) as an alternative to existing tantalum devices (Ta-STJs) to investigate how to separate material effects in the recoil spectrum from potential signatures of physics beyond the Standard Model. Three iterations of Al-STJs were fabricated. The first had electrode thicknesses similar to existing Ta-STJs. They had low responsivity and reduced resolution, but were used successfully to measure $^7$Be nuclear recoil spectra. The second iteration had STJs suspended on thin SiN membranes by backside etching. These devices had low leakage current, but also low yield. The final iteration was not backside etched, and the Al-STJs had thinner electrodes and thinner tunnel barriers to increase signal amplitudes. These devices achieved 2.96 eV FWHM energy resolution at 50 eV using a pulsed 355 nm (~3.5 eV) laser. These results establish Al-STJs as viable detectors for systematic material studies in the BeEST experiment. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2511.13956 Thu, 14 May 2026 00:00:00 -0400 arXiv:2511.13956v2 Announce Type: replace Abstract: In this document, a pileup deconvolution scheme not relying on any mathematics guessing is presented. In high energy physics experiment, as the luminosity increases, pile-up issues on detectors such as calorimeters become non-negligible. Deconvolution approaches developed for data taken from DAQ systems are usually rank-deficient or underdetermined, having less equations than unknowns, even with the ADC values from multiple beam crossings are collected. These deconvolution approaches need mathematic pre-assumptions such as Sparse Representation. For online computation tasks such as for trigger primitive creation, signal availability is significantly different as in offline data analysis stage, and therefore, it is possible to use different (yet simpler) algorithms. In this situation, number of ADC values of the calorimeter outputs is the same as the number of beam crossings (or 4 times number of beam crossings, depending on the ADC sampling rate), and therefore, the number of equations can be arranged to be the same as number of unknowns. This way, a determined deconvolution scheme with a full-rank squared convolution (and deconvolution) matrix becomes possible. The robustness of deconvolution over long time windows is also studied in this paper. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2603.07538 Thu, 14 May 2026 00:00:00 -0400 arXiv:2603.07538v2 Announce Type: replace-cross Abstract: Quantum key distribution is unbreakable in theory but may be hacked via imperfections in its hardware implementations. While many imperfections have been mitigated by countermeasures and advanced security proofs, several remain unsolved. One of these is a superlinear behaviour in single-photon detectors, when the click probability rises faster with the photon number of an incoming light pulse than expected from individual independent photon detections. Here we test an avalanche single-photon detector sinusoidally-gated at 312.5 MHz for superlinearity. Its click probability is moderately superlinear. However, we notice that the click timing depends strongly on the incoming pulse energy. The click occurs progressively earlier, shifting more than 2 ns as the energy rises over a wide 50-dB range. An attacker might use this energy-time effect to conditionally toggle the click between adjacent key bit slots, violating an implicit assumption in the security proofs and rendering them inapplicable. We propose two attacks that exploit this flaw. Physics/physics.ins-det_(Instrumentation_and_Detectors) https://arxiv.org/abs/2605.12891 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12891v1 Announce Type: new Abstract: Traditional VMAT optimization often ignores dynamic machine limits, treating delivery time as an emergent property rather than a steerable parameter. This work introduces Dynamic Modulated Arc Therapy (DMAT), an intent-driven framework that jointly co-optimizes dosimetric quality, delivery time, and modulation complexity. DMAT couples machine emulation accounting for axis synchronization and finite acceleration with dynamic modulation control and clinical cost functions. A user-selected level (-3 to +3) governs leaf-travel, MU behavior, and CP density. Plans are created by initializing CP geometry, leaf positions, and MU, then iteratively alternating dosimetric updates with sequencing updates (penalties for motion, velocity changes, MU uniformity, and complexity), followed by post-processing. CP density is adapted by first optimizing with a uniform distribution and then redistributing CPs to arc sectors with higher complexity. DMAT was evaluated using a hypothetical system (2.5 RPM gantry, 6.25 cm/s MLC, 3000 MU/min) on H&N, lung SBRT, and prostate SBRT cases. Higher modulation levels produced increased MU/Gy and longer delivery times, while adaptive CP allocation concentrated resolution in high-reward sectors. H&N cases showed substantial quality gains with increased modulation, whereas prostate and lung SBRT exhibited smaller incremental improvements. When efficiency was prioritized (negative levels), DMAT reduced modulation and maintained a constant CP budget while shortening delivery time, producing quantifiable reductions in plan quality. DMAT enables intent-driven planning where quality and complexity are co-optimized via machine-aware timing. Accurate delivery time is exposed during planning, making trade-offs transparent and navigable for next-generation systems and time-constrained workflows like motion-sensitive or adaptive radiotherapy. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.12896 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12896v1 Announce Type: new Abstract: Radiotherapy (RT) patient scheduling is a complex operational problem. Current scheduling often relies on manual coordination and can be difficult to adapt to changing clinical demands. This study evaluated the feasibility of using a large language model (LLM) to generate candidate RT patient schedules satisfying predefined clinical and operational constraints. A simulated three-LINAC RT scheduling environment was developed over one year using synthetic patient arrivals and treatment characteristics modeled after clinical practice. A total of 1,400 new patients across 12 treatment categories were generated. An LLM-based scheduling framework used structured natural-language prompts encoding clinical rules, operational constraints, and scheduling objectives. Performance was evaluated across scenarios involving weekly time consistency, LINAC continuity, gap-constrained temporal relaxation, and infeasible request handling. Generated schedules were validated using deterministic rule-based checks and manual review. LLM-generated schedules satisfied predefined feasibility rules in the evaluated scenarios. Approximately 99% of evaluated fractions remained within the preferred 60-minute weekly treatment-time window. Adding a LINAC-continuity objective reduced LINAC switching from 54.6% to 10.1%. Adding gap-constrained temporal relaxation reduced Friday mean daily gap time from 169.5 to 89.2 minutes while maintaining approximately 99% of fractions within the 60-minute window. The framework also identified infeasible scheduling requests and proposed interpretable corrective actions. These results suggested that LLMs may support RT patient scheduling in constraint-rich simulated clinical environments, motivating further investigation of LLM-assisted scheduling as a flexible, human-in-the-loop decision-support approach for RT operations. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.13555 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13555v1 Announce Type: new Abstract: Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density information. Repeated CT acquisitions impose radiation exposure and logistical burdens, MRI lacks electron density, and cone-beam CT (CBCT) requires correction for dose calculation. Synthetic CT (sCT) generation addresses these by converting MRI or CBCT into CT-equivalent images with accurate Hounsfield Unit (HU) values, enabling MRI-only RT and CBCT-based adaptive workflows. Building on SynthRAD2023, SynthRAD2025 benchmarked sCT methods on 2,362 patients from five European centers across head and neck, thorax, and abdomen. Two tasks: MRI-to-CT (890 cases) and CBCT-to-CT (1,472 cases), evaluated via image similarity (MAE, PSNR, MS-SSIM), segmentation (Dice, HD95), and dosimetric metrics from photon and proton plans. With 803 participants and 12/13 valid submissions, Task 1 top performance reached MAE $64.8\pm21.3$ HU, PSNR $\sim$30 dB, MS-SSIM $\sim$0.936, Dice 0.79, photon $\gamma_{2\%/2\text{mm}}>98\%$, proton $\gamma\approx85\%$. Task 2 improved: MAE $48.3\pm13.4$ HU, PSNR 32.6 dB, MS-SSIM 0.968, Dice 0.86, photon $\gamma>99\%$, proton $\gamma\approx89\%$. Strong image--segmentation correlations ($\rho=0.78$--$0.79$) but moderate dose correlations confirmed image quality is insufficient as a dosimetric surrogate. Head-and-neck cases were most consistent; thoracic and abdominal cases showed greater variability. Residual errors at tissue interfaces propagate along beam paths, affecting proton dose more than photon. SynthRAD2025 demonstrates that deep learning yields clinically relevant sCTs, especially for CBCT-to-CT, while identifying persistent MRI-to-CT challenges and underscoring dose-based evaluation as essential for clinical validation. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2301.12647 Thu, 14 May 2026 00:00:00 -0400 arXiv:2301.12647v3 Announce Type: replace Abstract: X-ray imaging is a fast, precise and non-invasive method of imaging which, when combined with computed tomography, provides detailed 3D rendering of samples. Incorporating propagation-based phase contrast can vastly improve data quality for weakly attenuating samples via phase retrieval, allowing radiation exposure to be reduced. However, applying phase retrieval to multi-material samples commonly requires choice of which material boundary to tune the reconstruction. Selecting the boundary with strongest phase contrast increases noise suppression, but at the detriment of over-blurring other interfaces and potentially removing quantitative sample information. Additionally, conventional phase-retrieval algorithms cannot be used for regions bounded by more than one material, requiring alternative methods. Here we present a computationally-efficient, non-iterative nor AI-mediated method for applying strong phase retrieval, whilst preserving sharp boundaries for all materials within the sample. 3D phase retrieval is combined with morphological operations to prevent over-blurring artefacts from being introduced, while avoiding the potentially long convergence times required by iterative approaches. This technique, entitled 3DMPR, was tested on phase contrast images of a rabbit kitten brain encased by the surrounding dense skull. Using 24kVp synchrotron radiation with a 5m propagation distance, 3DMPR provided a 6.8-fold improvement in the signal-to-noise ratio (SNR) of brain tissue over the standard phase retrieval procedure, without over-smoothing the images. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2407.06527 Thu, 14 May 2026 00:00:00 -0400 arXiv:2407.06527v3 Announce Type: replace Abstract: Many lung diseases require detailed visualisation for accurate diagnosis and treatment. High-resolution computed tomography (CT) is the gold-standard technique for non-invasive lung disease detection, but it presents a risk to the patient through the relatively high ionising radiation dose required. Utilising the X-ray phase information may allow improvements in image resolution at equal or lower radiation levels than current clinical imaging. Propagation-based phase-contrast imaging requires minimal adaption of existing medical systems, and is well suited to lung imaging due to the strong phase gradients introduced by the lung-air material interfaces. Herein, propagation-based phase contrast CT is demonstrated for large animals, namely lambs, as a model for paediatric patients, using monochromatic radiation and a photon-counting detector at the Imaging and Medical Beamline of the Australian Synchrotron. Image quality, normalised against radiation dose, was optimised as a function of the beam energy and propagation distance, with the optimal conditions used to test the available image quality at very low radiation dose. The resulting CT images demonstrate superior resolution to existing high-resolution CT systems, pushing dose to the quantum limit to comply with current Australian guidelines for infant chest CT exposure of $<2.5\:\text{mSv}$ effective dose. Constituent raw projections are shown to have significant proportions of pixels with zero photon counts that would create severe information loss in conventional CT. Phase retrieval enabled clear visualisation of minor lung airways at doses up to 1,225$\pm$31\% times lower than conventional CT reconstruction, at a voxel size of just 75$\mathrm{\mu}$m. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2603.05658 Thu, 14 May 2026 00:00:00 -0400 arXiv:2603.05658v2 Announce Type: replace Abstract: Patient derived xenograft (PDX) tumor models initiated in avian chorioallantoic membranes (CAM) are under investigation to evaluate the effectiveness of therapeutic options with the objective of personalizing treatments. CAM PDXs paired with ultra-high frequency ultrasound (UHFUS) imaging could potentially constitute prospective high throughput assays that can rapidly assess tumor volume and vascular response to therapy. To date, little work has been conducted to adapt and validate UHFUS flow imaging methods to CAM tumor models. Here we report the development and evaluation of an imaging pipeline for UHFUS detection of microvascular flow in a CAM tumor model using interframe subtraction (IS) to suppress tissue clutter. The IS pipeline included a tissue motion compensation (MC) stage prior to clutter filtering and was compared to a singular value decomposition (SVD) clutter filter. The performance was evaluated using UHFUS data acquired in phantom and in vivo Sunitinib-treated renal cell carcinoma. MC substantially reduced tissue motion effects. MC+IS was comparable to MC+SVD filtering at detecting flow within tumors. The results for both IS and SVD filters were dependent on the details of implementation. The UHFUS imaging methods detected a significant decrease in blood flow metrics in treated versus control tumors. An effective imaging pipeline was developed for the assessment of the treatment response of CAM PDX models in a clinically relevant timeframe. The MC+IS approach implemented on B-scan image derived data is less computationally intensive and can be used with widely available UHFUS systems. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.12663 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12663v1 Announce Type: new Abstract: Quantum emitters in hexagonal boron nitride (hBN) have emerged as a promising solid-state platform for quantum technology applications. However, a persistent challenge in the field is the unclear origin of many observed emission lines, particularly in the visible range, which can be difficult to distinguish from signals arising from organic or process-induced contamination during sample preparations and handling. This ambiguity limits both the reproducibility of emitter generation and the reliable identification of truly intrinsic quantum defects. This work provides a step-by-step framework to assess whether quantum emitters in electron-irradiated hBN are associated with organic contaminants introduced during sample preparation. We employ hyperspectral imaging, thermal annealing, and oxygen plasma etching to investigate the origin of the green-yellow emitters in electron-irradiated hBN. The combined results not only rule out organic contamination as the source of emission but also provide insight into the spectral variability, thermal stability, and vertical localization of the emitters generated in electron-irradiated hBN that was created without any pre- or post-processing. In addition, our experiments demonstrate the feasibility of creating stable emitters in hBN with thicknesses below 10 nm. These findings provide practical guidance for the identification and controlled implementation of hBN-based single-photon emitters in quantum photonic devices. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.12884 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.12884v1 Announce Type: new Abstract: Ultrafast optical imaging has enabled direct observation of femtosecond-nanosecond dynamics, yet three-dimensional (3D) dynamic measurements at high numerical aperture (NA) remain hindered by the intrinsically shallow depth of field (DoF) of conventional microscopes. Here, we propose an ultrafast, wide-field pump-probe interferometric microscope on a telecentric platform that significantly extends the effective DoF to ~18 micrometer at a high NA of 0.9 while maintaining high spatial resolution (down to 235 nm) and temporal resolution (~170 fs). The system enables single-frame 3D topography reconstruction without axial scanning or multi-view acquisition. We demonstrate these capabilities by capturing axial material flow during laser-induced microsphere melting that remain unobservable with conventional narrow-DoF systems, and by tracking the azimuthal rotation of ablation lobes during axial propagation of temporal focused spatiotemporal optical vortex (TF-STOV) pulses, directly revealing the spatiotemporal evolution of STOV-matter interactions Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13177 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13177v1 Announce Type: new Abstract: Optical neural networks offer a route to low-latency and energy-efficient inference by encoding computation in light propagation. However, most existing implementations rely on planar photonic circuits or discretely spaced diffractive layers, restricting volumetric integration and imposing stringent alignment requirements. Here we demonstrate a volumetric optical scattering neural network (OSNN) in which densely packed weak scatterers form a three-dimensional, locally connected optical computing medium. In contrast to fully connected diffractive architectures, the OSNN uses near-field scattering interactions, described under the first-Born approximation, to compress optical interconnections into a monolithic volume. We implement this concept using resilient inverse design and two-photon nanolithography, yielding OSNN devices with a volume of ~$3.8*10^{-4}mm^{3}$ and a record-breaking neuron density of $1.0*10^{9}/mm^{3}$. Experimentally, the fabricated classifier achieves $94.8\%$ blind-test accuracy on MNIST, while the imager performs optical compressed imaging with a $1-{\mu}m$ effective resolution and average FSIM values of $0.93$ on Fashion-MNIST and $0.91$ on VesselMNIST3D. OSNN paves the way for ultra-dense, ultra-compact, and efficient optical computing, creating a universal platform for embedded optical intelligence and promising widespread application in AI fields ranging from autonomous driving to medical diagnosis. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13191 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13191v1 Announce Type: new Abstract: Achieving reliable joining between transparent materials and metals under non-optical-contact conditions remains challenging due to limited energy coupling and uncontrolled interfacial reaction across $\mu$m-scale gaps. Burst-mode ultrafast lasers provide a potential solution for large-gap welding through temporally distributed energy deposition. However, the underlying interaction mechanisms and achievable joining limits remain unclear. In this study, burst-mode ultrafast laser welding of sapphire to Invar alloy was investigated under controlled interfacial gaps from 3 to 10 $\mu$m. Cross-sectional microscopy, elemental mapping, white-light interferometry, and shear testing were employed to analyze joint morphology, elemental distribution, fracture behavior, and mechanical performance.After optimization of the processing parameters for burst-mode ultrafast laser welding, the interfacial morphological evolution and joint strength under different gap conditions were systematically investigated. At a 3 $\mu$m gap, cyclic thermal stresses induced by burst pulses generate transverse micro-crack networks in sapphire, accompanied by a reduction in joint strength with increasing sub-pulse numbers. Notably, at a 10 $\mu$m gap, where single-pulse welding fails, burst-mode ultrafast laser welding enables interfacial bridging with a maximum shear strength of 6.3 MPa, representing the highest level among published studies.These results indicate a gap-dependent evolution in burst-mode welding behavior governed by crack formation and energy accumulation. This study provides an important theoretical basis and practical guidance for achieving high-performance joining of dissimilar materials under large gap conditions. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13224 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13224v1 Announce Type: new Abstract: We demonstrate an on-chip 0.96 TOPS hyperdimensional photonic tensor core by utilizing a time-spacewavelength multiplexed silicon photonic Crossbar (Xbar). The novel architecture relies on serializing the large matrix-vector or tensor-vector products by unfolding multiply and accumulation operations over time domain, while simultaneously distributing the computational workload over different spatial and wavelength channels. We experimentally demonstrate the operation of a 4-channel 2-input TSWDM Xbar that incorporates 56 GHz electroabsorption modulators (EAMs) and 4-channel integrated multiplexing stages. Its successful operation as a 4x2x1 tensorvector multiplication unit demonstrated an average error of 3.9%. Its performance as a photonic AI accelerator was also evaluated in the classification task of the Iris dataset, presenting experimental accuracies of 93.3% at data rates between 4x10 and 4x30 GBd, reaching 83.3% when the data rate increases to 4x60 GBd. Finally, we discuss the TSWDM Xbar scalability potential, revealing that the inclusion of a WDM scheme in the SDM architecture reduces the operating laser power, feasibly boosting the potential of constructing photonic accelerators with computational throughput in the POPS regime. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13272 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13272v1 Announce Type: new Abstract: To address the fundamental limitations imposed by chromatic dispersion and environmental susceptibility in standard single-mode fiber (SMF) for long-haul high-precision time transfer, we systematically explore the application potential of hollow-core fiber (HCF) through comparative experiments. We designed a bidirectional time transfer platform enabling direct comparison between HCF and SMF links across distances of 91 km, 68 km, and 54 km. We quantitatively characterize the impact of critical non-reciprocal error sources, specifically the optical Kerr effect and chromatic dispersion, under varying laser power, wavelength drift, and environmental perturbations. Our results show that HCF exhibits significantly suppressed dispersion, with a mean coefficient of 3.4 ps per nm per km, and reduced environmental sensitivity compared with SMF. Notably, over the 91 km link, the HCF yields a signal-to-noise ratio (SNR) enhancement of more than 24 dB and confines the time deviation to less than 80 ps, which is nearly an order-of-magnitude improvement over SMF, where the time deviation exceeds 600 ps, while remaining nearly immune to power and wavelength fluctuations. Under 24 hour diurnal monitoring, the 68 km HCF link demonstrates strong robustness, with environment-induced time delay fluctuations of 776 ps, corresponding to only 24.5% of those in SMF, which reach 3166 ps. Consequently, the time transfer stability, evaluated by time deviation (TDEV), reaches 0.2 ps at an integration time of 1000 s, representing a twofold improvement over SMF. These findings validate HCF as a superior transmission medium with low latency, low nonlinearity, and high thermal stability, paving the way for next-generation ultra-stable, long-haul time-frequency distribution networks. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13327 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13327v1 Announce Type: new Abstract: Laser ablation in liquids enables the synthesis of surfactant-free nanoparticles but remains limited in productivity due to intrinsic constraints imposed by the liquid environment. These constraints include nonlinear optical losses, material redeposition, and cavitation bubble-induced shielding. Temporal intensity shaping of the incident laser pulse offers a potential route to mitigate these limitations. Here, ultrashort GHz-burst ablation is applied to laser ablation of gold in water. By distributing the pulse energy into a sequence of picosecond sub-pulses arriving within the nanosecond time window preceding cavitation bubble formation, GHz-burst irradiation enables energy delivery before the onset of bubble-induced shielding. This increases the threshold fluence for nonlinear losses and yields an ablation efficiency enhancement of up to a factor of three compared to single-pulse ablation. Importantly, this efficiency gain is not accompanied by an increase in cavitation bubble size or lifetime. In addition to enhanced efficiency, burst irradiation yields a twofold narrower nanoparticle size distribution. These results demonstrate that GHz-burst ablation is a promising approach to increase productivity while simultaneously improving nanoparticle quality. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13353 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13353v1 Announce Type: new Abstract: The conventional formulation of power absorption, optical forces, and torques on dipolar particles involve lenghty and cumbersome expressions that obscure their shared physical origin. We apply a bispinor formalism that unifies these disparate phenomena in a very general case including chiral and nonreciprocal particles. This reveals that force, torque, absorbed power, and absorbed helicity rate can all be concisely expressed in terms of broken symmetries, and leads to the fundamental inequalities that dipolar particles' cross-sections must satisfy. This framework uncovers profound connections normally hidden behind complex algebra -- for instance, pressure forces depend exclusively on the difference in linear momenta of different light components and the corresponding breaking of symmetry by a particle, and optical recoil forces depend exclusively on helicity cross sections -- providing clarity, conciseness, and a powerful predictive tool for arbitrary dipole interactions. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13443 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13443v1 Announce Type: new Abstract: Speckle is an intrinsic pattern in optical coherence tomography (OCT) that obscures fine image features and degrades effective resolution. In this study, we propose a numerical speckle reduction method based on the dispersed scatterer model and the imaging formulation of OCT. Utilizing the shifted-complex-conjugate-product, the proposed method digitally modulates speckle patterns by shifting the complex en face OCT signal and averaging the resulting real-part images. This approach allows for effective speckle suppression using a single volumetric acquisition without additional hardware modifications. OCT point spread function phantom measurement demonstrated lateral resolution preservation of the proposed method. We validated the method using a custom-built full-field swept-source OCT system on human breast adenocarcinoma spheroids and a zebrafish eye. Quantitative evaluations using the contrast-to-noise ratio and equivalent number of looks demonstrated that the proposed method significantly outperforms conventional frame-averaging techniques. The speckle-reduced images revealed microstructures previously obscured by speckle, such as necrotic regions in spheroids, while preserving the original image sharpness and resolution. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13483 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13483v1 Announce Type: new Abstract: Vector beams, whose polarization varies across the transverse profile, are a central resource in structured-light optics and quantum photonics. Their characterization, however, becomes challenging when the field lies in a spectral region for which efficient spatially resolving detectors are unavailable. Here we demonstrate the spatially resolved reconstruction of an undetected vector beam by exploiting induced coherence in a nonlinear interferometer. In this effect, indistinguishability between two down-conversion pathways allows information encoded in an undetected field to be read out through interference of its detected partner. A telecom-wavelength idler field acquires a spatially varying polarization transformation but is never directly detected. Instead, its local polarization information is inferred from single-photon interference in the visible signal field, enabled by momentum correlations of the photon pair. Using phase-shifting and off-axis quantum holography with two polarization projections, we reconstruct the horizontal and vertical amplitudes and their relative phase across the beam profile, thereby recovering the full vectorial structure of the undetected field. We experimentally retrieve the polarization texture of an $m=2$ vector beam and compare multi-shot and single-shot reconstruction strategies. Our results extend imaging with undetected light from scalar objects to vectorial optical fields and open a route to polarization-sensitive sensing and state reconstruction in spectral regions that are difficult to access directly. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13541 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13541v1 Announce Type: new Abstract: High-order edge-enhanced imaging enables precise feature localization and effective background suppression, offering a powerful tool for real-time recognition and high-contrast visualization. Extending this capability to the mid-infrared (MIR) regime is particularly valuable for applications such as biomedical diagnostics, material inspection, and remote sensing, yet remains limited by inadequate spatial-frequency modulation fidelity and low detection sensitivity. Here, we demonstrate a high-sensitivity MIR upconversion differentiator operating at 3 $\mu$m, which achieves isotropic high-order edge enhancement by optically imprinting topological complex-amplitude patterns onto MIR Fourier components via nonlinear parametric interaction. Vortex transfer functions $t(k_r, \phi) \propto k_r^\ell e^{i\ell\phi}$ are precisely encoded on a phase-only spatial light modulator to enable tunable MIR differentiation from first- to fourth- order, with real-time switching at up to 60 Hz. Benefiting from a low-noise upconversion process and a single-photon-sensitive silicon camera, the system achieves high-contrast edge imaging under low-light conditions. Experimental results confirm accurate edge extraction and background suppression for both amplitude and phase objects, hence underscoring its potential for noninvasive diagnostics and label-free material analysis. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13619 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13619v1 Announce Type: new Abstract: Extended depth of field microscopy encodes axial information into a single acquisition through engineered point spread functions, but conventional and deep optics approaches are subject to degradation in scattering tissue. We introduce DeepFilters, a scattering-aware deep optics framework that jointly optimizes a parameterized pupil filter and a digital-filter-based reconstruction network through a calibrated differentiable forward model to achieve broad generalization without retraining. Incorporating empirical scattering kernels, physics-guided regularization, and a hybrid genetic-gradient initialization strategy, DeepFilters extends the PSF from 16 micron to >400 micron in clear media and enables signal recovery beyond 120 micron deep in biological tissues, validated across fixed brain slices and sea urchin embryos. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13745 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13745v1 Announce Type: new Abstract: Multimode intracavity frequency-doubled lasers can reach states of amplitude noise suppression orders of magnitude beyond the predictions of independent-mode partition statistics. We show that the chi2 coupled-wave dynamics in the doubling crystal admit a Lyapunov functional whose monotone decrease under each crystal pass establishes a constant-intensity manifold as the per-pass descent target of the mode dynamics. We confirm the mechanism in an intracavity frequency-doubled Nd:YVO4-LBO laser, observing a 100 fold contrast between full and Fabry-Perot-filtered output noise at fixed detector bandwidth, well beyond the statistical-averaging baseline. The mechanism rests on the algebraic structure of the coupling, a coherent superposition of oscillators sharing a quadratic dissipative channel, and is therefore a candidate for analogous noise-suppression effects in other coupled oscillator systems with the same algebraic form. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13828 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13828v1 Announce Type: new Abstract: Rare-earth gain media form the foundation of modern optical communications, emerging quantum hardware, and ultrafast optics. While chip-scale integration can enable fiber-like, and potentially beyond-fiber, functionality with unprecedented scalability, development in the visible and near-infrared remains in its early stages. Here, we demonstrate ytterbium-based optical gain integrated into an aluminum oxide photonic platform, achieving both single-mode lasing and optical amplification in the near-infrared regime. This platform delivers optical amplification with output powers exceeding 0.5 W, an optical-to-optical conversion efficiency above 70%, and a noise figure of 3.3 dB, approaching the quantum limit for phase-insensitive amplification. Furthermore, we achieve femtosecond pulse amplification to a record peak power of 14 kW, enabling supercontinuum generation with visible dispersive waves extending from 780 to 476 nm in conjunction with nonlinear photonic devices. This platform is compatible with heterogeneous integration into standard photonic circuits, laying the foundation for scalable visible-near-infrared photonic systems, including coherent laser arrays, mode-locked lasers, optical clocks, and microwave oscillators. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13387 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13387v1 Announce Type: cross Abstract: Nanophotonic traps for cold atoms typically have trap volumes that are orders of magnitude smaller than, e.g., free-space optical tweezers. This makes efficient loading of these traps challenging, thereby limiting the total number of atoms coupled to the nanophotonic waveguide. Here, we demonstrate that $\Lambda$-enhanced gray-molasses ($\Lambda$GM) can substantially increase the number of trapped atoms in a nanofiber-based cold-atom setup. Specifically, we observe a six-fold increase in the number of loaded atoms compared to conventional red-detuned polarization gradient cooling. Despite the unusually small depth of our optical trap of only 24 $\mu$K, we load about 4000 individual Cesium atoms, achieving optical depths exceeding 140 and reaching the collisional blockade regime over a length of approximately 1 mm. After loading, we perform efficient EIT-assisted cooling that is found to increase the trap storage time to 400(9) ms. This is a 5-fold improvement over the passive storage time. Remarkably, EIT-cooling also works with two co-propagating nanofiber-guided light fields and requiries only about a few hundred picowatt of optical power. Our results provide an efficient method to boost both the number of loaded atoms and the storage time of nanophotonic atom traps. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13466 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13466v1 Announce Type: cross Abstract: We present the results of an experimental study of the anomalous anisotropy of alignment signals in cesium vapors under strong spin exchange conditions in zero magnetic fields under linearly polarized optical pumping. We show that the anisotropy of the Hanle resonances in the plane perpendicular to the pump beam increases sharply with increasing concentration. In one direction, the resonance widths are determined by classical spin exchange, while in the other, by the SERF (Spin-Exchange Relaxation Free) effect. With further concentration increases, additional nonlinear effects arise, such as an increase of the normalized signal amplitude, effective magnetic field, bistability, hysteresis, and memory. To explain these observations, as well as the results presented in our previous studies, we construct a demonstration theoretical model incorporating spontaneous polarization effects arising under strong spin exchange. The model qualitatively shows that the experimentally observed ultra-narrow alignment resonances may originate predominantly from quadrupole anisotropy associated with spontaneous transverse orientation projected onto the detection axis.The unique properties of these resonances, such as their ultra-small width and magnetic field-controlled bistability with a long-term memory effect, make them promising for use in quantum sensing and information. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13545 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13545v1 Announce Type: cross Abstract: Integrated photonics has emerged as a promising platform for quantum communication and quantum computation. Thin-film lithium niobate (TFLN) has gained significant attention in this field due to its exceptional optical properties, enabling the realization of numerous integrated photonic devices. However, quantum memory, which serves as a universal building block for the quantum internet, has not yet been demonstrated in TFLN. In this study, we realized the first on-chip quantum memory using erbium ions doped TFLN. The developed quantum memory achieves a storage time of 400 ns with an efficiency of 1.95%, significantly outperforming conventional waveguide delay lines. The multimode capability is demonstrated by successfully storing four temporal modes. Furthermore, single-photon-level coherent pulses are encoded into time-bin qubits and stored with a fidelity of 96.8% , surpassing the classical limit achievable by measure-and-prepare strategy. Our results demonstrate the first on-chip quantum memory for telecom-band time-bin qubits in TFLN, providing a key building block toward integrated quantum registers and repeaters for scalable quantum information processing. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13664 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13664v1 Announce Type: cross Abstract: Thermal-infrared (TIR) hyperspectral imagery (HSI) provides critical scene information for various applications. However, its practical utility is severely limited by unique sensor degradations beyond the capabilities of existing restoration methods, which are ignorant of underlying thermal physics. Here, we propose HAIR (HADAR-based Image Restoration) as a physics-driven framework for ground-based TIR-HSI restoration. HAIR utilizes the HADAR rendering equation (HRE) and combines it with the atmospheric downwelling radiative transfer equation (RTE) to model TIR-HSI using temperature, emissivity, and texture (TeX) physical triplets. This physical model leads to a TeX decompose-synthesize strategy that guarantees physical consistency and spatio-spectral noise resilience, in stark contrast to existing approaches. Moreover, our framework uses a forward-modeled atmospheric downwelling reference, along with spectral smoothness of emissivity and blackbody radiation, to enable spectral calibration and generation that would otherwise be elusive. Our extensive experiments on the outdoor DARPA Invisible Headlights dataset and in-lab FTIR measurements show that HAIR consistently outperforms state-of-the-art methods across denoising, inpainting, spectral calibration, and spectral super-resolution, establishing a benchmark in objective accuracy and visual quality. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13694 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13694v1 Announce Type: cross Abstract: Tweezer arrays of polarizable objects are a promising platform for assembling quantum matter and building next-generation quantum sensors. Light-induced dipolar interactions have emerged as a method to couple their motion, thereby establishing a new paradigm for controlling collective mechanical degrees of freedom. Here, we extend these into the regime of Floquet-driven interactions, combined with the intrinsic nonreciprocity of optical forces. We demonstrate beamsplitter, single-, and two-mode squeezing operations, as well as signatures of a negative-mass-like oscillator arising from the nonreciprocity. Moreover, we show that a programmable combination of these operations enables continuous tuning of complex eigenfrequencies. These results establish a toolbox of quantum operations of nonreciprocal interactions that are essential for investigating non-Hermitian many-body physics and collective quantum optomechanics. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13707 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13707v1 Announce Type: cross Abstract: Optical spin-orbit interactions (SOI) link photonic spin to momentum, offering a route toward on-chip polarization control and beam steering. Nevertheless, achieving sufficient optical SOI and nonlinearities on sub-micrometer scales - a prerequisite for dense photonic integration - remains an outstanding challenge. Here, we show that highly birefringent van der Waals (vdW) waveguides provide an ideal, chip-compatible platform to address this limitation. We focus on the ferroelectric semiconductor NbOI2, which exhibits record optical nonlinearities and dielectric anisotropy. Using femtosecond optical microscopy, we image light propagation and harmonic conversion beyond the total internal reflection barrier over tens of micrometers in NbOI2 slab waveguides. We report giant optical spin-splitting through the optical spin Hall effect, which facilitates spatial separation of optical spin currents on sub-micrometer scales, in quantitative agreement with a microscopic light-matter interaction model. We further leverage optical spin-momentum locking to realize polarization-controlled waveguide steering. We generalize these observations across various vdW waveguides and empirically confirm a scaling law linking dielectric anisotropy to geometric spin-splitting. Our results establish highly anisotropic vdW waveguides as an ideal platform for densely integrated opto-spintronic technologies. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.13056 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13056v1 Announce Type: cross Abstract: This work is devoted to the study of the influence of temperature anisotropy and parallel heat flux on the stability of supersonic shear flow in collisionless plasmas. Within a fluid-based framework, we employ the 16-moment transport equations -- derived from the Vlasov-Maxwell system -- to describe the plasma dynamics. By performing a modal analysis we investigate the oblique propagation of linear disturbances within a magnetized plasma characterized by a shear flow of arbitrary profile aligned with the ambient magnetic field. In the unperturbed state, both the plasma density and the magnetic field are assumed to be homogeneous. For a smooth, hyperbolic velocity profile representing supersonic shear, the governing wave equation is reduced to a form amenable to an exact analytical solution. Analytical solutions are expressed in terms of special functions that yield an infinite discrete spectrum of complex eigenfrequencies ($n = 0, 1, 2, \dots$). The instability is identified as resonant, peaking when the wave phase velocity matches the mean flow velocity, with the growth rate decreasing for higher-order modes. The results indicate that, while heat flux exerts a negligible influence under conditions of supersonic flow, the growth rate decreases and approaches an asymptotic value as the Mach number increases. Notably, the instability vanishes in the vortex sheet limit, distinguishing it from the classical Kelvin-Helmholtz mechanism. These findings suggest that this specific instability holds significant potential for explaining the problem of observed boundaries between isotropic and anisotropic proton temperature regions in a low-beta solar wind plasma. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.13305 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13305v1 Announce Type: cross Abstract: Neural ordinary differential equations (Neural ODEs) often fit training trajectories while generalizing poorly to unseen initial conditions and long horizons. We propose MPINeuralODE, which combines a soft physics-informed residual with a Multiple-Initial-Condition (MIC) multiple-shooting curriculum whose ingredients are structurally complementary: the physics term anchors the vector-field magnitude on the support that MIC enlarges. We evaluate along three axes: out-of-sample error, long-horizon stability, and Hamiltonian drift, which together expose whether the learned dynamics recover the underlying vector field. On Lotka-Volterra, MPINeuralODE achieves the lowest out-of-sample and long-horizon MSE among data-driven methods, with a 26% reduction over the baseline Neural ODE, while essentially matching the PINN ablation on Hamiltonian drift. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.13654 Thu, 14 May 2026 00:00:00 -0400 arXiv:2605.13654v1 Announce Type: cross Abstract: We report the experimental characterization of free-surface deformations generated by three-dimensional homogeneous and isotropic turbulence. Using Fourier transform profilometry in a jet-forced turbulent tank, we perform spatiotemporal measurements of the surface elevation field over a wide range of turbulence intensities. The standard deviation of surface deformations scales linearly with subsurface velocity fluctuations. The spectra of surface deformations highlight the coexistence of two mechanisms: transient coherent structures (e.g., upwelling) contributing to the low-frequency, large-scale spectral components, and a passive response to subsurface turbulent pressure fluctuations responsible for the power-law spectral scaling. The wavenumber and frequency spectra of surface deformations exhibit similar power-law exponents (-2.5), suggesting the advection of turbulent structures at the free surface. We develop a linear response model based on the transfer function from the free surface to turbulent pressure fluctuations, incorporating wave-turbulent damping. The model successfully predicts the main features of the turbulent surface: spatiotemporal spectrum shape, similar spectrum power-law exponents (-7/3), and dominance of passive response over wave generation. These findings provide new insights into free-surface turbulence in regimes where turbulent velocities remain below the surface-breaking threshold. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.11454 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11454v1 Announce Type: new Abstract: An improved neural refractive-index-primitive method for background-oriented schlieren tomography is presented, enabling continuous three-dimensional reconstruction of refractive-index fields using a compact multilayer perceptron. The method adopts the refractive-index field as the sole neural primitive and integrates multiresolution hash encoding, automatic-discrete gradient losses, and a three-dimensional mask to enable fast convergence and high-resolution, spatially coherent reconstructions. Tests on numerical combustion phantoms and real flame data demonstrate accurate recovery of both large-scale structures and fine-scale turbulence, strong robustness to noise, and clear advantages over frequency-encoding-based and voxel-based reconstruction methods. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.11797 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11797v1 Announce Type: new Abstract: Existing models for droplet impact prescribe the spreading contact time and effective spreading velocity from asymptotic arguments, which prevents a self-consistent prediction of the maximum spreading ratio across regimes. Here, the total spreading time and characteristic spreading velocity are derived directly from the energy balance, with explicit capillary and viscous contributions. Multiplying this time and velocity to obtain the maximum spreading diameter yields a closed, unified scaling law for the maximum spreading ratio of wetting drops across inertio-capillary and inertio-viscous regimes. The resulting expression quantitatively collapses the present measurements and literature data over wide ranges of Weber and Ohnesorge numbers, droplet sizes, and surface wettabilities without prefactors that need to be adjusted to a certain regime. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.11969 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11969v1 Announce Type: new Abstract: Free-surface synthetic Schlieren (FS-SS) is a high-resolution, refraction-based optical technique for measuring the instantaneous elevation of a liquid interface. Under the assumptions of small amplitude, small slope, and small paraxial angle, the method yields a linear relationship between the gradient of the surface elevation and the apparent displacement field of a refracted pattern imaged through the surface. Here, we propose three new, nonlinear extensions of the FS-SS method that are specifically dedicated to telecentric imaging. Paraxial distortions are eliminated with a telecentric lens, thereby simplifying the optical model. This allows us to derive nonlinear surface reconstruction models that reach beyond the usual limits of small slope and small wave-magnitudes. We implement these nonlinear surface reconstruction algorithms and compare them to the original, linear reconstruction algorithm in three different experiments, using a solid glass lens, spreading oil drops and nonlinear Faraday waves. At the price of a few iterations, we can realise nonlinear surface reconstructions that are more precise, in particular when we reach high slopes or high amplitude regimes. We share a library that encodes these nonlinear surface reconstruction algorithms. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.11981 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11981v1 Announce Type: new Abstract: This study investigates active flow control (AFC) of a 30P30N high-lift wing at a Reynolds number Re$_c$ = 450,000 and angle of attack $\alpha$ = 23$^\circ$ using wallresolved large-eddy simulations (LES). Two optimization strategies are explored: open-loop Bayesian optimization (BO) and closed-loop deep reinforcement learning (DRL), both targeting the mitigation of stall and the improvement of aerodynamic efficiency via synthetic jets on the slat, main, and flap elements. The uncontrolled configuration was validated against literature data, confirming the reliability of the LES setup. The BO framework successfully identified steady jet velocities that increased efficiency by +10.9% through a -9.7% drag reduction while maintaining lift. In contrast, the DRL agent, despite leveraging instantaneous flow information from distributed sensors, achieved only minor improvements in lift and drag, with negligible efficiency gain. Training analysis indicated that the penalty-dominated reward constrained exploration. These results highlight the need for carefully designed rewards and computational acceleration strategies in DRL-based flow control at high Reynolds numbers. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.12304 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12304v1 Announce Type: new Abstract: Computational fluid dynamics (CFD)-driven machine learning frameworks based on symbolic regression offer a promising pathway for turbulence model discovery, but are often hindered by numerical instability, residual stagnation, and non-physical model behavior during training. In particular, realizability, which is rarely enforced explicitly during model development, remains a critical yet overlooked requirement, especially for accurate wake prediction. In this work, a residual- and realizability-filtered CFD-driven framework is proposed to enhance both efficiency and robustness within a gene expression programming (GEP) paradigm. The method integrates two residual-based filtering criteria along with a barycentric-map-based realizability constraint directly into the CFD solution loop, enabling early identification and rejection of unstable and non-realizable candidate models. This reduces unnecessary computational effort while guiding the search toward physically admissible solutions. The proposed approach achieves a 42.3% reduction in computational cost relative to the baseline CFD-driven GEP framework and reduces non-realizable models at convergence from 58.4% to 1.7%. The framework is trained on a canonical cylinder wake. The resulting models enhance mean wake prediction and remain realizable across training and test cases, with robust generalization to diverse geometries and operating conditions, including a rectangular cylinder, an airfoil, and an axisymmetric body. The study further provides insights into realizable model statistics, coefficient trends, and conditions governing physically consistent wake behavior. These results demonstrate that incorporating realizability and stability constraints within CFD-driven learning enables efficient and physically consistent turbulence model discovery, offering a scalable pathway toward reliable data-driven closure development. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.11916 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11916v1 Announce Type: new Abstract: Air entrainment can occur when a water jet impacts a water/air interface, a process central in various real systems, ranging from dam spills to breaking waves. Despite its prevalence, a comprehensive description of the mechanism controlling bubble size distribution remains elusive. Here, we establish a link between the geometry and the dynamics of the cavity observed when an inclined impinging jet impacts a water interface and the resulting bubble cloud. We show that the bubbles result from the destabilization of the wavefield developing at the interface of the cavity. The origin of this wave field is the creation of a shear layer, due to the asymmetric detachment of the flow field from the interface. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.11991 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11991v1 Announce Type: new Abstract: Recent X-ray imaging experiments have revealed that multiphase flow through porous media involves transient fluctuations in local occupancy, even under fixed macroscopic steady-state conditions where capillary forces dominate at the pore scale. To examine how intermittency manifests at the pore scale we perform direct numerical finite volume simulations (DNS) of immiscible two-phase flow through a micro-CT-derived Bentheimer sandstone geometry at capillary numbers in the Darcy and intermittent flow regimes. We show that intermittent disconnection and reconnection are accompanied by strongly coupled local pressure redistribution and non-wetting phase flow. This behaviour contrasts with the Darcy flow regime, in which the phases remain predominantly in fixed pathways. Macroscopically the computed pressure-gradient-capillary-number relationship ($\nabla P$-Ca) recovers both the linear Darcy and the sub-linear intermittent scaling regimes consistent with previous experimental measurements. We show how an increase in intermittency leads to the transition from the linear to the sub-linear regime. Using topology-aware snap-off detection, we show that the spatial extent of intermittency increases with capillary number. Spectral, local-geometry, and network-connectivity analyses provide further evidence that the intermittent elements organise into connected conduits embedded within a stable backbone of fixed flow pathways: intermittency is a network-coupled rather than purely local process. This work characterises the pore-scale manifestation of intermittency as a periodic sequence of drainage and imbibition displacements triggered by local pressure fluctuations whose macroscopic consequence is to improve the overall mobility of the fluid phases. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.12166 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12166v1 Announce Type: new Abstract: This work employs structured input-output analysis (SIOA) to study Waleffe flow. The SIOA framework employs structured uncertainty to include the componentwise structure of nonlinearity in Navier-Stokes equations, and SIOA quantifies the flow response using structured singular values. The structured input-output analysis identifies the wavelength and inclination angle of oblique turbulent bands observed in large-domain direct numerical simulations. The structured input-output response scales over Reynolds number as $\sim Re^{1.7}$. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.12254 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12254v1 Announce Type: new Abstract: A localised overpressure translating at a uniform speed greater than a critical value acts at the interface between two deep fluid layers with different densities. We analyse the resulting wave patterns using an initial-value problem formulation within the linearised, inviscid, potential flow framework. The steady-state interface exhibits short capillary waves ahead of the forcing and long gravity waves behind it, arising from an asymmetric cancellation of Fourier components in the far field. The time-dependent part of the solution, decaying algebraically with time, plays a crucial role in this mechanism. This contrasts with classical steady approaches, which require additional conditions to select a unique solution. We extend this approach to a two-fluid interface and validate the predictions against nonlinear simulations. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2507.17081 Wed, 13 May 2026 00:00:00 -0400 arXiv:2507.17081v2 Announce Type: replace Abstract: Active particles exhibit complex transport dynamics in flows through confined geometries such as channels or pores. In this work, we employ a generalized Taylor dispersion (GTD) theory to study the long-time dispersion behavior of active Brownian particles (ABPs) in an oscillatory Poiseuille flow within a planar channel. We quantify the time-averaged longitudinal dispersion coefficient as a function of the flow speed, flow oscillation frequency, and particle activity. In the weak-activity limit, asymptotic analysis shows that activity can either enhance or hinder the dispersion compared to the passive case. For arbitrary activity levels, we numerically solve the GTD equations and validate the results with Brownian dynamics simulations. We show that the dispersion coefficient could vary non-monotonically with both the flow speed and particle activity. Furthermore, the dispersion coefficient shows an oscillatory behavior as a function of the flow oscillation frequency, exhibiting distinct minima and maxima at different frequencies. The observed oscillatory dispersion results from the interplay between self-propulsion and oscillatory flow advection -- a coupling absent in passive or steady systems. Our results show that time-dependent flows can be used to tune the dispersion of active particles in confinement. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2601.05523 Wed, 13 May 2026 00:00:00 -0400 arXiv:2601.05523v3 Announce Type: replace Abstract: Accurate prediction of flow resistance in high-Froude-number aerated flows remains challenging due to air entrainment, which causes strong spatial variability in mixture density. Here, we introduce for the first time a density-weighted (Favre) averaging approach within a Shallow Water Equation framework specifically tailored to account for this strong mixture density variability. Within this framework, we present a novel Darcy-Weisbach friction factor formulation that decomposes contributions associated with uniform flow, spatially varying flow, and temporally evolving flow, and incorporates momentum and pressure correction factors reflecting the vertical structure of the mixture. Application to experimental data demonstrates that spatial flow development systematically reduces the effective friction factor relative to the uniform-flow estimate, and that momentum-based and energy-based formulations yield nearly identical results. The framework recovers classical uniform-flow predictions in the quasi-uniform downstream region and reduces to standard single-phase formulations in the absence of aeration. Overall, it provides a physically consistent tool for resistance prediction in high-Froude-number spillways, chutes, and open-channel systems, with a structure compatible with depth-averaged numerical solvers. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2601.15246 Wed, 13 May 2026 00:00:00 -0400 arXiv:2601.15246v2 Announce Type: replace Abstract: Droplet impact and spreading on solid substrates are well understood for Newtonian fluids, yet how viscoelasticity alone modifies the maximal spreading remains unclear. To identify the mechanisms governing the spreading dynamics, we conducted impact experiments and measured the maximal spreading diameter to quantify how fluid elasticity modifies the maximal spreading of impacting droplets. Experiments were performed using fluids within a narrow range of viscosity and surface tension, but with varying relaxation times. For a wide range of conditions, viscoelastic droplets follow a similar behavior as Newtonian ones; however, their maximal spreading diameter is significantly reduced compared with the Newtonian behavior when the Deborah number is of order unity. These observations are rationalized by incorporating the viscoelastic effects into a classical energy balance model. The scaling argument obtained from this model explains the reported reduction in maximal spreading and identifies the range of fluid properties for which the strongest viscoelastic effects emerge. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.11457 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11457v1 Announce Type: new Abstract: Losses are ubiquitous in physics and are usually regarded as harmful in quantum information processing. Here, we propose a loss-induced scheme to achieve nonreciprocity and nonreciprocal entanglement in a superconducting platform, where two remote superconducting transmon qubits are connected via two lossy auxiliary cavities. The nonreciprocity in our scheme originates from interference between multiple lossy coupling paths. The coherent phases associated with the qubit-resonator couplings reverse sign under propagation reversal, while the loss-induced phases remain direction independent. Their combined effect leads to different interference conditions in the opposite directions, resulting in unequal effective couplings. We show that this loss-induced scheme can generate nonreciprocal quantum entanglement, indicating that loss can be utilized as a resource. Moreover, the tunability of nonreciprocity and nonreciprocal entanglement in our scheme can be manipulated by the relative phase induced by loss, allowing to tailor both reciprocal and nonreciprocal behaviors. Our results establish a direct link between engineered loss and nonreciprocal entanglement in quantum information processing and offer potential applications in scalable quantum networks. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11417 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11417v1 Announce Type: new Abstract: Applied category theory provides powerful mathematical tools for modelling processes and their composition. Symmetric monoidal categories, which involve series and parallel composition, are particularly well-suited for describing the composition of processes in space and time. Also called process theories, they admit string diagrams, which constitute a visually intuitive, mathematically rigorous, expressive and flexible syntax that is applicable to wide-ranging scientific domains. In this thesis, we employ string diagrams to investigate a selection of topics in the areas of quantum foundations, computing, and natural language processing: (1) We formalise constructor theory as a process theory. In the context of quantum physics, we also demonstrate the conflict between constructor-theoretic principles of locality and composition. Moreover, we argue that if the principle of locality is rejected, categorical quantum mechanics (CQM) can be conceived as a constructor theory of quantum physics. (2) We develop a formalism for wave-based logic circuits with phase encoding. We motivate the formalism using the example of spin-wave circuits, and then demonstrate its utility in design, analysis and optimisation of Boolean logic circuits. (3) We investigate the elimination of inter-language grammatical bureaucracy in the distributional compositional circuits (DisCoCirc) framework. In particular, we develop a hybrid grammar for a restricted fragment of the Urdu language, and show that Urdu text endowed with this hybrid grammar maps surjectively to DisCoCirc text circuits. Furthermore, we show that for the same language fragment, Urdu and English text circuits become the same up to gate-level translation. The aforementioned work supports the view that a process-relational outlook in science is well-supported by applied category-theoretic tools, particularly string diagrams. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11399 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11399v1 Announce Type: new Abstract: We investigate the relationship between quantum battery capacity and quantum resources in a two-qubit system consisting of mutually coupled battery and charger subsystems. We find that the battery capacity decreases monotonically with the quantum entanglement, steering, Bell nonlocality and coherence, and peaks when these four quantum resources vanish. Moreover, we reveal the capacity gap between the total system capacity and the sum of the battery and charger spin capacities, which is the residual battery capacity, and establish its positive correlation with entanglement. Furthermore, unlike the first four resources, although the battery capacity decreases monotonically with quantum imaginarity, its disappearance under system detuning does not guarantee a peak capacity, and this effect becomes more pronounced as the detuning increases. In contrast to the first five resources, the quantum state texture shows a positive correlation with battery capacity, but a negative correlation with entanglement, steering, Bell nonlocality, coherence, imaginarity, and residual battery capacity. These monotonic relationships are independent of the choice of system parameters. Our findings reveal the relationship between quantum battery capacity and quantum resources during the dynamic evolution of a quantum battery system, and advances the theory of quantum batteries and the development of quantum energy storage systems. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11382 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11382v1 Announce Type: new Abstract: High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical processing units (GPUs). This convergence calls for runtimes capable of managing both classical and quantum workloads in a unified manner. We introduce an intelligent, task-based runtime that marries the Intelligent RuntIme System (IRIS) asynchronous scheduler with a quantum programming stack through the Quantum Intermediate Representation Execution Engine (QIR-EE). Our design allows programs written in the quantum intermediate representation (QIR) to be dispatched concurrently to a variety of back-ends, including multiple quantum simulators and nascent quantum processors, enabling genuine hybrid execution on a single node. To illustrate its practicality, we partition a 4-qubit and 20-qubit circuit into three sub-circuits using quantum circuit cutting via the QCut library. Each sub-circuit is simulated independently by the QIR-EE driver within IRIS, after which a classical post-processing step merges the simulation results to recover the outcome of the original full-circuit computation. This case study demonstrates how finer task granularity can enable the parallel execution and lower the simulation burden per quantum task while preserving overall accuracy, highlighting the feasibility of our hybrid approach. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11375 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11375v1 Announce Type: new Abstract: Quantum processors are being integrated into HPC ecosystems as co-processors, where compilation of quantum circuits into hardware-executable form determines both output fidelity and runtime. Current compilers use a fixed pass sequence and ignore the fact that optimal pass selection varies with circuit, hardware, and noise conditions. We present TuniQ, a reinforcement learning-based system that selects compilation passes at each pipeline stage, adapting to circuit, backend, and current noise profile. TuniQ introduces several novel design components like a dual-encoder for stage-aware representation, shaped rewards for cross-stage credit assignment, and dynamic action masking for valid compilation. Evaluated across diverse quantum workloads on multiple IBM Quantum Cloud processors, TuniQ improves fidelity and reduces compilation time over the state-of-the-art IBM Qiskit transpiler, generalizes across backends without retraining, and scales strongly to utility-scale circuits with growing advantage. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11323 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11323v1 Announce Type: new Abstract: The measurement of top-quark spin correlations provides a key tool for probing its interactions with high precision. Owing to its extremely short lifetime ($\tau \sim 10^{-25}$ s), the top quark preserves its spin polarization information, making the $t\bar{t}$ system an ideal framework for investigating quantum correlations in high-energy physics. In this work, we analyze quantum correlations in $t\bar{t}$ pairs produced in QCD using several quantum information-theoretic measures, including Bell nonlocality, quantum steering, concurrence, and geometric quantum discord. Their dependence on kinematic variables is examined in both the $gg \to t\bar{t}$ and $q\bar{q} \to t\bar{t}$ channels, with convergence toward the $gg \to t\bar{t}$ dominated regime in the ultra-relativistic limit ($\beta = 1$). We also investigate the effect of three effective decoherence channels (AD, PD, and PF). The AD and PD channels lead to a monotonic degradation of correlations as the decoherence parameter $p$ increases, while the PF channel exhibits a symmetric behavior around $p=1/2$. The impact of these channels on quantum teleportation is analyzed, showing that it remains above the classical threshold of $2/3$ even in the presence of noise. These results indicate that certain quantum resources can persist despite decoherence, opening new perspectives at the interface of quantum information and particle physics. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11318 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11318v1 Announce Type: new Abstract: The hypergraph product creates a quantum stabilizer code from two input classical linear codes; a paradigmatic example being the surface code as a hypergraph product of two classical repetition codes. Many properties of the hypergraph product code can be inherited from those of the classical codes such as the code dimension, minimum distance and certain fault-tolerant gadgets. We investigate ways to reduce the number of physical qubits in hypergraph product codes while maintaining some of their useful properties for fault tolerance. We show that the code dimension, canonical logical basis, and minimum distances of the hypergraph product code are preserved through this reduction. We also provide distance-preserving syndrome measurement schedules as well as examples of reduced hypergraph product codes with parameter improvements such as $[\![610,64,6]\!] \rightarrow [\![441,64,6]\!]$ and $[\![1225,49,11]\!] \rightarrow [\![931,49,11]\!]$. In memory simulations with circuit-level depolarizing noise, we observe that the reduced codes can have similar subthreshold performance as their unreduced versions, but using fewer physical qubits. Finally, we show how overhead reduction can be compatible with homomorphic measurement gadgets, fold-transversal gates and automorphisms, which extends the savings to logical computation. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11285 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11285v1 Announce Type: new Abstract: Simple families of quantum Hamiltonians can simulate general many-body systems at arbitrary precision through the use of perturbative gadgets, however this generally requires interaction strengths spanning many orders of magnitude which scale polynomially in the system size and inverse precision, resulting in physically unrealisable systems. In this work, we show that for non-critical systems these required scalings can be exponentially reduced through classical post-processing, by simulating the model at smaller energy scales and extrapolating observables to the perturbative limit. In particular, we show that both local and extensive properties of thermal states with exponentially decaying correlations and ground states with a sufficiently stable gap can be simulated using gadgets whose interaction strengths scale only polylogarithmically in the inverse precision and the system size. As a key tool, we develop a generalised treatment of the local Schrieffer-Wolff transformation for geometrically quasi-local Hamiltonians over many energy scales, facilitating the analysis of perturbative gadget Hamiltonians without extensive global energy penalities, which may be of independent interest. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11228 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11228v1 Announce Type: new Abstract: We give a quantum algorithm for a novel type of black-box problem: identifying a hidden $d$-regular base graph $G$ on $n$ vertices from oracle access to an obfuscated version of it, rather than traversing it. From $G$ we build the spired graph $G_{\rm spire}$ in three steps: each vertex is lifted into an exponentially large cluster, with adjacent clusters joined by a random bipartite graph; each cluster is then crowned with a balanced spire; finally, all vertices are randomly relabelled. Specializing to $G=K_2$ recovers the welded-trees graph. Our algorithm is conceptually simple: a continuous-time quantum walk on $G_{\rm spire}$, followed by a single Hadamard test at a classically precomputed time $t^*$; the algorithm returns the candidate whose predicted amplitude is closest to the measurement. The design rests on a rigorous spectral theory: from the apex of any spire, the walk is confined to a polynomial-dimensional invariant subspace evolving under the adjacency matrix of a simpler towered graph $G_{\rm tower}$; that matrix block-diagonalizes into $n$ independent tridiagonal systems of size $n$, each solved in closed form by a Chebyshev secular equation. Efficient numerics enabled by this decomposition supply $t^*$ and the predicted amplitudes. On the prism graphs $Y_m$ versus the M\"obius ladders $M_m$ (each on $n=2m$ vertices), the numerical study supports a precise conjecture that $\widetilde O(n^2/\log n)$ measurements at evolution time of order $m^2$ suffice to distinguish the two families; we have tested $4 \le m \le 5121$ ($n$ up to $10242$). By analogy with the welded-trees lower bounds, we further conjecture that any classical algorithm requires queries exponential in $n$. Together these conjectures point to an exponential quantum speedup for the identification of an obfuscated base graph. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11213 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11213v1 Announce Type: new Abstract: We study parity features as representations that can be evaluated entirely classically once the binary or quantized input representation and parity words are fixed, particularly when labels depend on higher-order feature interactions or when discrete inference interfaces support perturbation robustness. A parity feature is a signed product over selected bits of a binary input: once the participating bits are known, evaluation requires no quantum resources. Reaching a useful parity representation requires solving two challenges. When the input is parity-ready (a meaningful binary string), the challenge is basis discovery: selecting useful parity words from a combinatorial search space. Otherwise, the challenge is encoding: constructing a binary vector on which parity computation is meaningful. We use hybrid quantum-classical training pipelines to address these: learnable Pauli word selection for basis discovery, learned projection encodings for continuous embeddings, and sPQC-Parity for discrete inputs. On three native-binary parity tasks with 5-10 qubits, the learned parity basis improves mean accuracy by 23.9% to 41.7% over logistic-regression and support-vector baselines. A model comparison shows that the improvement comes primarily from discovering the right parity basis, rather than from quantum moment computation at inference. On five continuous text benchmarks, learned projection recovers much of the loss introduced by dimensionality reduction and fixed binarization, exceeding the full continuous baseline on CR, SST-2, and SST-5. On three encoding-limited discrete datasets, when compared with PCA-bin as the baseline, sPQC-Parity reaches 94.6% improvement on mushroom, 3.0% on splice, and matches PCA-bin on promoter. We also analyze inference robustness under binary or quantized inference, where rounding gives exact invariance below half the quantization step. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11158 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11158v1 Announce Type: new Abstract: Characterizing errors on many-qubit quantum computers remains a key challenge to understanding and improving the performance of these devices. Current characterization methods either don't scale beyond a few qubits, or make simplifying assumptions (such as assuming stochastic Pauli error) that obscure the underlying physical error mechanisms. In this work, we present a scalable extension to gate set tomography-linearized gate set tomography-that enables characterization of many-qubit systems. Linearized gate set tomography relies on sparse error models, a linear approximation to enable efficient data fitting, and data from shallow circuits-so that the systematic error in the linear approximation is small. We demonstrate the accuracy of our technique using simulations of a ten-qubit system with coherent and stochastic errors, including coherent crosstalk, and we demonstrate that it is robust in presence of additional errors that are not included within the sparse error model ansatz. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11092 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11092v1 Announce Type: new Abstract: We study how a punctured surface code can turn many local $Z$-type couplings into one protected logical signal for distributed quantum metrology, where the goal is to estimate a weighted average of the coupling strengths. We consider an ordinary planar patch with two $X$-cut holes and provide a distributed sensing protocol where all $Z$-type couplings correspond to the same nontrivial logical $\bar{Z}$ for the punctured surface code. When the couplings are disjoint, we show that the relevant global condition is equivalent to the existence of a closed dual loop, called a witness, that has an odd number of intersections with every chain. Together with a local clean opening condition, this witness criterion gives a concrete punctured-code construction in which all signal chains implement the same nontrivial logical $\bar Z$. For three-body interactions with overlapping supports, we also identify the class of interactions where our punctured surface code protocol applies. Overall, our results provide a novel, noise-robust distributed sensing protocol for many-body interactions, with corresponding topological design criteria. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11088 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11088v1 Announce Type: new Abstract: It is desirable that a distributed quantum computer can operate despite the replacement or failure of its constituent components, allowing the reliability of the distributed system to exceed that of its subcomponents. We first show that when quantum error correction is performed over a modular quantum network, quantum devices can be swapped out or replaced, during operation, with minimal impact on logical error rates. We also investigate the ability of the toric and hyperbolic Floquet quantum error correcting codes to protect logical information under low rates of modular node failure. In particular, we show that under the proposed distributed quantum error scheme, the selected codes are able to maintain good logical error suppression during the failure of entire nodes. For catastrophic node failure of probability p/100, we suggest that a distributed toric code would outperform one implemented on a monolithic device below a physical error rate of 0.05%. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11076 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11076v1 Announce Type: new Abstract: Random circuit models often describe local dynamics using generic two-qubit gates, which have proven successful in capturing entanglement growth and operator spreading in many contexts. This approach naturally leads to the expectation that detailed gate structure plays only a limited role in coarse-grained entanglement and scrambling diagnostics. We show that the internal structure of multipartite circuit primitives can significantly influence these dynamical rates, even within a fixed random-circuit architecture. To investigate this, we study an exactly simulable family of Clifford quantum circuits built from fixed $n$-qubit graph-state preparation unitaries, which we treat as elementary building blocks. Specifically, we consider a one-dimensional chain of $N$ qubits initialized in a product state and evolved by layers in which nonoverlapping length-$n$ blocks are placed at uniformly random positions with sparsity $\alpha$. We find that different choices of graph-state building blocks lead to strongly varying dynamical rates. Graph states that are inequivalent under local Clifford (LC) transformations generate sharply different entanglement velocities $v_E$ and butterfly velocities $v_B$, even though the circuits are drawn from the same ensemble with identical architecture and randomness parameters. We further show that this hierarchy is captured by two complementary block-level characteristics: the distribution of entanglement across internal bipartitions of the graph state, which correlates with $v_E$, and a graph-theoretic connectivity profile across bipartitions, which correlates with $v_B$. Neither descriptor alone fully determines the dynamics; rather, entanglement growth and operator spreading are controlled by distinct structural features of the local circuit blocks. Notably, AME states appear among the fastest scrambling building blocks within the ensembles studied here. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11073 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11073v1 Announce Type: new Abstract: We present a novel implementation of an n-qubit fanout gate using resonance engineering. Our proposed mechanism uses Jaynes-Cummings interactions between multiple qubits and a common harmonic oscillator to realize a fanout gate at the system-level. Our theoretical analysis establishes upper bounds on the gate error, demonstrating linear infidelity scaling in constant time -- a favorable trade-off compared to a conventional CNOT decomposition. To validate the performance of our scheme at large system sizes, we exploit permutation symmetry to reduce the simulation complexity from exponential to polynomial in the number of qubits, enabling simulation up to 100 qubits. The results of this numerical analysis are consistent with our theoretical findings and allow us to characterize the performance well. Our gate will enable faster stabilizer readouts and could provide polynomial speedups in many quantum algorithms. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11041 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11041v1 Announce Type: new Abstract: A giant atom is an artificial matter configuration whose spatial scale is comparable to the wavelength of the interacting electromagnetic wave, such that the usual electric-dipole approximation is no longer valid. As a consequence, certain quasi-direct scattering channels for the electromagnetic wave can arise. Given that the well-known input-output approach can only work for the usual point scattering configuration, wherein the electric-dipole approximation is well satisfied, here we develop a modified input-output approach, wherein an additional low-Q cavity channel is introduced, to treat the electromagnetic scattering problem of a giant atom. We demonstrate that, beyond the multiple coupling-point model used widely in recent publications, the present approach can well explain the Fano-type scattering spectra observed generically and extract certain physical parameters, including the energy dissipation parameter of a two-level giant atom and its coupling strength with the scattered electromagnetic wave. Consequently, we argue that various high-performance optical quantum devices, typically the giant-atom-based optical quantum switches, can be generated by engineering the Fano-type scatterings of giant atoms. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11031 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11031v1 Announce Type: new Abstract: We identify a class of finite quantum systems, namely, acyclic systems whose transition graph is a directed acyclic graph (DAG), for which the Born series collapses into an exact algebraic identity with finitely many terms and strictly zero truncation error. The sufficient condition is the nilpotency of the transfer operator T = G_0(E)V. If T^{m+1} = 0, then the exact solution of the Lippmann-Schwinger equation is the finite sum |psi> = sum_{k=0}^{m} T^k |phi>, with no condition on ||T||. We prove that the acyclicity of the transition graph implies the nilpotency of T (Theorem 19), and that the nilpotency index coincides with the maximal path length of the graph (Proposition 21). The main result (Theorem 23) concerns the four-level quantum system with diamond-graph structure. In this case, the transition amplitude toward the final state is A_4 = t_{42}t_{21} + t_{43}t_{31}, an exact algebraic identity encoding constructive interference, exact destructive interference (dark state formation), and partial interference. The first-order Born approximation predicts identically zero amplitude in all regimes, thereby failing quantitatively in 100% of the cases. The Born-SON framework additionally provides the exact full resolvent, the exact T-matrix, explicit error control in the quasi-nilpotent regime, and a scalar structural metric, the Born-SON depth, quantifying the intrinsic complexity of an acyclic quantum system. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.11016 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11016v1 Announce Type: new Abstract: Many quantum computing workflows manipulate long lists of Pauli strings. A basic classical subroutine involves taking $m$ Pauli strings on $n$ qubits, each of weight bounded by a constant, to determine if they are pairwise commuting, identify any counterexamples, or calculate the exact number of anticommuting unordered pairs. The standard general-purpose route represents Pauli strings in binary symplectic form and checks pairs in $O(m^2)$ time. Here, we provide an $O(m)$ algorithm for the bounded locality regime. It maintains counts of all labeled subpatterns of previously inserted strings and answers each new string query by a subset zeta identity. Our algorithm is particularly useful for processing large collections of Pauli strings within the bounded locality regime. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.10967 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.10967v1 Announce Type: new Abstract: We develop a theoretical framework for describing superposed coherent states in graphene quantum systems using the concept of catability as a phase-sensitive metric functional measure. In this case, the formalism quantifies interference stability and coherence structure via phase-dependent contributions of quantum superposition states. Catability is defined as a functional measure sensitive to relative phase variations within coherent state combinations, serving as a diagnostic tool for quantum interference effects in graphene-based systems. Also, the formulation is extended using Lie algebra techniques, where the underlying symmetry structure of graphene quantum states is represented through operator algebras governing state transformations in quantum space. In this context, to describe nonlocal propagation and phase-resolved dynamics, a Green function approach is incorporated, enabling systematic treatment of quantum correlations in a spatially extended structures framework. A unified framework is constructed by combining Lie algebraic symmetry analysis with Green function propagation theory, yielding a consistent description of phase-sensitive catability in complex graphene quantum configurations within the framework approach. Results provide a structured route for testing coherence, interference stability, and quantum state control in low-dimensional quantum materials systems. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.10963 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.10963v1 Announce Type: new Abstract: Recent advancements in quantum computing highlight the need for efficient encoding of classical data into quantum states to ensure robust quantum information processing. Traditional encoding schemes often impose impractical requirements about the knowledge of quantum states and lack adaptability to noisy quantum channels and broader tasks. To address these limitations, we propose a novel end-to-end learnable quantum transcoding scheme explicitly optimized for compactness and robustness in noisy quantum communication scenarios. Our approach integrates neural network-based data compression with Cholesky decomposition-based quantum encoding and bypasses full density matrix reconstruction. Through normalized quantum observables, our method enables efficient tomography and achieves high reconstruction and classification performance even under extreme noise conditions. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2604.08321 Wed, 13 May 2026 00:00:00 -0400 arXiv:2604.08321v3 Announce Type: replace Abstract: Ion temperature clamping -- the saturation of the ion temperature regardless of heating power -- is observed across stellarator experiments. We propose a minimal model based on Anderson localisation. Starting from a reduced fluid model for drift waves [Phys. Fluids 26, 880 (1983)], we show that aperiodic stellarator geometry leads to a quasiperiodic Hill equation for the ion-temperature-gradient (ITG) mode structure. In a tight-binding approximation this equation reduces to an Aubry--Andre--Harper difference equation, suggesting an Anderson-localisation mechanism for ITG eigenfunctions. We identify a three-threshold ordering: the linear instability threshold lies below the Anderson localisation threshold, which lies below the observed clamp. This is conjectured to create a low-transport second regime above the instability threshold, qualitatively analogous to the second stability regime of MHD ballooning theory, and provides a power-independent lower bound on the observed gradient. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2601.20734 Wed, 13 May 2026 00:00:00 -0400 arXiv:2601.20734v3 Announce Type: replace Abstract: In thermally non-equilibrium plasmas, conventional harmonic models can significantly mispredict superelastic electron heating rates. When the vibrational temperature exceeds the gas temperature ($T_{\rm v}>T_{\rm g}$), these models underestimate energy transfer by several times; conversely, they overestimate heating when $T_{\rm g}>T_{\rm v}$. We show that this discrepancy arises from neglecting the exponential heating from overpopulated, high-lying states in anharmonic Treanor-Gordiets distributions, and their thermodynamic depopulation at high gas temperatures. To resolve this, we derive a closed-form, thermodynamically consistent macroscopic closure based on detailed balance and a second-order Dunham expansion. This unified framework introduces an analytic anharmonic correction factor that captures the kinetic competition between vibrational-vibrational (V-V) up-pumping and vibrational-translational (V-T) relaxation. By predicting the Treanor minimum, this formulation recovers the fidelity of full state-to-state kinetic benchmarks. Ultimately, this model provides a governing equation for heat exchange between electrons and excited states in non-equilibrium environments -- including plasma-assisted combustion and hypersonic flows -- enabling the development of accurate, rate-limited reduced-order models for macroscopic fluid solvers. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.11139 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11139v1 Announce Type: cross Abstract: Electron-only reconnection (EREC) is a magnetic reconnection regime occurring within subion-scale current sheets (CSs), exhibiting only electron jets, without any ion outflows. EREC has been first observed in the Earth's magnetosheath, where its occurrence is linked to the small correlation length of magnetic fluctuations, limiting the growth of CSs to very large scales. On the other hand, the development of EREC in open systems with large magnetic correlation lengths, such as the solar wind (SW), remains an open question. To address this problem, we employ a large-scale 2D hybrid simulation with finite electron inertia, investigating the development of EREC driven by turbulence. By injecting energy at very large scales, we allow EREC to develop spontaneously due to the turbulent cascade, without any external small-scale forcing or imposed constraints on the turbulence correlation length. We find that EREC develops in our simulation via two distinct turbulence-driven mechanisms: (1) secondary EREC induced by the interaction of plasmoids in the outflows of large-scale ion-coupled reconnection; (2) EREC directly driven at subion scales by the electron Kelvin-Helmholtz instability in small-scale velocity shears. Furthermore, we perform a statistical analysis of CSs using the machine-learning clustering algorithm HDBSCAN, showing that subion-scale CSs capable of hosting EREC are dominant in our simulation. Our results suggest that EREC could occur even in large-scale space and astrophysical systems, like the SW, driven by secondary turbulent processes, potentially playing a key role in dissipating energy at kinetic scales. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.12132 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12132v1 Announce Type: new Abstract: Recent developments in high peak-power table-top laser systems reaching highly relativistic light intensities have led to significant advances in laser-driven particle acceleration schemes (mainly the laser wakefield acceleration, LWFA) that heavily rely on particle-in-cell (PIC) simulations for the microscopic understanding of the acceleration process. Efficient algorithms have been developed by taking advantage of the cylindrical geometry of the laser-plasma acceleration interaction, which reduces the computational and memory costs of these simulations, but with the trade-off of reduced accuracy compared to the 3D simulations. The most successful solution solves the Maxwell equations on a Fourier-Bessel spectral basis in this geometry, as used by the well-known FBPIC code. In this work, we present a solution that is a real-space equivalent of the latter using the finite difference exponential time-domain method. Spatially, we represent the derivatives with high-order staggered finite differences locally and address issues of the near-axis particle representation. Additionally, we also develop an exponential solution to propagate the laser envelope potential with high accuracy in the cylindrically symmetric PIC model. We show that this method provides a very high accuracy without relying on a transformation to special basis functions. We verified the accuracy and the convergence of these methods in various benchmarks involving laser propagation in vacuum and in underdense plasma. Electron injection in the non-linear laser wakefield regime has also been simulated and the results are compared with 3D simulations, and to the cylindrical spectral solution of FBPIC. We found good agreement between these methods; however, the spectral solution resulted in less energetic electrons and a smoother spatial distribution near the cylindrical axis. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.12116 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12116v1 Announce Type: new Abstract: This is the six month progress report to Fusion Energy Science (FES) and the American Science Cloud (AmSC) on the MPEX AI Digtial Twins project that was started in October 2025. There are two milestones to demonstrate the Artificial Intelligence (AI) advantage for MPEX operations and scientific discovery, that will be completed by June 2026. The first is a Helicon AI Hot-Spot Controller (Sec. 3.1), which is the helicon heating component of the more comprehensive planned MPEX AI Hot Spot Digital Twin (Sec. 3). The second is an E-beam Damage Assessment Digital Twin (Sec. 4.1), which is a reduced electron beam damage modality prototype for the MPEX AI Damage Assessment Digital Twin (Sec. 4). These two phase I milestones are on track for the June demonstration. In addition to these two milestones, progress on configuring the Galaxy software interface for automation, validation and data analysis is reported (Sec. 5). This interface now connects a subset of the main physics simulation codes to DOE HPC resources and will connect to the MPEX data acquisition system so that analysis of data, validation and execution of simulations can be performed by the scientist or by AI-Agents. When AmSC is ready to accept connections and data, Galaxy will be the MPEX interface to AmSC Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.11305 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11305v1 Announce Type: new Abstract: Dynamic alignment in magnetohydrodynamic (MHD) turbulence is usually interpreted as a cascade-wide tendency of Elsasser increments to become increasingly collinear at smaller scales. We argue instead that the standard measurements mainly detect a conditional survival effect of intense events. In high-resolution Johns Hopkins MHD simulations, the typical folded Elsasser-increment angle remains only modestly below the random-orientation baseline and shows no evidence for a rigid, monotone, volume-filling ordering of the cascade. Much smaller angles appear primarily in the strongest Elsasser-amplitude events, while conditioning on current density leaves the angle close to its unweighted behavior. Shuffled-null tests show that this reduction is caused by a genuine negative covariance between event amplitude and angular misalignment, not by weighting alone. Cross-scale angular correlations are measurable but decaying, indicating partial and non-rigid persistence of the local alignment field. A finite-time state-retention test directly supports the proposed mechanism: high-amplitude large-angle events leave their amplitude--angle sector faster than high-amplitude small-angle events, while incoming transitions continually replenish the large-angle sector. NASA Wind solar-wind observations show the same angle--amplitude hierarchy and negative covariance in Taylor-sampled Elsasser increments. These results indicate that dynamic alignment, as measured by conventional weighted diagnostics, is best understood as selective sampling of longer-lived intense small-angle events, not as a cascade-wide alignment of typical MHD fluctuations. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2203.06695 Wed, 13 May 2026 00:00:00 -0400 arXiv:2203.06695v2 Announce Type: replace-cross Abstract: A projective quantum logic in terms of relative states is developed, emphasizing the importance of information transfer between a system under study and its environment. The need for accounting for the historical evolution of system is highlighted and it is found that the conjunction of observations involving conjugate variables can be consistently defined but is found to be non-commutative. It is shown that the Birkhoff and von Neumann approach to quantum logic is unable to deal with such conjunctions. It is found that whilst the proposed scheme is still not distributive in general, the discrepancy is directly related to interference effects that may disappear when information is transferred from the system to its environment. It is argued that the probabilities associated with projections be mapped to an orthocomplemented ternary logic, in which it is shown that the law of the excluded middle still holds. Physics/physics.hist-ph_(History_and_Philosophy_of_Physics) https://arxiv.org/abs/2602.16515 Wed, 13 May 2026 00:00:00 -0400 arXiv:2602.16515v2 Announce Type: replace Abstract: Accurate assessment of anthropogenic climate change relies on historical instrumental data, yet observations from the early 20th century are sparse, fragmented, and uncertain. Conventional reconstructions rely on disparate statistical interpolation, which tends to smooth local features and create unphysical artifacts, often leading to an underestimation of intrinsic variability and extremes. While recent machine learning approaches have improved reconstruction accuracy, they remain confined to purely spatial inpainting of coarse-resolution fields. Here, we present a unified, probabilistic generative deep learning framework that overcomes these limitations and reveals previously unresolved historical climate variability back to 1850. Leveraging a learned generative prior of Earth system dynamics, our model performs probabilistic inference to estimate spatiotemporally consistent historical temperature and precipitation fields from sparse observations. Our approach preserves the higher-order statistics of climate dynamics, transforming reconstruction into a robust uncertainty-aware assessment. We demonstrate that our reconstruction mitigates the smoothing effects inherent in widely used historical reference products, including those underlying IPCC assessments, especially regarding extreme weather events. Notably, we uncover higher early 20th-century global warming levels compared to existing reconstructions, primarily driven by more pronounced polar warming, with mean Arctic warming trends exceeding established benchmarks by 0.15--0.29C per decade for 1900--1980. Conversely, for the modern era, our reconstruction indicates that the broad Arctic warming trend is likely overestimated in recent assessments, yet explicitly resolves previously unrecognized intense, localized hotspots in the Barents Sea and Northeastern Greenland. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2605.12470 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12470v1 Announce Type: new Abstract: Topography at the core-mantle boundary (CMB) couples the outer core to the mantle and likely generates observable variations in the length of day ($\Delta$LOD) and the geomagnetic field, though these effects remain poorly understood. We use direct numerical simulations of rotating shell convection with finite-amplitude CMB topography to investigate dynamical effects on the outer core. A range of topographic shapes is used, including individual spherical harmonics and a model representing seismically inferred heterogeneities in the deep mantle. As predicted by prior linear theory in the rotating annulus model, a new instability arises for Rayleigh numbers below the onset of convection; we confirm its existence in a global geometry, though the predicted scalings are quantitatively modified. The shape of the geostrophic contours -- lines of constant axial height -- plays a central role: deformed contours allow buoyancy to do work on the time-averaged flow, driving increases in Reynolds and Nusselt numbers of up to $\sim$100\% relative to a spherical boundary. Previous work showed that topographic torques scale linearly with topographic amplitude and quadratically with flow speeds; we confirm this scaling and extend it with new theory that estimates the torques for global, spectrally broad topography. When extrapolated to core conditions, the predicted torques are consistent with the magnitude required to drive observed decadal and subdecadal $\Delta$LOD variations. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2605.12329 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12329v1 Announce Type: new Abstract: A numerical validation of the stress-jump coupling conditions for Stokes-Darcy flow in two dimensions is presented, addressing a gap that has remained since their introduction by Angot et al.. These conditions, formulated for arbitrary flow directions at the interface between a porous medium and an adjacent free-flow region, involve a friction tensor whose coefficients are not known a priori. We calibrate these parameters for a range of porous-medium configurations and flow regimes by matching the macroscopic model to reference solutions derived from processed pore-scale simulations. Several optimization strategies are assessed for this calibration task. The results show that, although three parameters are formally required, exploiting structural properties of the porous medium enables an effective reduction to a one-dimensional calibration with negligible loss in accuracy. A regional sensitivity analysis further indicates that even coarse parameter estimates can yield a well-performing model, highlighting the robustness and practical applicability of the stress-jump formulation. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2605.11245 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11245v1 Announce Type: new Abstract: Iron disproportionation reactions in mantle silicates can produce metallic iron that drives Earth's deep mantle toward metal saturation under reduced conditions. Subducting slabs transport hydrated silicates to these depths, where interactions with metallic iron can reduce structurally bound hydrogen in silicates to reduced hydrogen-bearing phases, such as molecular hydrogen or iron hydrides, leaving mantle rocks in effect dry. Using the thermodynamic code HeFESTo with its latest self-consistent treatment of iron-bearing mantle phases, we investigate the stability and distribution of metallic iron in Earth's pyrolitic mantle across a broad range of oxidation states, represented by whole-rock Fe3+/$\Sigma$Fe ratio from 1% to 10%. We find that metallic iron is present through much of the lower mantle across this range and, under very reduced compositions of whole-rock Fe3+/$\Sigma$Fe = 1-3%, extends into the upper mantle. Where subducted water meets metal-saturated regions, hydrous melts may form and migrate upward, rehydrating the overlying mantle or pooling near the transition zone. Metal saturation can thus redistribute hydrogen internally, creating a sharp contrast between a wet shallow mantle and a dry deep mantle. This redox-driven redistribution can decrease mantle silicate water storage capacity by 64-96% today, to only 0.1-0.8 modern ocean masses, and may explain the viscosity contrast near the upper-lower mantle boundary. Although quantitative estimates of metal abundance and distribution depend on thermodynamic assumptions and remain uncertain above 50 GPa, our results reveal the role of redox reactions between disproportionated iron and subducted water in governing the speciation and redistribution of hydrogen in Earth's mantle. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2605.11109 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11109v1 Announce Type: new Abstract: Self-supervised learning (SSL) has emerged as a promising approach to seismic data denoising as it does not require clean reference data. In this work, the deployment of the Noisy-as-Clean (NaC) method was evaluated for real seismic data denoising under controlled conditions. Two independent seismic acquisitions, each comprising noisy and filtered data, were organized into four real datasets. The NaC SSL method was adapted to add real noise to the noisy input, controlled by a parameter. An experimental protocol with ten experiments was designed to compare different strategies for deploying the NaC SSL method with the supervised learning baseline, using identical network topology and hyperparameters. The models were evaluated in terms of denoising performance, computational cost, and generalization capability. The results show that the synthetic additive white Gaussian noise (AWGN) is inadequate for the denoising of seismic data within the NaC method, and performance strongly depends on the compatibility between the injected and actual noise characteristics. Furthermore, both the characteristics of the seismic data and the noise level influence the performance of the model. Self-supervised fine-tuning on test data has improved SSL performance, whereas no such gain was observed for fine-tuning of supervised models. Finally, NaC has shown to be a simple, effective, and model-independent method that offers a feasible solution for the denoising of real seismic data. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2512.16941 Wed, 13 May 2026 00:00:00 -0400 arXiv:2512.16941v2 Announce Type: replace Abstract: The string tensions can be dynamical in the modified measure formalism and appear as an additional dynamical degrees of freedom . These tensions may not be universal, instead, each string generates its own tension. We then consider a new bulk field that can couple to the strings, the tension scalar which changes locally the tension along the world sheet. In the case with two string tensions there is a braneworld solution which gives rise to an induced de Sitter space in the brane, avoiding swampland constraints of the standard string theory. Strings with different tension to ours can appear also as Dark Matter and since they share the same space and compactifications as visible matter, they should lead to Dark copies of the standard model, Physics/physics.gen-ph_(General_Physics) https://arxiv.org/abs/2605.10986 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.10986v1 Announce Type: new Abstract: We discuss a formal and physical connection between the Bohm quantum potential and the scalar mode of the Aharonov-Bohm extension of electrodynamics. The analysis is motivated by the effective non-relativistic bosonic model recently proposed by Minotti and Modanese, in which the electromagnetic field is coupled to a conserved current while the field equations contain an additional source term. In the Madelung representation $\psi=R\exp(i\theta/\hbar)$, the Bohm quantum potential $ Q_B=-\frac{\hbar^2}{2m}\frac{\nabla^2 R}{R} $ is determined by the relative curvature $\nabla^2R/R$ of the amplitude profile $R$. In the same bosonic model, the scalar electromagnetic mode $S=\partial_\mu A^\mu$ is sourced by the extra-current $I=\partial_\mu j^\mu$, which contains the density-weighted electromagnetic combination $\nabla\cdot(R^2\mathbf A)$. Thus $Q_B$ does not act as a direct source of $S$; rather, the two quantities probe different differential aspects of the same amplitude profile: $Q_B$ is sensitive to the relative curvature of $R$, whereas the source of $S$ is sensitive to its density and gradient content through $R^2$ and $\nabla R$. We show that, once boundary and normalization data are fixed, this observation may be written as a mediated functional dependence of $S$ on $Q_B$ through $R$. We also clarify the physical status of $Q_B$: although it is state-dependent and should not be interpreted as an autonomous external potential, its density-weighted integral gives the amplitude-gradient energy, equivalently a Fisher-information contribution. This makes $Q_B$ a compact diagnostic of quantum pressure, rigidity, and inhomogeneity of a bosonic condensate. The resulting link with $S$ is therefore best understood as a structural relation between the order-parameter amplitude profile of the condensate and the scalar sector of the extended electromagnetic theory. Physics/physics.gen-ph_(General_Physics) https://arxiv.org/abs/2602.22776 Wed, 13 May 2026 00:00:00 -0400 arXiv:2602.22776v3 Announce Type: replace-cross Abstract: In experimental High-Energy Physics, unfolding refers to the problem of estimating the underlying distribution of a physical observable from detector-level data, in the presence of statistical fluctuations and systematic uncertainties. Starting from its reformulation as a regularized quadratic optimization problem, we develop a framework to address unfolding using both classical and quantum-compatible methods. In particular, we derive a Quadratic Unconstrained Binary Optimization (QUBO) representation of the unfolding objective, allowing direct implementation on quantum annealing and hybrid quantum-classical solvers. The proposed approach is implemented in QUnfold, an open-source Python package integrating classical mixed-integer solvers and D-Wave's hybrid quantum solver. We benchmark the method against widely used unfolding techniques in RooUnfold, including response Matrix Inversion, Iterative Bayesian Unfolding, and Singular Value Decomposition unfolding, using synthetic dataset with controlled distortion effects. Our results demonstrate that the optimization-based approach achieves competitive reconstruction accuracy across multiple distributions while naturally accommodating regularization within the objective function. This work establishes a unified optimization perspective on unfolding and provides a practical pathway for exploring quantum-enhanced methods in experimental HEP data analysis. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.11359 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11359v1 Announce Type: cross Abstract: Scientific data processing often requires task-specific algorithms or AI models, creating a barrier for domain scientists who need to analyze their data but may not have extensive computing or image-processing expertise. This barrier is especially pronounced when data are noisy, have a high dynamic range, are sparsely labeled, or are only loosely specified. We introduce CVEvolve, an autonomous agentic harness with a zero-code interface for scientific data-processing algorithm discovery. CVEvolve combines a multi-round search strategy with tools for code execution, evaluation implementation, history management, holdout testing, and optional inspection of scientific data and visual outputs. The search alternates between discovery and improvement actions, and uses lineage-aware stochastic candidate sampling to balance exploration and exploitation. We demonstrate CVEvolve on x-ray fluorescence microscopy image registration, Bragg peak detection, and high-energy diffraction microscopy image segmentation. Across these tasks, CVEvolve discovers algorithms that improve over baseline methods, while holdout test tracking helps identify candidates that generalize better than later over-optimized alternatives. These results show that zero-code, autonomous LLM-powered algorithm development can help domain scientists turn unstructured scientific image data into practical algorithms and downstream scientific discoveries. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.11197 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11197v1 Announce Type: cross Abstract: Regression to the Mean and Regression Dilution are often viewed as unrelated issues in the clinical and ecological literatures. In reality, they are different names for the same problem: measurement error in an independent variable that biases the perceived relationship between two factors. This study unifies these traditions by comparing specialized clinical tools, like the Berry correction, with standard structural estimators such as Major Axis and Reduced Major Axis regression. Using an analytical framework, we evaluate how these methods perform across various noise levels and sample sizes. Our results show that the Berry method is a specialized tool designed for clinical scenarios where a 1:1 relationship is expected. However, applying it to ecological trade-offs with negative slopes can lead to severe errors. We provide maps of optimality to identify which estimator most accurately recovers the true biological signal under different conditions. By reconciling these disparate methods, we offer a principled guide for researchers to choose the correct tool based on their data's noise profile rather than their disciplinary tradition. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.09523 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.09523v2 Announce Type: replace-cross Abstract: Neural operators provide fast surrogate models for time-dependent partial differential equations, but their standard autoregressive use usually assumes that the instantaneous field $u(t,\cdot)$ is a complete state. This assumption fails for delay equations, distributed-memory systems, and other non-Markovian dynamics: two trajectories may agree at time $t$ and nevertheless have different futures because their histories differ. We introduce the History-Space Fourier Neural Operator (HS-FNO), a neural operator for delay and memory-driven PDEs formulated on the lifted state $u_t(\theta,x)=u(t+\theta,x)$, $\theta\in[-\tau,0]$. The key computational step is to decompose one history-state update into a learned predictor for the newly exposed future slice and an exact shift-append transport for the portion of the history window already known from the previous state. This avoids learning deterministic history coordinates, reduces the learned output dimension, and enforces the natural discrete history update. We test HS-FNO on five benchmark families covering delayed reaction--diffusion, spatial epidemiology, nonlocal neural-field dynamics, delayed waves, and distributed-memory closures. Across ten random seeds, HS-FNO attains the lowest aggregate one-step, history-space, and rollout errors among the principal baselines. The largest gain occurs in autoregressive prediction, where aggregate rollout error decreases from $0.241$, $0.188$, and $0.185$ for current-state, lag-stack, and unconstrained history-to-history operators, respectively, to $0.094$. The same model uses fewer parameters than unconstrained history prediction. These results indicate that enforcing the discrete shift structure of history-state evolution is an effective inductive bias for non-Markovian PDE surrogate modeling. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.09500 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.09500v2 Announce Type: replace-cross Abstract: We propose a time-domain boundary integral method to model linear wave propagation with refractive, focusing, and Doppler effects arising from medium heterogeneities and moving obstacles. In contrast to existing techniques, our method avoids volumetric discretization and yields a formulation posed only on the boundary of the obstacle. We combine two classical ingredients: a geometric--optics parametrix to capture leading-order behavior at propagating wavefronts, and a ray-based characterization of the distorted causal geometry. The former provides a framework for defining layer potentials and deriving the associated boundary integral equations, while the latter enables a pure boundary-only formulation. Taken together, these ingredients extend existing numerical techniques for the homogeneous, fixed-boundary case to the heterogeneous, moving-boundary setting, with appropriate modifications to capture the discrete causal structure arising from the intersection of distorted light cones with the worldsheet of the moving boundary. Numerical experiments demonstrate the ability of the method to resolve Doppler effects from moving obstacles, including a rotating turbine configuration, with stable performance up to Mach 0.9. In heterogeneous media, the method captures strong refractive effects from spherical inclusions: wave propagation wrapping around a gas bubble in water, and defocusing from a hot fireball rising through a stratified atmosphere. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2604.25635 Wed, 13 May 2026 00:00:00 -0400 arXiv:2604.25635v2 Announce Type: replace-cross Abstract: We explore the nonlinear dynamics of classical field theories containing ghost degrees of freedom, focusing on two coupled scalar fields with opposite kinetic terms in (1+1) and (2+1) dimensional Minkowski spacetime. Using a spacetime finite element formulation, we perform a systematic numerical study across a broad class of initial data. We find that ghost-normal systems can exhibit long-lived, dynamically bounded evolution over extended time intervals, with stability strongly controlled by spectral content and amplitude. Ultraviolet-dominated and small-amplitude configurations remain stable significantly longer than infrared-dominated or large-amplitude data, indicating that instability is mediated by nonlinear spectral energy transfer rather than instantaneous runaway. Nonlinear self-interactions play a dual role: while they can accelerate energy exchange between sectors, certain potentials, including a lifted $\phi^6$ interaction supporting oscillon-like structures, generate transient metastable regimes that partially suppress ghost-induced growth. Our results demonstrate that the dynamical consequences of ghost modes in classical field theory depend sensitively on dispersion, nonlinearity, and phase structure, revealing a richer metastability landscape than commonly assumed. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2510.13677 Wed, 13 May 2026 00:00:00 -0400 arXiv:2510.13677v2 Announce Type: replace-cross Abstract: Physics-Informed Neural Networks (PINNs) embed the partial differential equations (PDEs) governing the system under study directly into the training of Neural Networks, ensuring solutions that respect physical laws. While effective for single-system problems, standard PINNs scale poorly to datasets containing many realizations of the same underlying physics with varying parameters. To address this limitation, we present a complementary approach by including auxiliary physically-redundant information in loss (APRIL), i.e. augment the standard supervised output-target loss with auxiliary terms which exploit exact physical redundancy relations among outputs. We mathematically demonstrate that these terms preserve the true physical minimum while reshaping the loss landscape, improving convergence toward physically consistent solutions. As a proof-of-concept, we benchmark APRIL on a fully-connected neural network for gravitational wave (GW) parameter estimation (PE). We use simulated, noise-free compact binary coalescence (CBC) signals, focusing on inspiral-frequency waveforms to recover the chirp mass $\mathcal{M}$, the total mass $M_\mathrm{tot}$, and symmetric mass ratio $\eta$ of the binary. In this controlled setting, we show that APRIL achieves up to an order-of-magnitude improvement in test accuracy, especially for parameters that are otherwise difficult to learn. This method provides physically consistent learning for large multi-system datasets and is well suited for future GW analyses involving realistic noise and broader parameter ranges. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2506.14097 Wed, 13 May 2026 00:00:00 -0400 arXiv:2506.14097v2 Announce Type: replace-cross Abstract: This paper reformulates complementarity-based time-stepping for frictionless nonsmooth contact between smooth rigid bodies as a recursively generated linear complementarity problem (ReLCP), involving a sequence of LCPs of increasing dimension. Starting from a classical single-constraint shared-normal signed-distance (SNSD) LCP, the method adds unilateral constraints only when the discrete-time update predicted by the current contact set would violate nonpenetration of the underlying smooth surfaces. The resulting procedure acts directly on smooth geometry, enforces nonpenetration to a prescribed tolerance, and avoids the oversampling inherent to proxy-surface contact models such as tessellations or multi-sphere decompositions, for which improved geometric fidelity can drive rapid growth in constraint count and cost. For strictly convex bodies, we prove that an initially overlap free configuration with sufficiently small timestep sizes, imply finite termination of the adaptive augmentation, and yield a unique discrete-time velocity update. In the small timestep limit and for any fixed overlap-free discrete state with a fixed geometric overlap tolerance, we prove that the recursion terminates after the initial solve, reducing the method to the classical single-constraint SNSD LCP and retaining the usual consistency of complementarity time-stepping with the underlying differential variational inequality. Numerical tests on colliding ellipsoids, compacting ellipsoid suspensions, growing bacterial colonies, and taut chainmail networks demonstrate stable large-timestep behavior, bounded interpenetration without discretization-induced surface roughness, and substantial reductions in both active constraint counts and runtime relative to representative discrete-surface complementarity formulations. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2604.14083 Wed, 13 May 2026 00:00:00 -0400 arXiv:2604.14083v2 Announce Type: replace Abstract: For many materials, macroscopic mechanical behavior is determined by an intricate microstructure. Understanding the relation between these two scales helps scientists and engineers design better materials. The relation which maps microstructure to bulk mechanical properties can be understood via the well-established theory of homogenization. However inverting the homogenization process, to recover microstructural information from measured macroscopic properties, is fraught with difficulties because of the averaging processes that underlie homogenization. Therefore, scientists and engineers usually need recourse to more invasive, often highly localized, investigations to learn about a microstructure. In this work, we develop a noninvasive methodology by which one can leverage large collections of measured bulk mechanical properties to learn information about the statistics of microstructure at a global level. We call this, distributional inverse homogenization. We study this problem in one and two dimensions, considering both periodic and stochastic homogenization. We demonstrate the methodology in the context of 2D Voronoi constructions and underpin the observed empirical success with theory in 1D. We also show how the natural spatial variability of microstructure can be exploited to gather data that enables distributional inversion. And we concurrently learn a surrogate model, approximating the homogenization map, that accelerates the resulting computations in this setting. The work formulates a new class of inverse problems, bridging ideas from probability and homogenization to facilitate the learning of microstructural material variability from macroscopic measurements. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2512.00776 Wed, 13 May 2026 00:00:00 -0400 arXiv:2512.00776v2 Announce Type: replace Abstract: Controlling the magnetic properties of nanosystems by an electric field offers a number of advantages for spintronics applications. Using the noncollinear Alexander-Anderson model, we have shown that the interaction of localized magnetic moments formed by itinerant electrons strongly depends on the position of the d-level relative to the Fermi level, which determines the number of localized electrons. Depending on this parameter, the ground state of the magnetic dimer can be ferromagnetic, antiferromagnetic, or noncollinear without the effects of spin-orbit interaction. The magnetic state can be controlled by shifting the d-level with an electric field, even without current flow. For a sufficiently large value of the hopping parameter between localized states there can be several self-consistent solutions with different values of magnetic moments. This opens new possibilities for manipulation of the magnetic structure of nanosystems. The results obtained lead to a new interpretation of the mechanisms of magnetization reversal, recording, and deleting of magnetic structures in tunneling spectroscopy experiments. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2511.05233 Wed, 13 May 2026 00:00:00 -0400 arXiv:2511.05233v3 Announce Type: replace Abstract: Lithium-Sulfur batteries (LSBs) are believed to have a high potential for aerospace applications due to their high gravimetric energy density. However, despite decades of research and advances, they still suffer from poor rate capability and low power output, eventually preventing their practical implementation. One particular aspect we want to shed light on is the influence of the porous cathode structure on the rate performance during discharge. Therefore, we present a scale-resolved simulation methodology involving high-performance computing (HPC), which aims to provide structural insights into the electrochemical cell behavior that are experimentally hardly accessible even for modern operando methods. Our \emph{numerical operando approach} employs scaling analysis for efficient model parametrization as well as rigorous parameter transfer between models of different dimensionality and is based on a coarse-grained continuum model. The latter is spatially discretized with a Discontinuous Galerkin (DG) method and advanced in time by an adaptive controller. The models and methods as well as HPC aspects of our toolbox will be critically discussed, finally showcasing the capabilities of our workflow to improve LSBs. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2505.23356 Wed, 13 May 2026 00:00:00 -0400 arXiv:2505.23356v2 Announce Type: replace Abstract: Diseases caused by bacteria have been a threat to human civilisation for centuries. Despite the availability of numerous antibacterial drugs today, bacterial diseases continue to pose life-threatening challenges. The credit for this goes to Gram-Negative bacteria, which have developed multi-drug resistant properties towards \b{eta}-lactams, chloramphenicols, fluoroquinolones, tetracyclines, carbapenems, and macrolide antibiotics. V arious mechanisms of bacterial defence contribute to drug resistance, with Multi-Drug Efflux Pumps and Enzymatic degradation being the major ones. An effective approach to cope with this resistance is to target and inhibit the activity of efflux pumps and esterases. Even though various Efflux Pump Inhibitors and Esterase resistant macrolide drugs have been proposed in the literature, none of them has achieved FDA approval due to several side effects. This research has provided valuable insights into the mechanism of drug resistance by RND efflux pump and Erythromycin esterase. A handful of potential efflux pump inhibitors have been predicted through machine learning and molecular dynamics. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.12165 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12165v1 Announce Type: cross Abstract: In light of the recent advancements in machine learning, we propose a novel approach to neutron source distribution estimation through the utilisation of probabilistic generative models. The estimation is based on a Monte Carlo particle list, which is only required during the training stage of the machine learning model. Once the source distribution has been learned, the model is independent of the original particle list, allowing for further sampling in an efficient, rapid, and memory-costless manner. The performance of various generative models is evaluated, including a variational autoencoder, a normalizing flow, a generative adversarial network, and a denoising diffusion model. These approaches are then compared to existing source distribution estimations, and the advantages and disadvantages of each approach are discussed. The results demonstrate that source distributions can be modeled through the use of probabilistic generative models, which paves the way for further advancements in this field. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.12014 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12014v1 Announce Type: cross Abstract: Preserving scalar boundedness is important for numerical schemes used in turbulent compressible multi-component flow simulations to prevent unphysical results and unstable simulations. However, ensuring scalar boundedness for high-order, low-dissipation numerical schemes poses challenges in highly under-resolved conditions due to inherent dispersion errors that generate spurious oscillations. Numerical dissipation is needed to mitigate these oscillations, but excessive dissipation negatively affects resolution. In this work, we propose formulations for high-order finite-difference schemes to preserve scalar boundedness without predefined bounds, while maintaining high accuracy and low numerical dissipation. The proposed formulations augment a non-dissipative numerical flux of a high-order central-difference scheme with an explicit dissipative numerical flux that adaptively switches between high-order and low-order formulations. Building on a deliberate choice of the non-dissipative flux, we construct two schemes using Jameson's artificial viscosity method and a monotonicity-preserving limiter as the dissipative flux. We examine the schemes in one-dimensional scalar advection problems and a three-dimensional temporal turbulent mixing-layer case involving sharp scalar gradients and under-resolved conditions, evaluating their accuracy, boundedness of species mass fractions, and numerical diffusivity. The scheme with the monotonicity-preserving limiter demonstrates superior performance. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.12007 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12007v1 Announce Type: cross Abstract: Forward propagation of input uncertainties in physics-based wildfire models is computationally prohibitive, limiting the use of high-fidelity simulators in risk assessment workflows. This work introduces a geometry-aligned bi-fidelity surrogate framework that addresses the convection-dominated nature of wildfire spread by mapping low- and high-fidelity solution snapshots onto a common reference domain prior to basis selection and reconstruction. Unlike conventional bi-fidelity schemes, which combine spatially shifted snapshots and thus suffer from oscillations and excess basis requirements near sharp fronts, the proposed mapping aligns the dominant front geometry through per-variable shift/stretch transforms in 1D and an activity indicator-based affine alignment in 2D, so that reduced bases compare physically corresponding structures rather than displaced ones. Building on the ADfiRe physics-based simulator, we demonstrate the method on 1D and 2D test cases in which low- and high-fidelity models differ in mesh resolution and physical completeness. Across both settings, the geometry-aligned surrogate reproduces full-field temperature and fuel composition with substantially lower error than its unmapped counterpart, eliminates Gibbs-type oscillations near steep gradients, and recovers high-fidelity probability density functions for key quantities of interest (e.g., maximum temperature, evaporated moisture, and burned area). After offline training, online predictions are roughly three orders of magnitude cheaper than direct high-fidelity evaluation, making the framework a practical building block for many-query uncertainty quantification once the offline cost is amortized over enough queries. We discuss the conditions under which the geometric alignment is most effective, its limitations for non-convex or topologically complex fronts, and the path toward validation against real data. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.11843 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11843v1 Announce Type: cross Abstract: Large eddy simulation has been widely used to simulate turbulence at balanced computational cost and accuracy. Many Subgrid-Scale (SGS) models have been proposed over the years, where data-driven and machine learning-aided approaches set the recent trend. To address the problem of extrapolation in these models, we propose a new data-driven SGS model based on an information-theoretic picture of turbulence. To this end, we estimate the model parameters by maximizing mutual information, which correspond to the scale-by-scale local equilibrium hypothesis in developed turbulence or "information preservation." An a priori test confirmed that the estimated parameters are in good agreement with the previously reported empirical values. Furthermore, a posteriori tests on periodic box turbulence and channel turbulence exhibited accuracy comparable to the existing models. These results suggest the utility of the information-theoretic picture of turbulence for constructing more generic SGS models without the need for empirically prescribed model parameters, while enhancing physical interpretability beyond black-box approaches. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.11604 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11604v1 Announce Type: cross Abstract: Cementitious materials are widely used for hazardous-waste encapsulation, yet the molecular mechanisms governing heavy-metal ion retention across different gel chemistries remain insufficiently resolved. Here, classical molecular dynamics simulations were employed to investigate the adsorption-controlled mobility of representative heavy-metal ions (Pb2+, Ba2+, and Cs+) within nanopores of C-S-H, C-(N)-A-S-H, and N-A-S-H gels. By combining pore-averaged diffusivity, spatially resolved diffusivity and residence-time analysis, ion-density profiles, two-dimensional adsorption maps, radial distribution functions, coordination analysis, and interfacial binding-strength descriptors, this study establishes a comparative atomistic framework linking gel surface chemistry to ion mobility suppression under nanoconfinement. Ion mobility is substantially reduced in all gel nanopores relative to bulk solutions, but the extent and mechanism of suppression vary strongly with gel chemistry. C-(N)-A-S-H with higher Al/Si ratios exhibits the strongest retention, driven by ion accumulation around Al-linked oxygen species via an ion-exchange-like mechanism with charge-balancing Na+. C-S-H immobilizes ions primarily through surface hydroxyl oxygens and Ca-mediated linkages, whereas N-A-S-H exhibits more distributed binding environments. Pb2+ and Ba2+ exhibit broadly similar immobilization mechanisms, whereas Cs+ shows more distinct, gel-dependent interactions with silicate and aluminosilicate oxygen sites. A relative total binding strength (rTBS) descriptor is introduced, showing a strong positive correlation with the extent of ion immobilization across gel types, ion species, and pore sizes examined. These results clarify gel-specific and ion-specific mechanisms controlling heavy-metal retention in idealized cementitious nanopores. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.11308 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11308v1 Announce Type: cross Abstract: Conductivity models for warm dense matter inform simulations of planetary structure and fusion experiments. State-of-the-art conductivity calculations based on density functional theory approximate many-body physics and neglect electron-electron scattering lifetimes. We introduce a many-body framework for electrical conductivity using the GW approximation of the electronic self-energy. For beryllium, improved transition energies yield a surprisingly large reduction in low-temperature DC conductivity, while electron-electron scattering primarily reduces high-temperature DC conductivity. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.11162 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11162v1 Announce Type: cross Abstract: We present the Quantum Hamiltonian Analysis Toolkit (QHAT), a newly developed application that provides a user-friendly interface for studying Hamiltonians and performing Hamiltonian simulation on fault-tolerant quantum computers. QHAT enables the generation and analysis of Hamiltonians through a powerful and feature-rich application, driven by simple inputs designed to reflect user needs rather than algorithmic details, so that productive research on your application of interest can be done without needing a deep understanding of quantum computing algorithms. QHAT enables a streamlined workflow to analyze Hamiltonians and Hamiltonian simulation, supporting multiple choices of algorithms and analyses. It supports Hamiltonians from multiple sources but can also generate Hamiltonians based on a simple description of the system, saving intermediate data files for re-use when generating related Hamiltonians. Deriving the parameters for quantum computing algorithms can be a challenge, so QHAT is built around user-facing concepts such as maximum allowable error, rather than being built around algorithmic details such as steps counts or order parameters. An emphasis on user-friendly interfaces and efficient analysis means that the barrier to entry is low while rapidly providing results useful for a broad scope of studies. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.11918 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11918v1 Announce Type: cross Abstract: The distortion of light's degrees of freedom when passing through complex random media is of great interest across a diversity of fields, e.g., scattering in biological studies. Emulating such media in a controlled laboratory setting conventionally relies on real-world physical samples (e.g., white paint), inhomogeneous mixtures with embedded scatterers, or biological tissue-mimicking phantoms. Such methods, while effective in certain contexts, are not without complexity and limitations: the exact medium properties are challenging to control and often require laborious preparation, external characterisation techniques, are not easily reproducible between studies and cannot be matched precisely by numerical simulations. Here, we propose a simple all-digital implementation of random scattering which can be readily implemented on any setup capable of producing digital holograms. Our approach employs binary random phase masks encoded onto a spatial light modulator which perturbs the input beam's phase and amplitude. We highlight two methods to precisely tune distortion strengths which show excellent agreement between simulated and measured results. We demonstrate distortion strengths comparable to real-world scattering samples and illustrate two example applications to emulate scattering of scalar and vectorial structured light. Finally we showcase the versatility of this toolkit for emulating various amplitude and phase profiles and suggest several easy to implement alternative modalities accessible with this method. This digital phantom circumvents many of the practical challenges of physical samples, making it ideally suited for applications at the intersection of structured light, biological imaging and optical communications. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2601.13420 Wed, 13 May 2026 00:00:00 -0400 arXiv:2601.13420v3 Announce Type: replace-cross Abstract: We demonstrate a neutral atom networking node that combines high photon collection efficiency with high atom photon entanglement fidelity in a compact, fiber integrated platform. A parabolic mirror is used both to form the trap and to collect fluorescence from a single rubidium atom, intrinsically mode matching $\sigma$ polarized emitted photons to the fiber and rendering the system largely insensitive to small imperfections or drifts. The core optics consist of millimeter scale components that are pre aligned, rigidly bonded on a monolithic in-vacuum assembly, and interfaced entirely via optical fibers. With this design, we measure an overall photon collection and detection efficiency of $5\%$, from which we infer an overall collection efficiency of $9\%$ after the single--mode fiber coupling. We generate atom photon entangled states with a raw Bell state fidelity of 0.93 and an inferred fidelity of 0.98 after correcting for atom readout errors. The same node design has been realized in two independent setups with comparable performance and is compatible with adding high NA objective lenses to create and control atomic arrays at each node. Our results establish a robust, cavity free neutral atom interface that operates near the limit set by the collection optics numerical aperture and provides a practical building block for scalable quantum network nodes and repeaters. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2604.12467 Wed, 13 May 2026 00:00:00 -0400 arXiv:2604.12467v2 Announce Type: replace Abstract: We present the first measurement of 9p 2P1/2,3/2 and 10p 2P1/2,3/2 excited levels absolute wavenumbers and radiative lifetime in francium. We used the Collinear Resonance Ionization Spectroscopy (CRIS) technique, applied on a beam of 221Fr atoms. Prior to this work, no experimental data existed for francium p-states with n > 8. The results provide a precision experimental test of relativistic coupled-cluster theory for the heaviest alkali, showing good agreement for lifetimes and relative excitation energies, despite a residual global offset in absolute energies. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2509.04882 Wed, 13 May 2026 00:00:00 -0400 arXiv:2509.04882v3 Announce Type: replace Abstract: This article presents an experiment that can be conducted today and that could provide a deeper understanding of the interaction between the wave and particle aspects of an atom. The wave-particle duality is often presented as mutually exclusive: one considers either the wave aspect or the particle aspect. Our proposed experiment involves both aspects simultaneously and raises new questions. It is a slightly modified version of Young's double-slit interference experiment (a grid of narrow slits is added between the two wide slits) and is carried out using Rydberg atoms. Young-type interference experiments typically involve only the de Broglie wave $\psi$, which depends solely on the mass and velocity of the atoms. However, with Rydberg atoms having a large principal quantum number, the ``size'' of the atom-particle also becomes significant. The two large slits are wide enough to allow the Rydberg atoms to pass through, whereas the grid of narrow slits prevents them from passing through. We numerically simulate the possible outcomes based on different hypotheses regarding wave-particle interaction. Conducting the experiment in practice would allow us to distinguish between these hypotheses and deepen our understanding of wave-particle interaction. The conceptual framework of Louis de Broglie's double solution theory is well-suited to this experiment because it distinguishes between two types of waves: an external or statistical wave (de Broglie's wave) and an internal or physical wave (corresponding to the physical particle). We will examine the relevance of this approach. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.12444 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12444v1 Announce Type: new Abstract: Axions and axion-like particles are among the most promising candidates for dark matter and for manifestations of new physics beyond the Standard Model. In the present work, the contribution of axion exchange to the energy of lithium-like ions is investigated within the framework of relativistic bound-state quantum electrodynamics. A formalism for the interelectronic interaction mediated by axion exchange is developed in the Furry picture with finite nuclear size taken into account. Energy shifts are calculated for a wide range of nuclear charge numbers \(Z\) and axion masses. The magnitude of the axion-induced contribution is shown to increase with increasing \(Z\) for all states considered. Based on the analysis of lithium-like bismuth, constraints on the axion-electron interaction parameters are obtained in the high-mass region. The results indicate that precision spectroscopy of highly charged ions is a promising tool for searches for new physics associated with the exchange of pseudoscalar bosons. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.12315 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12315v1 Announce Type: new Abstract: The natural and Dyson orbitals are studied for small helium drops comprising 5 to 20 helium atoms interacting via a soft two-body gaussian potential. The wave functions of these drops have been obtained in the hyperspherical cluster model (HCM) which provides a correct description of the single-particle behaviour at large separations from the system. The natural orbitals are obtained from diagonalization of the nonlocal one-body density matrix, while Dyson orbitals are constructed by direct overlap of the wave functions of two drops differing by one boson. This overlap converges with increasing basis of the HCM. The shapes and occupancies of the natural orbitals as well as their link to Dyson overlaps and evolution with increasing number of atoms are discussed. Both natural and Dyson orbitals can be used to represent the density of the system. However, the natural orbitals representation is demonstrated to be superior. With increasing boson numbers the difference between Dyson and natural orbitals becomes less prominent and it is expected to disappear in infinitely large systems of identical bosons. Physics/physics.atm-clus_(Atomic_and_Molecular_Clusters) https://arxiv.org/abs/2512.16732 Wed, 13 May 2026 00:00:00 -0400 arXiv:2512.16732v2 Announce Type: replace Abstract: Metamaterials benefit from unique architected patterns to achieve lightweight with exceptional mechanical properties inaccessible to conventional materials. Typical mechanical metamaterials are inspired by crystal-like lattice structures, whose closely packed frameworks often exhibit a rigid mechanical nature. Here, we present polymer-inspired metamaterials (PIMs) by programming deformation and strengthening mechanisms that mimic the mechanical roles of key constituent elements in polymer networks. By combining metamaterial programmability with polymer-inspired structures, we design crosslinking, proto-crystalline order, and entanglement in PIMs to enable macroscale strengthening mechanisms inspired by crosslink, molecular-density, and pre-stretch strengthening in polymers, expanding the metamaterial structure-property design space. This macroscale polymer-inspired programmability also suggests that PIMs could serve as a design platform incorporating the programmability strategies to achieve desired deformation and strengthening responses, holding a potential for applications in soft robotic joints and compliant connectors. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2501.07263 Wed, 13 May 2026 00:00:00 -0400 arXiv:2501.07263v3 Announce Type: replace Abstract: Biosensing based on optically trapped fluorescent nanodiamonds potentially allows to resolve biochemical processes inside living cells at a desired intracellular location. Towards this goal, we investigate near infrared (NIR) laser irradiation at 1064 nm on fluorescent nanodiamonds (FNDs) containing nitrogen-vacancy (NV) centers. The 1064 nm NIR wavelength is a popular choice for optical trapping because of its low absorption in bio-samples. By conducting comprehensive experiments, we aim to understand if and how NIR exposure influences the fluorescence and sensing capabilities of FNDs and to determine the potential implications for the use of FNDs in various sensing applications. Our experiments exposed FNDs to varying intensities of NIR laser light while carefully monitoring their optical and magnetic properties. Key measurements included all-optical fluorescence relaxation, optical spectroscopy, and optically detected magnetic resonance (ODMR) spectra. The findings reveal how increased NIR laser power correlates with alterations in ODMR central frequency but also that charge state dynamics under NIR irradiation of NV centers play a role. We demonstrate that FND biosensing works well with a protocol involving both NIR and green light, while mitigating the effect of NIR. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.12212 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12212v1 Announce Type: cross Abstract: We present an analytical emission model that accurately predicts the properties of effusive sources formed by long collimation tubes. By construction, it captures the full range of molecular flow, from the transparent flux regime, which occurs in highly rarefied gases, to the opaque regime, which arises as the flux increases and interparticle collisions become non-negligible. The model is based on a previously developed secondary-emission-surface approach, improved here to overcome its internal limitations and recover the well-established axial flux intensity. It provides accurate analytical predictions of the angular intensity distribution in the molecular flow regime, offering valuable guidance for the design of efficient primary sources across a broad range of experiments in atomic and molecular physics Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.11886 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11886v1 Announce Type: cross Abstract: Qualification of components operating in future fusion power plants will be heavily reliant on simulations of component behaviour. The lack of representative test environments for many aspects of the expected operating environment will necessitate full or partial virtual qualification of components. The cornerstone of virtual qualification is credible validation of the simulation models on which it relies. In this work, we present a probabilistic model validation framework that forms the basis for implementation of virtual qualification in fusion. We demonstrate our framework on a representative component; a high heat flux heat sink subject to a tightly coupled multi-physics loading. We perform data-rich, optimised experiments, in which we implement high fidelity diagnostics and rigorously quantify aleatoric and epistemic uncertainty on all measurements. Our simulation approach efficiently samples input uncertainty distributions to predict probability boxes describing component response, using a statistical surrogate to replicate behaviour of the finite element model we wish to validate. We then used a novel implementation of the modified area validation metric to quantify the model form error of the finite element model, isolating it from the aleatoric and epistemic experimental uncertainty. We discuss the contribution of our validation approach towards virtual qualification, and the benefits of the risk-based decision-making it facilitates. The experimental, simulation, and validation datasets are published as a benchmark of a probabilistic validation approach for fusion, and for use in development of new model validation methodologies. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2603.03669 Wed, 13 May 2026 00:00:00 -0400 arXiv:2603.03669v3 Announce Type: replace Abstract: All-sky OH airglow imaging provides two-dimensional observations of mesospheric gravity wave structure near ~87 km altitude. Ripple-scale instability signatures, characterized by 5-15 km horizontal wavelengths and short lifetimes, are particularly difficult to identify consistently using manual inspection. In this study, we develop a reproducible, automated detection framework based on a squeeze-and-excitation convolutional neural network (SE-CNN) trained on 41 x 41 pixel image patches, to identify ripple-scale structures in 512 x 512 pixel all-sky airglow images acquired at Yucca Ridge Field Station (40.7o N, 104.9o W). The time-differenced images are normalized using a robust median-absolute-deviation (MAD) scaling procedure to mitigate star contamination and background variability. The model is trained and validated on manually annotated ripple and non-ripple patches, then evaluated using independent test subsets. The automated detection is performed using a sliding-window approach with spatial and temporal clustering criteria for event definition. At the patch level, the classifier achieves 92\% F1-score with high precision and recall. At the event level, automated detections recover approximately 90\% of manually identified ripple events while identifying additional low-amplitude occurrences. Validated against previous manual identification study, the automated detection catalog enables objective quantification of ripple occurrence frequency, seasonal modulation, and lifetime distributions. By emphasizing methodological transparency, calibration considerations, and validation metrics, this framework establishes a scalable measurement technique for systematic detection of mesospheric instability signatures in long-term airglow image archives. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.12311 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12311v1 Announce Type: new Abstract: Fundamental inorganic chemistry shows that increasing concentrations of atmospheric CO2 will have no harmful effect on organisms that live in the natural waters of the Earths, and may well benefit them. Alkalinity and dissolved CO2 give high buffering capacity to most natural waters and minimize the change of pH from external influences. For example, doubling the atmospheric concentration of CO2 from 430 ppm to 860 ppm would reduce the pH of representative sea water at a temperature of 25 C from pH = 8.18 to pH = 7.93. This change is comparable to diurnal pH changes in biologically productive surface waters, due to photosynthetic fixation of dissolved inorganic carbon during the day and respiration at night. The change is also less than the variations of pH with latitude, longitude and depth in the oceans. This paper includes a quantitative review of the carbonate chemistry of seawater and freshwater, the buffering capacity, the Revelle factor, the transport of calcium carbonate in ground water, the formation of flowstone, and the classic use of limewater to detect gaseous CO2. The paper concludes with a brief review of those parts of chemical thermodynamics that are involved in ocean acidification. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.11531 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11531v1 Announce Type: new Abstract: Physics-based climate projections using general circulation models are essential for assessing future risks, but their coarse resolution limits regional decision-making. Statistical downscaling can efficiently add detail, yet many methods treat variables independently, degrading inter-variable relationships that govern compound hazards such as heat stress, drought, and wildfire. Here we show that a diffusion-based multivariate generative framework, combined with bias correction, recovers degraded inter-variable correlations even under a 50$\times$ increase in linear resolution. When applied to five meteorological variables over Japan, the framework reduces inter-variable correlation errors by more than fourfold relative to existing baselines while improving both univariate and spatial accuracy, leading to more accurate detection of severe drought. These results demonstrate that multivariate generative downscaling improves the reliability of compound risk assessment under large resolution gaps. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.10960 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.10960v1 Announce Type: new Abstract: Folk meteorological proverbs encode centuries of empirical observation by agricultural communities. Two Hebrew proverbs link lunar calendar anchor days to monthly winter rainfall: (i) "If Rosh Chodesh is rainy, the whole month is rainy" and (ii) "If it rains on Shabbat Mevarechim, the whole month is rainy." Shabbat Mevarechim is the last Saturday before each new Hebrew month, preceding Rosh Chodesh by one to seven days. The first proverb is widely known; the second circulates in Hasidic oral tradition with no identified written source. Both have never been formally tested. We analyse 75 years (1950-2024) of daily precipitation data from seven Israeli cities across three climatic regions, comprising 191,758 station-days and 2,422 Hebrew-month observations during the winter rainy season (Marcheshvan-Adar). A rainy Rosh Chodesh increases the probability of a rainy month from 22.2% to 38.6% (lift +16.4 percentage points; chi-square = 57.8, p = 2.9e-14; Bayes factor 1.81). A rainy Shabbat Mevarechim produces a similar effect (lift +16.5 percentage points, p = 8.0e-13), despite preceding Rosh Chodesh by up to seven days. The effect decays with lag and mirrors daily rainfall autocorrelation (r = 0.35-0.44 at lag 1; ~0 at lag 7), consistent with Mediterranean cyclone persistence. A bootstrap permutation test (p < 1e-4) and a 15-year rolling analysis show declining predictive power (-0.20 percentage points per year, p < 0.001), consistent with shortening precipitation events under warming climate conditions. Both proverbs encode real but probabilistic meteorological signals whose reliability is decreasing over time. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.10958 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.10958v1 Announce Type: new Abstract: Atmospheric correction is a critical preprocessing step in optical remote sensing, but repeated high-fidelity radiative transfer simulations remain computationally expensive for dense look-up-table generation, sensitivity analysis, retrieval support, and operational preprocessing. This study presents a physics-aware multi-fidelity surrogate framework for emulating atmospheric correction coefficients using paired 6S and libRadtran simulations. Atmospheric and geometric states are sampled using Latin Hypercube Sampling, and both radiative transfer models are evaluated under matched conditions for Sentinel-2 bands using spectral-response-function-aware coefficient generation. The high-fidelity targets are path reflectance, total transmittance, and spherical albedo. A physics-guided Kolmogorov-Arnold Network, termed pKANrtm, receives the atmospheric state and low-fidelity 6S coefficients, predicts the residual relative to libRadtran, and reconstructs the high-fidelity coefficients. The pKANrtm model uses an Efficient-KAN architecture and is trained with a physics-consistency penalty applied in the original coefficient space. The proposed model is evaluated against state-of-the-art regression-based RTM surrogates. Across both standard and out-of-distribution evaluation settings, pKANrtm achieves the strongest overall predictive performance among the compared models. Runtime benchmarking demonstrates substantial acceleration relative to libRadtran, with GPU inference providing approximately four orders of magnitude single-sample speedup and batched inference reaching tens of thousands of samples per second. These results indicate that physics-aware multi-fidelity pKANrtm emulation provides an accurate, physically structured, and computationally efficient strategy for atmospheric correction coefficient generation. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.10956 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.10956v1 Announce Type: new Abstract: Machine-learned surrogate modeling of advection may accelerate geoscientific models, but existing approaches have either achieved limited speedup or have sacrificed spatial resolution compared to the model they are trained to emulate. We developed a machine-learned solver that speeds up advection simulations without sacrificing spatial resolution through the use of temporal coarse-graining, where the model is trained to take larger integration steps than dictated by the Courant-Friedrich-Lewy (CFL) condition. Our solver framework includes a convolutional neural network that takes concentrations and CFL numbers as inputs and outputs mass flux. Our solvers emulate 10-day ground-level horizontal advection simulations with r$^2$ values against the baseline ranging from 0.60--0.98 with temporal coarsening factors of 4 to 32 times the baseline integration time step. Speed increases and accuracy decreases with increased coarsening, with $r^2 = 0.24$ in accuracy lost for every factor of 10 gained in speed, reaching a maximum 92$\times$ speedup while maintaining $r^2 = 0.60$. We deliberately trained our solvers only on January ground-level wind data to examine their ability to generalize across seasons and vertical heights. The 4$\times$-coarsened learned solver successfully reproduces simulations over 72 vertical levels. The 8$\times$--16$\times$ solvers (but not 32$\times$) emulate most vertical levels. The learned solvers also generalize well across seasons, except for instabilities in June and October. With additional fine-tuning, these learned solvers could be appropriate for operational use where trading accuracy for speed could be advantageous, such as in screening tools, in ensemble simulations, or with data assimilation. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.10951 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.10951v1 Announce Type: new Abstract: The subpolar oceans are characterized by intense storm forcing and complex littoral topography. Submesoscale frontal instabilities are significant sources of turbulent kinetic energy (TKE) in these regions. However, criteria for identifying and parameterizing these instabilities in regional models have predominantly relied on a geostrophic framework that neglects generalized ageostrophic shear. We derive criteria for overturning instability that account for stabilizing and destabilizing effects of ageostrophic shear on mechanically forced boundaries, deviating from the geostrophically derived potential vorticity (PV) criterion, $qf < 0$. Ageostrophic forcing modifies stability from that implied by the vertical PV structure underlying bulk surface boundary layer diagnostics, which may limit the applicability of such bulk criteria in strongly forced regimes and motivate the need for layer-resolved measures. We demonstrate their application using a feature model of a wind-forced jet, as well as a 1-km Regional Ocean Modeling System (ROMS) hindcast of the high North Atlantic, and assess the importance of forced ageostrophic overturning instability (AOI) in intense frontal zones. In the feature model, ageostrophic shear increases overturning instability by up to 20%, compared to a strictly geostrophic framework. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.10950 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.10950v1 Announce Type: new Abstract: Pakistan experienced an unusually severe flood season between June and December 2025, with cascading impacts on population, infrastructure, and agriculture. Existing operational flood products (e.g., UNOSAT) provide valuable episode-level snapshots but rarely deliver spatially and temporally continuous inundation maps at near-real-time latency within the country. We present a multi-sensor, ensemble-based remote-sensing framework for continuous flood nowcasting in Pakistan that integrates Sentinel-1 SAR, Harmonized Landsat-Sentinel (HLS L30 and S30), MODIS, and VIIRS observations on a harmonized grid in Google Earth Engine. The framework employs a tiered nowcasting ensemble that prioritizes higher-resolution sensors (Sentinel-1 and HLS) and falls back to MODIS and VIIRS when necessary, preserving daily continuity of flood extent at each sensor's native resolution. Applied to the 2025 monsoon period, the system generates near-real-time, spatially consistent inundation maps across Pakistan. As a nowcasting case study, we track the super-flood of 26 August-7 September 2025 day by day, demonstrating the framework's ability to capture the evolving flood footprint in near real time and extend beyond the temporal limits of episodic mapping products. Validation against GloFAS discharge anomalies and precipitation datasets (CHIRPS v3.0, MSWEP) shows strong agreement with observed hydrometeorological conditions. By integrating nowcast outputs with exposure layers (WorldPop, ESA WorldCover, Giga-HOTOSM), the framework enables rapid estimation of affected populations, cropland, and critical infrastructure, supporting timely disaster response and resilience planning in South Asia. Physics/physics.ao-ph_(Atmospheric_and_Oceanic_Physics) https://arxiv.org/abs/2605.12267 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12267v1 Announce Type: new Abstract: We present the first part of an efficient framework for nonlinear beam dynamics, termed Approximate Invariant Analysis (AIA). The framework is based on the construction of approximate invariants~[Y.~Li, D.~Xu, and Y.~Hao, Phys.\ Rev.\ Accel.\ Beams \textbf{28}, 074001 (2025)] and on the extraction of the betatron frequency with the geometric foundations of Poincar\'e rotation number~[S.~Nagaitsev and T.~Zolkin, Phys.\ Rev.\ Accel.\ Beams \textbf{23}, 054001 (2020)]. The method is demonstrated using the National Synchrotron Light Source~II (NSLS-II) storage ring as an illustrative example. Physics/physics.acc-ph_(Accelerator_Physics) https://arxiv.org/abs/2605.11896 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11896v1 Announce Type: new Abstract: This work develops advanced numerical methods for free-surface simulations of polymer mixing processes, integrating a Volume of Fluid (VOF) interface-capturing approach with a non-conforming Immersed Boundary (IB) method to model two-phase flows of highly viscous polymer melts and air within partially filled rotating mixing devices, implemented within the Finite Volume OpenFOAM library. To overcome severe numerical instabilities arising from the strong viscosity contrast between polymer melts and air, a block-coupled scheme providing fully implicit viscous diffusion treatment is integrated into the VOF-IB framework, relaxing time-step stability constraints and substantially reducing computational cost with respect to standard segregated solvers. The resulting BC-VOF-IB solver is applied to industrially relevant geometries of single- and twin-screw extruders, yielding physically consistent predictions of velocity and pressure fields under partial filling conditions. While further developments, most notably the inclusion of thermal effects, remain necessary, the proposed framework represents a meaningful step toward bridging academic CFD research and the practical demands of industrial polymer processing. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.12405 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.12405v1 Announce Type: cross Abstract: A Wiener-Hopf-type integral equation for the stationary PDF of a reflected random walk is derived rigorously based on modern probability theory, and an application to battery energy storage systems (BESS), specifically the sizing of the inverter, is discussed in depth. The methodological steps include the construction of a Markov kernel, the derivation of a Fredholm integral equation of the second kind for the PDF of the BESS power, and an analytical solution of the equation based on a Neumann series. The analytical results were compared against numerical solutions obtained with the Nystrom method, as well as against the results of an algorithmic simulation using simulated input time series. The use of truncated versions of the analytic solution allows for the construction of simplified design rules for the power systems practitioner. General insights into inverter sizing criteria of storage systems for ramp-rate control of variable renewable energy (VRE) sources such as wind and solar are provided. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.11637 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11637v1 Announce Type: cross Abstract: X-ray computed tomography (CT) reveals the materials' internal structures non-destructively from a tilt series of projected images. Filtered back projection (FBP) is a widely-adopted reconstruction algorithm in CT owing to its small computational cost. Under low-dose or sparse-view conditions, however, FBP often amplifies noise, severely degrading the reconstructed images. In this study, we evaluated the performance of a Bayesian CT reconstruction algorithm based on the Markov random field model under such adverse conditions. Through simulations, we demonstrated that the proposed algorithm shows higher reconstruction performance than FBP under both low-dose and sparse-view conditions. The hyperparameters are estimated by minimizing the Bayesian free energy, enabling adaptive reconstruction that reflects the noise characteristics of the observed projection data. These results suggest that the proposed algorithm can broaden the applicability of CT to dose-sensitive applications and time-constrained measurements, where only limited observed projection data are available. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.11982 Wed, 13 May 2026 00:00:00 -0400 arXiv:2605.11982v1 Announce Type: cross Abstract: Alnico magnets have gained renewed interest in the search for rare-earth free permanent magnets due to their high thermal stability and magnetisation. However, the limited coercivity of these shape-anisotropy-based alloys constrains their performance. Starting from a reference Alnico sample, we realised a finite elements micromagnetic study of exchange-decoupled rods by varying their dimensions and interrod spacing across those observed experimentally. We computed the hysteresis properties by progressing from micromagnetic simulations of a small number of rods within the magnetostatic field of their neighbours to large systems treated statistically based on the distribution of orientations of the grains. We compared the coercivity of an isolated rod with that of the exchange-decoupled system to highlight the effect of magnetostatic interactions. We computed analytically the stray field acting on a single rod as a consequence of its surrounding rods in order to confirm the scaling of the coercivity with the packing fraction p. We explored how intrinsic material properties influence magnetic behaviour by examining materials with different magnetocrystalline anisotropy constants and saturation polarisation values. Results from several hundred simulations were used to train a multi-layer perceptron regressor and predict the magnetic properties as function of the dimensions of the rods, interrod spacing and orientation of the grains. With this approach, we highlight the underlying trends by which nanoscale structuring, intrinsic material properties and grain alignment can be tailored to improve the magnetic properties of Alnico alloys. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.08849 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08849v1 Announce Type: new Abstract: Modal decomposition of turbulent flows using classical proper orthogonal decomposition (POD) often suffers from mode mixing, in which a distinct coherent structure may be distributed over several POD modes. We propose a decomposition method based on the Hilbert transform and band-pass filtering to address this issue (filtered Hilbert POD -- FHPOD). We apply this approach to the turbulent flow through a 180 bent pipe at $Re_D=10,000$ (based on bulk velocity ($U_b$) and pipe diameter ($D$)) and curvature $\gamma=0.2$, simulated using direct numerical simulation. The FHPOD results in four distinct mode families, including a swirl-switching mode at Strouhal number of 0.13 localised in the curved section. Our novel modal decomposition shows that the modes observed in the bend and downstream correspond to distinct physical mechanisms rather than to a single universal swirl-switching instability throughout the pipe, as previous work implied. To further examine the origin of the swirl-switching mode, we perform a local stability analysis of the cross-sectional mean flow along the bend. We find unstable eigenmodes at the same streamwise wavenumber and within the same range of Strouhal numbers as the swirl-switching mode found in the modal decomposition. The result supports the interpretation that the swirl-switching phenomenon is an intrinsic instability of the curved-pipe flow that can be excited and potentially enhanced by incoming turbulent structures, but is ultimately not caused by them. Finally, we also establish a link of the downstream modes to the local shear layers of the modified base flow, highlighting the different nature of these modes. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.08872 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08872v1 Announce Type: new Abstract: Turbulence modeling within the Lattice Boltzmann Method (LBM) framework has long relied on traditional algebraic sub-grid scale (SGS) models, which often suffer from over-dissipation and lack of spatial selectivity near solid boundaries. In this work, we utilize Physical Symbolic Optimization (Phi-SO) to discover explicit analytical closures from high-fidelity DNS datasets of Taylor-Green Vortex (TGV) and Lid-Driven Cavity (LDC) flows. Central to our methodology is the integration of virtual dimensional analysis and non-linear tensor invariants, a strategy that enforces physical scaling laws directly within the symbolic search process. The resulting model exhibits a highly non-linear dependency on both strain-rate and rotation-rate invariants. Numerical validations confirm that this symbolic closure outperforms the standard Smagorinsky approach in capturing kinetic energy dissipation rate peaks and resolving delicate secondary corner vortices. Furthermore, the model exhibits robust zero-shot generalization to wall-bounded turbulent channel flow (Re_tau = 180) without the aid of any supplemental wall-damping corrections. This work highlights the potential of symbolic regression to uncover robust, interpretable physical laws for the next generation of intelligent computational fluid dynamics solvers. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.08906 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08906v1 Announce Type: new Abstract: Particle migration and trapping in ultrasonically actuated microscale flows arise from the competition between acoustic radiation forces and streaming-induced drag. While these mechanisms are well understood in Newtonian fluids, the role of fluid viscoelasticity in governing particle dynamics remains largely unexplored. Here, we investigate particle transport and trapping in a viscoelastic fluid within an ultrasonically excited microchannel under the combined action of acoustic streaming and radiation forces. Using a perturbation framework, we solve the continuity, momentum and constitutive equations for an Oldroyd-B fluid to obtain the oscillatory acoustic field and the resulting steady streaming flows in the bulk and near-wall boundary layers. Acoustic radiation forces, incorporated through a semi-analytical model, drives particle migration, while streaming-induced drag can oppose, alter or suppress trapping. We show that particle trajectories and equilibrium trapping locations are governed primarily by the Deborah number ($De$) and viscous diffusion number ($Dv$). At high $Dv$, increasing $De$ shifts the trapping location from the bulk region to the channel wall, pressure nodal line, channel centre or ultrasound symmetry line. We further determine the critical particle size governing the transition between radiation-dominated and streaming-dominated regimes as a function of $De$ and $Dv$. The critical particle size can become significantly smaller than that in a Newtonian fluid, enabling effective manipulation of submicron particles and overcoming a key limitation of conventional acoustofluidics. These results demonstrate how viscoelasticity fundamentally modifies acoustophoretic transport and establish new mechanisms for tunable particle migration and trapping in complex fluids. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.09559 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09559v1 Announce Type: new Abstract: Laminar-turbulent transition in shock wave-boundary-layer interactions (SWBLI) remains a major challenge for hypersonic vehicle design, with implications for drag, heat transfer, and structural loads. Linear optimal perturbation analyses can identify candidate instabilities, but the full route to breakdown in SWBLI requires nonlinear optimisation. Here, we characterise the optimal transition pathway in a globally stable yet convectively unstable Mach 2.15 oblique SWBLI using a nonlinear input-output optimisation framework based on the space-time spectral Navier-Stokes formulation of Poulain et al. (Comput. Fluids, 2024). The nonlinear frequency-domain approach captures mean-flow distortion, resolves triadic energy transfers, and extracts intrinsic nonlinear stresses that activate additional instability mechanisms. We identify a four-stage pathway: (1) optimal forcing of oblique first Mack mode waves at moderate frequencies; (2) nonlinear self-interaction of counter-propagating Mack waves, generating streamwise Gortler-like vortices in the reattachment region where streamline curvature peaks; (3) lift-up of streamwise velocity streaks by these vortices; and (4) subharmonic sinuous secondary instability leading to streak breakdown. Optimisation across forcing amplitudes from infinitesimal to transitional levels yields quasi-invariant optimal forcing structures, showing that exciting the oblique first Mack mode alone can trigger the turbulent cascade. Parametric studies over frequency-wavenumber space and forcing configurations confirm this preferential pathway. By resolving nonlinear energy transfers with a finite number of harmonics, this work provides a tractable framework for transition prediction and control strategy development in high-speed separated flows, bridging linear stability theory and fully turbulent simulation. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.10301 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10301v1 Announce Type: new Abstract: This experimental, numerical, and theoretical study investigates the capillary thinning and breakup of Newtonian filaments formed following the coalescence of a millimetric-nozzle-generated pendant drop with a lower droplet cap contained in a millimetric cylinder in ambient air, i.e., dripping-onto-droplet capillary breakup (DoD). Our mixed approach combines filament breakup experiments recorded with a high-speed camera and three-dimensional numerical simulations based on a variational multiscale framework for multiphase fluid flows. The results are analysed by considering the dynamics of fluid filament thinning, energy transfers, and scaling laws. Three flow regimes are highlighted: capillary-inertial, capillary-viscous, and mixed capillary-inertial-viscous. All regimes are affected by gravity. The findings are summarised in a two-dimensional diagram that correlates the filament breakup time with different flow regimes using the important dimensionless parameters of the problem, e.g., the Ohnesorge number (which relates the viscous stress to inertial and capillary stresses) and the Bond number (which balances the gravitational stress with the capillary one). This diagram can be used to quantify both the liquid viscosity and the liquid-gas surface tension (for Newtonian fluids). Lastly, we demonstrate that DoD can also be used as a rheometric test, giving access to the extensional relaxation time of polymer solutions (for viscoelastic fluids). Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.08832 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08832v1 Announce Type: cross Abstract: Neural surrogate models for computational fluid dynamics (CFD) are typically trained as forward operators that map explicit problem specifications, such as geometry and boundary conditions, to solution fields. This ties the model to the conditioning variables seen during training and limits reuse under boundary-condition shifts or local geometry changes. We propose to reformulate steady CFD inference as an inpainting problem: instead of training on explicit boundary conditions, we learn a self-supervised prior over velocity fields and impose boundary constraints only during inference by fixing known regions such as inlet, outlet or unchanged regions from previous simulations. To scale this idea to large 3D meshes, we introduce a local neighbourhood tokeniser that represents high-resolution velocity fields as compact spatial latent tokens and train latent flow-matching and masked-autoencoder models on these tokens. On intracranial aneurysm hemodynamics, our method reconstructs full velocity fields from sparse boundary context, outperforms supervised neural surrogates under boundary-condition and dataset shift and enables local geometry editing by reusing unchanged simulation context. These results suggest that viewing CFD inference as context-conditioned inpainting can turn neural surrogates from task-specific predictors into reusable flow priors. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2510.06837 Tue, 12 May 2026 00:00:00 -0400 arXiv:2510.06837v2 Announce Type: replace-cross Abstract: We present a systematic pathway for solving differential equations within the quantum linear systems framework by combining block encoding with Quantum Singular Value Transformation (QSVT). The approach is demonstrated on a complex tridiagonal linear system and extended to problems in computational fluid dynamics: the heat equation with mixed boundary conditions and Carleman-linearized nonlinear Burgers' equation. Our scaling analysis of the heat equation identifies regimes where classical computation remains feasible and estimates circuit depths required to achieve potential quantum advantage. We further evaluate post-selection success probabilities for the presented examples and provide hardware resource estimates for block encoding and QSVT circuits in terms of two-qubit gate depth, evaluated on IBM superconducting processors with heavy-hex and square lattice topologies. These results highlight both the practical limitations of current hardware and key directions for depth reduction and scalable quantum linear solvers. Physics/physics.flu-dyn_(Fluid_Dynamics) https://arxiv.org/abs/2605.09056 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09056v1 Announce Type: new Abstract: We show how local periodic driving can be used to control dissipation in a structured environment in a highly selective manner. As a minimal setting, we consider two discrete levels coupled to a one-dimensional tight-binding continuum with a finite bandwidth, where only one level is driven while the other remains undriven. Without driving, both bare energies are placed outside the static continuum band so that neither level decays. We demonstrate that the drive can nevertheless activate a selective remote dissipation channel: the undriven level acquires a finite decay rate, whereas the driven level can remain long-lived. The mechanism is clarified within Floquet theory. Periodic driving generates photon-assisted channels shifted by integer multiples of the drive frequency, effectively creating a ladder of drive-shifted continuum sidebands (Floquet channels). A decay channel for the undriven level opens once its bare energy overlaps an open sideband accessed via drive-enabled pathways; in the tight-binding example, the decay is strongly enhanced near the sideband edge due to the increased density of states. The dominant remote pathway is controlled by Bessel-weighted couplings and can be switched and strongly suppressed by tuning the drive amplitude. We verify these predictions by direct numerical integration of the time-dependent Schr\"odinger equation. We also formulate a complex-eigenvalue problem for the Floquet Hamiltonian by eliminating the continuum via a Brillouin--Wigner--Feshbach projection, and show that the pole-implied decay rate quantitatively reproduces the time-domain decay envelope. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.09019 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09019v1 Announce Type: new Abstract: We extend quantum state tomography with minimal cumulative disturbance, first investigated in [arXiv:2406.18370], to arbitrary finite-dimensional pure states. A learner sequentially receives fresh copies of an unknown pure state, chooses a rank-one projector for each copy using the previous outcomes, and performs the corresponding two-outcome projective measurement. The goal is to learn the state while keeping the chosen projectors close to the unknown state in order to minimize disturbance. The qubit solution relies on the special geometry of the Bloch sphere and does not extend directly to qudits, where pure states form a curved manifold. We show that this obstruction can be overcome by working locally on the pure-state manifold. The algorithm proceeds in epochs. In each epoch, it fixes a current estimate, measures pairs of nearby rank-one projectors obtained by moving in opposite tangent directions, and takes differences of the corresponding outcomes. This gives an exact linear observation of the tangent component of the error. The resulting local linear models are combined with a robust variance-adaptive estimator and a hot-start regularization that transfers precision across epochs. For every unknown pure state in dimension \(d\), after \(T\) measured copies, our protocol achieves cumulative regret \(\mathcal{O}(d^3\log^2 T)\), and at each intermediate time \(t\leq T\) its current estimate has online infidelity \(\mathcal{O}(d^3\log(T)/t)\). Hence, pure-state tomography with essentially no cumulative disturbance is not a peculiarity of qubits but a geometric phenomenon that persists for qudits. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.09017 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09017v1 Announce Type: new Abstract: The quantum query complexity of subgraph-containment problems, which ask whether a given subgraph $H$ is present in an input graph $G$, has been the subject of considerable study. However, even for relatively simple subgraphs, such as paths and cycles, a complete understanding of their query complexities remains elusive. In this work, we consider several variants of path- and cycle-containment problems in the adjacency matrix model, where we search for paths or cycles of constant length $k$. We compare the settings where the graphs are directed or undirected, where the goal is to detect or find the existence of a path/cycle, and where the path/cycle we are looking for has length exactly $k$, or at most $k$. We also consider several promise versions of these problems, where we suppose that the input graph has a certain structure. We characterize the relative difficulty of these variants of the path/cycle-containment problems, by relating them to one another using randomized reductions, and grouping them into equivalence classes. When we restrict our attention to path-containment problems, we get a dichotomy result. Some of the path-containment problems can be solved using a linear number of queries, and all the others are equivalent to one another (and additionally to several cycle-containment problems) under randomized reductions, up to constant overhead. For the latter equivalence class, we prove a novel quantum-walk-based algorithm that achieves query complexity $\widetilde{O}(n^{3/2-\alpha_k})$, where $\alpha_k \in \Theta(c^{-k})$ and $c = \sqrt{3+\sqrt{17}}/2 \approx 1.33$, beating the previous best upper bound $O(n^{3/2})$ on its query complexity. We also provide a conditional lower bound based on the graph-collision problem, which implies that this equivalence class does not admit linear-query quantum algorithms unless graph collision admits an $O(\sqrt{n})$ query algorithm. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08923 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08923v1 Announce Type: new Abstract: Consider a bipartite quantum system S=AB such that each part interacts only with its local environment. Under such circumstances, one expects that the entanglement between parts A and B does not exceed its initial value during the time evolution. In fact, this is the case if the reduced dynamics of the system is given by $\mathcal{E}_{A}\otimes \mathcal{E}_{B}$, where $\mathcal{E}_{A}$ and $\mathcal{E}_{B}$ are quantum channels, i.e., completely positive trace-preserving maps. But, the reduced dynamics of the system may be given by a map as $\Psi_{A}\otimes \Psi_{B}$, where $\Psi_{A}$ and $\Psi_{B}$ are local non-positive maps. Then, the entanglement between A and B can exceed its initial value, as was shown in the case studied by Jordan et al. [Phys. Rev. A 76, 022102 (2007)]. In this paper, we first explore the general circumstances under which one can find such cases as they found. Next, we introduce another general procedure which leads to local non-positive maps that cause entanglement exceeding. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08918 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08918v1 Announce Type: new Abstract: Quantum transport in disordered systems poses intriguing fundamental questions about the interplay of disorder, interactions, and decoherence, with important implications for nanoscale energy transfer and quantum information transfer. Here, we investigate the emergence of multiple transport timescales in the dissipative dynamics of a spin impurity coupled to a small, spatially disordered network of spins. Using a two-dimensional tight-binding model with dipolar interactions and local dephasing, we demonstrate that geometric heterogeneity leads to hierarchical coupling strengths and pronounced separation of dynamical timescales. By analyzing different metrics for dynamics, we identify distinct relaxation timescales associated with cluster-level equilibration and global equilibration. A minimal three-site model reveals the physical origin of the longest timescale: strong internal hybridization generates an effective detuning that suppresses transfer to other weakly coupled sites, yielding a parametrically enhanced relaxation time in the weak-dephasing regime. We corroborate this picture with nonequilibrium steady-state transport calculations and simulations of disordered spin configurations, demonstrating orders-of-magnitude slowing of relaxation when hierarchical couplings are present. Our results highlight the central role of geometry and connectivity in spin networks and open quantum systems in general, and provide experimentally relevant predictions for relaxation times in small spin baths. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08771 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08771v1 Announce Type: new Abstract: Entanglement purification with two entangled resource pairs is widely employed in the literature on quantum repeater networks to counteract fidelity degradation introduced by noisy quantum memories and entanglement swapping across multiple hops. Standard purification protocols assume both resource pairs carry identical fidelity. In practice, entanglement generation is stochastic, the two resource pairs are heralded at different times, and so the first pair decoheres in memory while the second is being generated. Thus a fidelity asymmetry is a structural feature of any network operating under realistic memory conditions, leading to the question: when is it beneficial to perform purification? We derive a closed-form fidelity asymmetry tolerance delta(F) that governs whether a purification attempt is beneficial. We determine a universal upper bound delta_max of approximately 0.076 beyond which purification is always counterproductive. Our simulations show that with exponential memory decoherence, purification yields benefits in only approximately 14% of purification attempts on two resource pairs in a two-hop repeater chain. We define three network objectives: fidelity only, time only, and a combination of time and fidelity, to deliver end-to-end entanglement. We show that when the application fidelity requirement is achievable through swapping alone, no-purification is the superior policy, with its advantage increasing with the number of hops. When the fidelity requirement cannot be met with swapping alone and purification is necessary, to be effective, it must be conditioned on delta(F) between resource pairs. We introduce DeltaPurify, a policy that conditions purification decisions on local fidelity information, and show it reduces time-to-serve relative to both naive purification and no-purification across several fidelity thresholds and hops of a repeater chain. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08745 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08745v1 Announce Type: new Abstract: Replacing the task of retrieval with exclusion changes how preparation contextuality manifests operationally under parity-oblivious constraints, with exclusion showing a quantum advantage where retrieval does not. We introduce the parity-oblivious random exclusion code (POREC) and show that for prime symbol size $m$, classical and preparation-noncontextual encodings provide a tight noncontextual bound. For the first nontrivial case (two digits, three symbols), our derived exact qubit optimum violates this bound, in contrast to parity-oblivious retrieval, which displays no quantum advantage. This characteristic difference is absent without parity constraints. For general prime $m$, qubit strategies achieve a quantum-to-noncontextual gap that grows linearly relative to the random exclusion code (REC) gap, exceeding both parity-oblivious retrieval and standard REC. The exact qubit bound yields a sharp semi-device-independent certification of dimension $d \geq 3$. Our analysis of noise robustness demonstrates POREC to be amenable for experimental implementation on existing prepare-and-measure platforms, establishing parity-oblivious exclusion as a distinct operational probe of preparation contextuality, as well as a practical information processing protocol with wide applications. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08683 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08683v1 Announce Type: new Abstract: Evaluating the entanglement spectrum is essential for characterizing exotic quantum phases such as quantum criticality and topological order. However, for large quantum many-body systems, this task is hindered by the exponential measurement complexity of standard tomographic techniques. To address this challenge, we introduce a hybrid quantum-classical variational framework for partial singular value decomposition of bipartite states, built on the canonical form of matrix product states. We employ a deflation-based optimization approach to sequentially extract dominant and subdominant Schmidt components of target states. Because hardware noise and finite circuit depth can compromise the mutual orthogonality of these extracted vectors, we propose an improved deflation algorithm incorporating explicit classical orthogonality correction. This classical post-processing acts as an error-filtering mechanism, enabling shallow and suboptimal quantum circuits. As a result, numerical accuracy is decoupled from quantum circuit optimization, mitigating optimization difficulties caused by barren plateaus and hardware noise. Furthermore, shallow ansatzes enable a concurrent execution strategy. Overlap matrices are evaluated by classical tensor network contractions, while cross terms between the target state and the extracted vectors are computed using an auxiliary reference state. This concurrent hybrid design improves computational throughput and bypasses the overhead of controlled target-state preparation. Numerical benchmarks on the ground states of one- and two-dimensional Heisenberg models demonstrate improved accuracy and numerical stability. By mitigating hurdles of circuit depth, optimization hardness, and measurement complexity, our framework provides a robust pathway for large-scale entanglement spectrum estimation on advanced near-term quantum devices. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08548 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08548v1 Announce Type: new Abstract: We suggest a scheme for obtaining negative refraction with low absorption in a left-handed atomic system.Under the the appropriate conditions,the atomic system displays negative refraction with negative permittivity and permeability(Left-handedness)in a common frequency range,simultaneously.And the imaginary parts of permittivity and permeability show transparently propagate in the same frequency range.Finally,the negative refraction show low absorption due to the EIT effect,and the figure of merit demonstrated this in this resonant atomic system. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08535 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08535v1 Announce Type: new Abstract: A Rydberg superheterodyne sensing architecture is demonstrated in which a self-sustained oscillator (SSO) serves as a dynamically perturbed local oscillator (LO) for microwave detection. The SSO is realized by a phase-controlled radio-frequency (RF) feedback loop coupled to a transverse electromagnetic (TEM) cavity containing a Rydberg vapor cell. The system operates near 5.49 GHz using a cesium ladder scheme with an 852 nm probe and 510 nm coupling laser addressing the 6S to 6P to 49D transition, with microwave coupling to the 50P state. Injection of a microwave signal pulls the SSO frequency via nonlinear dynamics, converting input power into a measurable frequency shift read out optically as a Rydberg probe intermediate-frequency (IF) signal. The response follows Adler-type injection-pulling behavior, with continuous IF tuning with input power. A peak responsivity of 35 kHz/dB is observed, with enhanced sensitivity near synchronization. These results demonstrate power-to-frequency transduction using a dynamically perturbed LO combined with Rydberg atomic readout. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08523 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08523v1 Announce Type: new Abstract: We present several finite-temperature recursive Fermi-operator expansion schemes based on the second-order spectral projection (SP2) method. Our approach builds on a previous observation that the electronic structure problem, as formulated through a recursive SP2 expansion, can be mapped onto the architecture of a deep neural network. Using this perspective, we generalize SP2 to finite electronic temperatures and construct machine learning models to determine optimized expansion coefficients. These coefficients are trained for a specified chemical potential and electronic temperature and are not available in closed analytical form. However, by employing an appropriate affine rescaling strategy to the Hamiltonian matrix, we eliminate the need to retrain the model during a simulation if the temperature and chemical potential change. Our approach avoids explicit diagonalization and relies solely on highly optimized matrix-matrix multiplication kernels. Compared to state-of-the-art diagonalization, we achieve an order-of-magnitude speedup in the single-particle finite-temperature density matrix calculation for small and moderately sized matrices on modern GPUs and dense matrix multiply units. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08425 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08425v1 Announce Type: new Abstract: We implement a time-of-flight imaging technique utilizing a differential-readout SNSPD to spatially resolve detection events in a fiber-coupled detector platform. We measure the spatial detection profiles for ultra-high numerical aperture fiber, standard single-mode fiber, and thermally-expanded core fiber (mode-field diameters 4.1{\mu}m, 10.4{\mu}m, 30{\mu}m respectively) in an active area surrounded by an all-dielectric optical stack designed for near-unity detection efficiency. We see no beam divergence in all but the smallest fiber optic modes. This contradicts previously-held beliefs that beam divergence during the detection process necessitates activate areas much larger than coupled optical modes, opening new paths toward smaller and better-optimized detectors. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08402 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08402v1 Announce Type: new Abstract: Classical computation relies heavily on information manipulation. Each component of a hardware needs to communicate with others, and this is done by encoding information into strings of bits and application of logical operations. When dealing with quantum technologies, there arises a new set of paradigms and devices, based on manipulations of qubits, the quantum analogues of conventional bits. This work investigates the generation and distribution of quantum entanglement, a uniquely non-classical correlation, across spin chains, which serve as promising platforms for quantum information processing. We systematically compare two distinct entanglement generation protocols: Protocol 1 (P1), based on alternating weak and strong couplings that create a band structure enabling an effective trimer-model approximation, and Protocol 2 (P2), which employs symmetric boundary couplings and virtual excitations to establish a direct effective interaction between the chain ends. Our results demonstrate that a protocol based on virtual excitations and optimized boundary couplings consistently outperforms its counterpart in speed, achieved entanglement, and robustness against fabrication imperfections and noise. Furthermore, by employing effective model reductions and open quantum systems techniques we provide a comprehensive framework for understanding the resilience of distributed entanglement in solid-state quantum devices. The characteristics of the virtual-coupling protocol highlight its potential for experimental implementation in scalable quantum technologies. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08375 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08375v1 Announce Type: new Abstract: The concept of an isolated system, and Frauchiger and Renner's extended `Wigner's friend' scenario are discussed. It is argued that: (i) it is questionable whether the approximation of the isolated system is valid when measurement-like processes are involved; (ii) one may infer, from Frauchiger and Renner's thought-experiment, and similar thought-experiments, that any interpretation of quantum theory involving *subjective collapse* fails; (iii) this does not distinguish single-world from many-world (relative-state) interpretations of quantum theory; (iv) reasoning from observations has to take into account the possible quantum-erasure of those observations if it is to be valid reasoning; (v) a single-world interpretation is valid if certain kinds of outcome are not quantum-erased in the future. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08351 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08351v1 Announce Type: new Abstract: In quantum causality and quantum information, there is a vast landscape of abstract quantum protocols permitting cyclic or non-acyclic causal structures between operations, including frameworks for indefinite causal order and higher-order quantum processes such as process matrices. A longstanding open question is what is the largest class of abstract processes that admit physical realisations without post-selection. In this work, we provide a rigorous answer using a top-down approach grounded in relativistic causality principles. Building on the framework of causal boxes, which characterise the most general quantum information-processing protocols compatible with fixed background spacetimes, we formalise additional constraints (Acting Once + Local Order) capturing the closed-laboratory assumptions of the process matrix framework at a fine-grained spacetime level. We prove that any protocol in a classical acyclic spacetime satisfying these conditions is behaviourally equivalent to a quantum circuit with quantum control of causal order (QC-QC), providing a top-down derivation of QC-QCs from physical principles. Our results show that QC-QCs constitute precisely the class of higher-order quantum processes, including those with indefinite order, that can be physically realised within classical spacetime, ruling out more general non-causal processes under the closed-labs assumption. This clarifies the relationship between abstract higher-order process matrix frameworks and experimentally accessible quantum protocols, as well as the interplay between coarse-grained cyclic and fine-grained acyclic operational causal structures. We also develop characterisation techniques for process box protocols that lead to new causality-based open questions concerning spacetime quantum protocols and relativistic quantum experiments. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08341 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08341v1 Announce Type: new Abstract: We introduce a new method for error-corrected quantum metrology where only partial quantum error correction (QEC) is needed to suppress local noise and maintain the probe states' super-standard-quantum-limit (super-SQL) sensing performance. This stands in contrast to the existing QEC-assisted sensing schemes in Phys. Rev. Lett. 112, 080801 (2014) and Phys. Rev. Lett. 112, 150802 (2014), where a probe state is encoded into the logical subspace of a quantum code and error correction involves measurements on all checks of the code. Here, we encode the probe states into superpositions of energetically different states of the underlying quantum code. For our probe states, error correction using a subset of checks is enough to suppress noise both before and after phase imprinting. We analyze the tradeoff in noise suppression. For noise parallel to our phase imprinter of operator weight $l$, we achieve a suppression of $p^\delta$, where $p$ is the noise strength and $\delta = \lfloor (l+1)/2 \rfloor$. We propose an adaptive imprinter-weight-increasing strategy to maintain super-SQL performance as we scale up the system. In all our examples, checks and phase imprinters are chosen to be local operators, avoiding non-local connectivity. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08332 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08332v1 Announce Type: new Abstract: Feedback-based adaptive quantum optimization (FALQON) is a promising approach for solving combinatorial problems on noisy intermediate-scale quantum (NISQ) devices, requiring only single circuit evaluations per layer. However, standard FALQON relies on fixed hyperparameters that severely limit convergence speed, requiring hundreds to thousands of layers for acceptable solutions. This paper proposes Optimal FALQON, an optimization-based formulation that treats the per-layer time step ($\delta_k$) and scaling factor ($M_k$) as decision variables optimized via classical methods. We present a comprehensive empirical study on all 94 non-isomorphic 3-regular graphs with 12 vertices, comparing Optimal FALQON with standard FALQON and multiple QAOA variants. Results demonstrate statistically significant improvements in success probability, evaluation efficiency, and depth-normalized cost across the evaluated benchmarks. Furthermore, initializing QAOA with parameters from Optimal FALQON yields superior warm-start performance compared to fixed initialization. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08259 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08259v1 Announce Type: new Abstract: We obtain quantitative estimates on the decay of the multiplayer optimal value under parallel repetition. In comparison to a previous work of the author in 2025 (arXiv: 2508.09380) which sought to generalize dependency-breaking and anchoring variables from two-player Quantum games, being able to establish quantitative estimates on the decay of the optimal value of a multiplayer game under parallel repetition is of interest to establish under different assumptions. Specifically, independently of the dependency-breaking and anchoring variables that have previously been employed to remove correlations from entangled information shared between Alice and Bob (hence removing dependencies), monotonic concave functions can be used in place of such variables to obtain rates of decay on the optimal value. The game-theoretic setting with two players was first analyzed with monotonic concave functions by Lanzenberger and Maurer. For $q_i , x_i > 0$ $\forall 1 \leq i \leq N$ where $N > 0 $ is the total number of players we adddress an open question raised in their work regarding potential generalizations of two-player monotonic concave functions, through amplification functions of the form $\Psi_{\textit{Mult}} \equiv \Psi = N - \underset{1 \leq i \leq N}{\prod} \mathrm{exp} \big[ - q_i x_i \big]$, which in the multiplayer game-theoretic setting have more intricate combinatorial structures. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08251 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08251v1 Announce Type: new Abstract: Zero-noise extrapolation (ZNE) reduces noise-induced bias but can increase sampling variance through Richardson coefficients and shot splitting. We define a finite-shot help-harm boundary: the lower local mean-squared-error crossing where fixed Richardson ZNE changes from harmful to helpful. A local expansion shows that this boundary is governed by the first squared-bias improvement and first excess-variance penalty, producing either a shrinking power law, a budget threshold, or no shrinking lower boundary. Qiskit Aer simulations and variance-exponent fits support the predicted separation between deterministic stabilizer measurements and variational energy measurements, while readout-regime diagnostics and IBM Quantum checks delineate measurement-protocol and hardware-traceability limits. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2605.08248 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08248v1 Announce Type: new Abstract: In this work, a unified Lie-algebraic formulation of catability is constructed for relativistic quantum systems with arbitrary spin within this framework. In this case, the analysis starts with constructing catability as a quantitative measure for superposed coherent states, where coherence structure and quantum interference properties are studied using algebraic representations in this framework. Also, a generalized Foldy-Wouthuysen transformation is formulated within a Lie algebraic framework, delivering a systematic procedure for block-diagonalization of relativistic Hamiltonians and separation of positive- and negative-energy components in this framework. Within this formalism, a phase-sensitive catability operator is introduced to study phase correlations and coherence effects in the relativistic quantum dynamics framework. The approach is applied to Dirac spin-$1/2$ particles, where relativistic fermionic catability is analyzed in relation to spinorial structures and symmetry generators framework. The formalism is extended through a unified geometric and Lie-algebraic treatment, establishing a consistent description of catability in a relativistic quantum mechanics framework. In this context, the generalized framework is constructed for arbitrary spin-$s$ fields, enabling investigation of higher-spin relativistic quantum states within the same algebraic structure framework. In this context, the obtained results show a generalized theoretical platform for investigating relativistic quantum coherence, superposition effects, and algebraic symmetries in the framework of fermionic and bosonic systems. Physics/quant-ph_(Quantum_Physics) https://arxiv.org/abs/2603.07715 Tue, 12 May 2026 00:00:00 -0400 arXiv:2603.07715v2 Announce Type: replace-cross Abstract: The chiral plasma instability (CPI) has been invoked as a possible mechanism for generating primordial magnetic fields in the universe and ultrastrong fields in neutron stars. We investigate chiral dynamos where the chirality imbalance is pumped by a source on a timescale $t_0$ and show that the CPI rate $\gamma$ is limited to $\gamma_0/(1+{\cal Q}^2)$, where ${\cal Q}= (\gamma_0 t_0)^{1/3}$ and $\gamma_0$ corresponds to models with instantaneously created chirality imbalance $(t_0=0)$. We then find that chiral flipping with rate $\Gamma_{\mathrm f}$ hinders the chiral dynamo if $\Gamma_{\mathrm f} >\gamma_0/(1+{\cal Q}^2)$ and completely suppresses it if $\Gamma_{\mathrm f} >\gamma_0/(1+{\cal Q}^{3/2})$. Realistic $t_0$ typically give ${\cal Q}\gg 1$, which makes the dynamo greatly vulnerable to suppression by chiral flipping. The suppression is strong in protoneutron stars and may be (barely) avoided near the electroweak transition in the early universe. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.05614 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.05614v2 Announce Type: replace Abstract: Proton radiography of laser direct-drive spherical implosions has shown anomalous structures that correspond to strong electric or magnetic fields extending throughout the corona. These fields have the ability to affect laser-target interactions and act as an energy sink. To better understand the these fields, simplified experiments were conducted in planar geometry on the OMEGA EP laser at the Laboratory for Laser Energetics. Varying target material, target size, pulse shape, and intensity, and measured the field structure using dual-axis proton radiography and a 4w probe. Proton radiographs were analyzed and quantitatively demonstrate that the growth of these features is dominated by laser energy and target Z. The data strongly supports that a secondary instability as a consequence of the expansion driven Weibel instability in these interactions is the primary driver for these fields. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2604.10033 Tue, 12 May 2026 00:00:00 -0400 arXiv:2604.10033v2 Announce Type: replace Abstract: We report an unanticipated electron dynamics in a classical setting of a uniform magnetic field, a parallel electric field, and a right-handed circularly polarized wave (R-wave). The setting admits a natural trajectory that a particle accelerated by the electric field reaches a Doppler-shifted cyclotron resonance and becomes trapped in the resonance space. Remarkably, once it becomes resonantly trapped, the electron undergoes reversal of parallel acceleration together with perpendicular energization, despite the parallel electric field remaining constant. This counterintuitive behavior has important implications for particle scattering in various laboratory and space plasmas. Applied to fusion devices, particle-in-cell simulations show that an externally injected R-wave can act as a firewall suppressing further runaway-electron acceleration. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2604.04002 Tue, 12 May 2026 00:00:00 -0400 arXiv:2604.04002v2 Announce Type: replace Abstract: A spherical torus (ST) p B11 plasma model that satisfies multi-magnetofluid force balance is developed, which includes small fractions of suprathermal ions with temperatures around 0.5 MeV and suprathermal electrons in the MeV range. Alongside the primary thermal plasma with ion temperatures exceeding 100 keV and densities above 10E20 m-3, these components enhance fusion reaction rates by leveraging the p B11 double-peak fusion cross section. Suprathermal ions and strong toroidal rotation driven by neutral beam injection have been observed in devices such as START, MAST, NSTX, Globus-M2, and ST40. Central-solenoid-free plasma initiation, ramp-up, and sustainment were tested on EXL-50 and replicated on EXL-50U with partial central induction, demonstrating efficient current drive and consistent with the multi-magnetofluid equilibrium model. Motivated by ENN's aneutronic commercial fusion roadmap, this paper presents a rotating, thermally un-equilibrated ST p B11 plasma with unique properties: fluid components experience separate balance under centripetal, electrostatic, and Lorentz forces with common electric and magnetic fields, leading to large rotation speed differences between thermal boron ions and suprathermal protons; a large outboard region with magnetic well and omnigeneity is created, affecting neoclassical transport and gradient-driven turbulence; suprathermal charged particles can extend beyond the last closed flux surface and be limited by plasma-facing components, influencing recycling and pedestal conditions; and the superposition of these plasma components modifies sources and sinks of free energy, prompting renewed evaluation of stability, turbulence, transport, heating, current drive, and flux diffusion. Challenges and opportunities for sustained burn are discussed for a compact p B11 ST with 1.4-meter major radius, 13-MA current, and 3-T toroidal field. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2603.25777 Tue, 12 May 2026 00:00:00 -0400 arXiv:2603.25777v2 Announce Type: replace Abstract: There is great potential for the application of AI tools in fusion research, and substantial worldwide benefit if fusion power is realised. However, using AI comes with its own challenges, many of which can be mitigated if responsible and robust methodologies are built into existing approaches. To do that requires close, long-term collaborations between fusion domain experts and AI developers and awareness of the fact that not all problems in fusion research are best tackled with AI tools. In April 2025, experts from academia, industry, UKAEA and STFC discussed how AI can be used to advance R&D in fusion energy at the first edition of The Economist FusionFest event. This Perspective is an expanded and updated summary of the round table discussion, providing more context and examples. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2602.05606 Tue, 12 May 2026 00:00:00 -0400 arXiv:2602.05606v3 Announce Type: replace Abstract: A random number generator for the Kappa velocity distribution in particle simulations is proposed. Approximating the cumulative distribution function with the q-exponential function, an inverse transform procedure is constructed. The proposed method provides practically accurate results, in particular for k<4. It runs fast on graphics processing units (GPUs). The derivation, numerical validation, and relevance to GPU execution models are discussed. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2601.15661 Tue, 12 May 2026 00:00:00 -0400 arXiv:2601.15661v2 Announce Type: replace Abstract: When restricted to magnetic flux tubes, the gyrokinetic theory of microturbulence gives the same radial transport for ions and electrons. But, exact magnetic surfaces do not exist in the presence of what is called electrostatic microturbulence. At a finite plasma pressure, a turbulent electric potential is accompanied by a turbulent magnetic field $\tilde{B}$, which makes the magnetic field lines chaotic. Quasi-neutrality along the chaotic magnetic field lines requires a potential that obeys $en \vec{B}\cdot \vec{\nabla} \Phi = \vec{B}\cdot \vec{\nabla} p_e$, where $p_e$ is the electron pressure. This potential produces radial transport similar to that of diffusion coefficient $D_{ef}= (\Delta/a_T)T_e/eB$. $\Delta$ is the radial distance over which the potential $\Phi$ is correlated by the electron motion along the chaotic magnetic field, and $|dT_e/dr| = T_e/a_T$. The chaos-produced electron transport gives an effective viscosity on the electron flow, which can counterbalance a non-ambipolar part of the ion radial particle diffusion that is $f_{na}$ times gyro-Bohm diffusion. This non-ambipolarity would otherwise require a radial electric field that confines ions and hence impurities. The maximum $f_{na}$ that can be counterbalanced and the required plasma beta to avoid shielding the magnetic perturbations $\tilde{B}$ are calculated. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.10729 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10729v1 Announce Type: cross Abstract: We present and compare distributed parallelization strategies for the particle-in-Fourier (PIF) schemes used in kinetic plasma simulations. The different strategies are i) domain decomposition, where both the particles and Fourier modes are split between the MPI ranks ii) particle decomposition, where only the particles are split between the ranks and each rank carries all the modes, and, iii) space-time decomposition, in which time parallelization based on the parareal algorithm is added on top of the particle decomposition. We describe the different communication patterns involved in each of the strategies, the parameter regimes where they work best, and explain their advantages and disadvantages. We implement the strategies within the open-source, performance portable library IPPL and conduct scaling studies with 3D-3V Landau damping and Penning trap benchmark problems on Alps and JUWELS booster supercomputers. We analyze the dominant component timings in each of the strategies and identify areas for future optimizations. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.10773 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10773v1 Announce Type: new Abstract: Sustained collisionless interpenetrating plasma flows have been generated on the OMEGA laser facility to enable direct investigation of nonlinear evolution of fields generated by electromagnetic kinetic instabilities. FLASH simulations and Thomson scattering measurements are used to determine the plasma conditions achieved. Interpenetrating flows are observed to remain collisionless for at least 11 ns, longer than any prior OMEGA experiment, supporting the growth and nonlinear saturation of the Weibel instability. Resulting magnetic fields are measured using proton radiography. This work establishes a unique platform for late-time filament evolution measurements. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.10697 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10697v1 Announce Type: new Abstract: This paper explores plasma wave modes using the extended magnetohydrodynamics (XMHD) model, incorporating Hall drift and electron inertia effects. We utilize the geometric optics ansatz to study perturbed quantities, with a focus on incompressible systems. Our research concludes with the derivation of the dispersion relation for incompressible XMHD and the associated eigenvector solutions, offering new perspectives on plasma wave behavior under these extended scenarios. The dispersion relation shows distinct ion cyclotron and whistler wave branches, with characteristic saturation at the ion and electron gyrofrequencies, respectively. Comparisons between Hall MHD and XMHD demonstrate that XMHD provides a more accurate representation of plasma dynamics, especially at higher wave numbers, bridging the gap between simplified models and comprehensive two-fluid descriptions and smoothing out singularities present in Hall MHD solutions and capturing more physics of the full two-fluid model. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.10694 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10694v1 Announce Type: new Abstract: A central unresolved question in fusion energy research is whether energetic alpha particles, the primary products of deuterium-tritium fusion reactions, enhance or degrade plasma confinement. In burning plasmas, the operating regime of future devices such as ITER and SPARC, alpha particles become the dominant heating source, yet their impact on confinement has remained uncertain. Here, we present self-consistent simulations of burning plasmas that simultaneously evolve microturbulence, alpha-particle heating, and macroscopic plasma profiles to steady state, and find that alpha particles can substantially improve confinement. Fusion-born alpha particles weakly destabilize toroidal Alfven eigenmodes (TAEs), which nonlinearly enhance zonal flows that shear apart and suppress ion-scale turbulence. The resulting reduction in turbulent heat transport drives stronger core profile peaking, increasing alpha heating by up to 25% and establishing a self-reinforcing feedback loop. This mechanism has no direct analogue in present-day experiments, where external heating dominates, and reveals an intrinsic pathway toward improved confinement in burning plasmas. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.09913 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09913v1 Announce Type: new Abstract: Tokamak design is inherently challenging due to several cross-competing effects which require a careful and calibrated treatment to obtain an optimal operational envelope. Incorporating physics across varied fidelities is crucial in this exercise. Jenga is developed as a unified design and modeling framework for tokamaks, seamlessly coupling systems-level studies to high-fidelity models based on first principles. In this work, static Grad-Shafranov (GS) equilibrium for an entire pulse and the neutronics study of the Mega Ampere Spherical Tokamak Upgrade (MAST-U) tokamak are carried out in Jenga. Coil currents and plasma profiles from the EFIT++ reconstruction of MAST-U shots are used to reproduce the plasma poloidal flux and shape targets at different time slices. The results from Jenga are also in good agreement with FreeGSNKE and Fiesta codes. Neutronics analysis is performed for a hypothetical 50-50 mixture of deuterium-tritium (DT) fuel, using the same data structure as the systems and equilibrium studies. A distributed neutron source is initialized within the last closed flux surface (LCFS) of the plasma, with their strength being functions of the density and temperature of the ions. The distribution of the neutron flux across the energy spectrum is computed for the active coils and the first wall (limiter) independently over multiple scenarios. We demonstrate the capabilities of Jenga with a comprehensive analysis that takes inputs about the plasma geometry, tokamak design and plasma profiles and performs 0D, 2D and 3D numerics for the systems study, equilibrium and neutron transport respectively. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.09205 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09205v1 Announce Type: new Abstract: Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.09191 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09191v1 Announce Type: new Abstract: The energy distribution of energetic protons inside a solid target is a key quantity governing nuclear reaction yields and energy deposition in high-intensity laser-driven fusion, including nonthermal proton--boron (p--B) schemes and proton fast ignition. Yet it has remained inaccessible to conventional particle diagnostics, which detect only ions escaping the target and are perturbed by intense plasma electromagnetic fields. Here we establish a quantitative diagnostic that uses nuclear activation reactions occurring within the target itself as an internal probe of the in-solid proton energy distribution. Applied to laser-driven p--B fusion experiments on the kJ-class laser, the method reconstructs an exponential-equivalent in-solid proton energy distribution from the absolute yields of $^{11}\mathrm{C}$ and $^{7}\mathrm{Be}$ produced via $\mathrm{^{11}B(p,n)^{11}C}$ and $\mathrm{^{10}B(p,\alpha)^{7}Be}$, and yields the absolute number of $\mathrm{^{11}B(p,2\alpha)^{4}He}$ reactions through a side-channel analysis with propagated cross-section uncertainties. This work opens a quantitative window onto the in-solid proton dynamics that drive nuclear reactions in laser-driven fusion experiments. Physics/physics.plasm-ph_(Plasma_Physics) https://arxiv.org/abs/2605.10731 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10731v1 Announce Type: cross Abstract: We develop a non-perturbative description of squeezed light generation in an arbitrary lossy structure consisting of multiple coupled microring resonators. This is applied to two ring photonic molecules where the interference of the fields in the coupled rings leads to a modification in the resonance spectrum near a shared resonance. Considering a dual-pump degenerate squeezing scheme under a five resonance approximation, we investigate two methods to suppress parasitic four-wave mixing contributions and compensate for group velocity dispersion within a primary resonator through hybridization effects with a second auxiliary resonator. In the former case, this comes from an effective splitting of the unwanted resonances supporting parasitic four-wave mixing interactions that add thermal noise to the desired degenerate squeezed state. For sufficiently strong coupling between the resonators, we demonstrate near complete suppression of such parasitic processes, resulting in near unit fidelities with the corresponding output state that would arise were the parasitic interactions neglected. In the latter case, the hybridization effectively shifts a pump resonance, realigning the desired dual-pump four-wave mixing process and leading to a significant enhancement of the signal generation and output squeezing. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.10657 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10657v1 Announce Type: cross Abstract: Time-independent scattering methods are widely used to analyze transport in periodic $\mathcal{PT}$-symmetric systems. However, their predictions become unphysical when the system supports time-growing bound states (TGBSs), which manifest as $S$-matrix poles in the first quadrant of the complex wave-number plane. Here, we analytically delineate the region of physical relevance for a $\mathcal{PT}$-symmetric chain of $N$ unit cells with gain/loss strength $\gamma$. We derive the TGBS onset threshold $\gamma_c = 2\sin[\pi/(4N)]$, which scales as $\pi/(2N)$ for large $N$ and vanishes in the thermodynamic limit. Enlarging the structure thus enriches stationary scattering phenomenology but inevitably triggers TGBSs at weaker gain/loss. Time-dependent wave-packet simulations confirm this analytical boundary quantitatively. Applying this criterion, we show that many previously reported predictions of gain-loss-induced localization, reflectionless transport, and coherent perfect absorbers and lasers in large periodic structures fall outside the physically relevant regime. $S$-matrix pole analysis is therefore an indispensable prerequisite for interpreting time-independent scattering predictions in periodic non-Hermitian systems. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.10492 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10492v1 Announce Type: cross Abstract: Examining and controlling the interaction between semiconductor quantum qubits and their environment can boost semiconductor quantum technologies, which have many applications in table-top quantum computing hardware. Electron beams in electron microscopes have opened up a new avenue for the quantum-coherent probing of semiconductor excitations and strong-coupling effects. Here, I provide a brief overview of recent advancements in electron-beam probes for investigating quantum coherence in semiconductors and two-dimensional materials, complemented by my perspective on using electron beams to manipulate the entanglement and correlations between quantum systems. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.09854 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09854v1 Announce Type: cross Abstract: Sensing weak forces through observing a mechanical motion near or below its quantum zero-point fluctuation has been desired in diverse areas. While mechanical oscillators have played a crucial role in such studies, their application to free-fall-type sensing has been elusive, in particular in the quantum regime. Here, we demonstrate sensing a static force of the order of 10 zeptonewtons with a levitated nanomechanical oscillator below the zero-point fluctuation through the rapid modulation of its confining potential. We prepare a squeezed state with a reduced velocity uncertainty by abruptly decreasing the potential. Subsequently, we detect the exerted static force through time-of-flight measurements, where we release the nanoparticle from the potential and measure the displacement during a free fall. Furthermore, time-of-flight measurements allow us to perform quantum state tomography of the squeezed state, from which we reconstruct its Wigner quasiprobability distribution and evaluate the Fisher information for the position measurement to quantify the achievable force sensitivity of our protocol. Our results demonstrate that modulating the trap stiffness serves as a crucial technique for quantum-limited force sensing and paves the way to utilize a levitated nanoparticle as a promising sensing platform beyond the quantum limit with a capability of quantum state tomography. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.10532 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10532v1 Announce Type: new Abstract: The concept of metasurfaces was recently applied to the extreme ultraviolet (EUV) spectral regime, providing a new opportunity for transmissive focusing elements in a regime where materials are highly lossy. The realization of metalenses in the EUV, however, is challenging due to the optical losses and low refractive index contrast of available materials, as well as the larger-than-wavelength periodicity of metaatom arrays imposed by fabrication limits. In this paper, we propose alternative EUV metalens design strategies, including layout schemes and metaatom mapping rules. We demonstrate that the focusing efficiency can be roughly doubled compared with the simple square-lattice design of an EUV metalens purely by using an alternative semi-analytical design approach without reducing the metasurface's minimum feature size. The proposed strategies are generally applicable to metaoptics design for efficiency improvement when metaatoms are lossy or induce diffraction orders. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.10329 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10329v1 Announce Type: new Abstract: A fundamental symmetry of the non-Hermitian operators describing wave-propagation in time-varying media imbue such systems with non-trivial topology. This topology may be measured directly in a wide range of experimental settings as a quantised real part of the Berry phase, contrasting unconstrained geometric gain or loss. This topological index is provided explicitly for practical examples, including a non-Hermitian analogue of the Su-Schrieffer-Heeger model. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.10283 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10283v1 Announce Type: new Abstract: Optical skyrmions offer a robust vectorial information degree of freedom for free-space communication, but practical deployment requires a compact platform capable of active topological reconfiguration. Here, we propose a silicon microring-resonator optical phased array that integrates spin-selective emission and programmable phase control on a single chip. Optimized inner- and outer-grating microring emitters provide decoupled LCP and RCP radiation bases with polarization fractions of 90.27% and 91.40%, enabling active switching between N\'eel-type and Bloch-type skyrmions, while dynamically tuning the skyrmion number across Nsk =-1.914 to 1.918. Using these programmable topological states, a 4-symbol free-space communication link is constructed and compared with ideal LG-OAM encoding under Kolmogorov turbulence. The skyrmion-encoded link maintains a lower symbol error rate over a broader turbulence range, demonstrating that topological observables are more robust than scalar OAM modes. These results establish actively reconfigurable optical skyrmions as compact, programmable, and turbulence-tolerant information carriers for next-generation free-space optical communication. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.10271 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10271v1 Announce Type: new Abstract: A thermally tunable extraordinary terahertz transmission in a hybrid metal-vanadium dioxide (VO2) metasurface is numerically demonstrated. The metasurface consists of a metal sheet perforated by square loops while the loops are connected with strips of VO2. The frequency and amplitude of the transmission resonance are modulated by controlling the conductivity of the VO2. For y-polarized incident field, the resonance transmission peak redshifts from 0.88 to 0.81 THz upon insulator-to-metallic phase transition of VO2. For x-polarized incident field, the transmission resonance at 0.81 THz is observed in the insulator phase. However, in the metallic phase of VO2, the electromagnetic field is effectively reflected in the 0.5-1.1 THz range with a transmission level lower than 0.14. The proposed metasurface can be utilized as a terahertz modulator, reconfigurable filter, or switch. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.10008 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10008v1 Announce Type: new Abstract: Optical readout in low-light imaging is fundamentally limited by measurement noise, including photon shot noise, detector noise, and quantization error. In this regime, downstream inference depends not only on the optical front end, but also on how noisy high-dimensional sensor measurements are represented before classification or decision-making. Here we show that eigentasks provide a measurement-adapted representation for optical sensor outputs by ordering readout features according to their resolvability under noise. Using experimental data from a lens-based optical imaging system and a reanalysis of published data from a single-photon-detection neural network, we find that eigentask representations frequently outperform standard baselines including principal component analysis and filtering-based compression. The advantage is most pronounced in photon-limited, few-shot, and higher-difficulty classification regimes. In few-shot MPEG-7 classification, for example, the advantage over other methods reaches about 10 percentage points as the number of classes increases. In these settings, eigentasks yield more informative low-dimensional features and improve sample-efficient downstream learning. These results identify measurement-adapted representation as a promising strategy for optical inference when photon budget, acquisition time, and task complexity are constrained. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.10000 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10000v1 Announce Type: new Abstract: Diamond 1 - 10 micrometers thick membranes are platform for photonic, quantum and opto-mechanic devices with applications across UV-IR spectral ranges. IR characterization of diamond gratings in reflection and transmission showed a change of the IR absorbance dichroism between positive and negative when the grating period was 1-2 wavelengths (free space) including inside the region of the intrinsic diamond absorbance. Femtosecond laser cutting of micrometers-wide and mm-long structures are demonstrated by steps of carbonization > 0.4 J/cm2/pulse (1030 nm/200 fs) and oxidation of diamond membranes. Light intensity distribution inside form-birefringent diamond structure was modeled for a scaled-down structure and wavelength to reveal characteristic interference patterns for different polarizations. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.09816 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09816v1 Announce Type: new Abstract: High brightness and low coherence laser sources with wideband tunability are essential for many full-field imaging applications aiming for high contrast and speckle free performance. However, this combination of parameters is challenging to achieve. The current solutions focus on decreasing spatial coherence or generation of time-varying speckle patterns, while suppression of temporal coherence typically compromises brightness. Here we demonstrate a wideband pulsed laser source with low temporal coherence and the absence of phase correlation between pulses as an alternative approach with simultaneous time and frequency diversity. The full gain spectrum of a Tm doped fiber laser (1650 nm 2000 nm) is operated in a tunable noise like pulse regime, which by nature is composed of countless structured elementary events with uncorrelated phases randomly varying from bunch to bunch. The measured spectral widths range from 13.8 nm to 18.8 nm, while the average output power varies between 63.3 mW and 213 mW. Numerical simulations reveal that temporal coherence decreases significantly with increasing optical gain, dropping from near unity at low gain to approximately 0.2 at high gain. The startup dynamics of the noise like pulse laser are experimentally studied using the dispersive Fourier transformation (DFT) method. Based on single shot spectra and frequency resolved optical gating traces, the coherence properties of the laser are further analyzed by calculating the mutual coherence function and cross-spectral density. The noise like pulse laser exhibits a coherence time of approximately 100 fs and an average pulse burst duration of about 40 ps in the high-gain regime. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.09758 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09758v1 Announce Type: new Abstract: Optical fiber multi parameter sensing is fundamentally constrained by cross-sensitivity and the complexity of multi sensor integration. Here, we present a dual-dip heterogeneous long-period fiber grating (LPFG) sensing platform enabled by bending assisted annealing, which introduces anisotropic refractive index redistribution and mode dependent coupling enhancement. This process yields enhanced sensitivity, improved dip contrast, and opposite spectral responses between dual resonance dips, providing intrinsic spectral heterogeneity. To overcome temperature cross sensitivity, a polymer-encapsulated cascaded LPFG-FBG architecture is developed, where the LPFG serves as the microbending sensitive element and the FBG acts as a reference channel. PDMS encapsulation enhances stress transfer and suppresses interfacial slippage, improving linearity and repeatability. As a result, the bending sensitivity increases from -3.44 to -8.97 nm per cm, and the detection limit improves from 0.017 to 0.006 cm. Building on this, a multi parameter sensing paradigm is established by integrating dual dip heterogeneity with LPFGFBG spectral orthogonality. With PAAm functionalization, the platform enables simultaneous and decoupled sensing of temperature, bending, and humidity, demonstrating scalable and versatile multi parameter capability. Overall, this work establishes a minimalistic yet robust paradigm for multi-parameter fiber-optic sensing, offering a scalable strategy for high-performance sensing in structural health monitoring and harsh environments. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.09388 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09388v1 Announce Type: new Abstract: Tunable bound states in the continuum (BICs) in metasurfaces offer powerful opportunities to control light-matter interactions, yet the role of out-of-plane symmetry breaking remains poorly understood. Here, we reveal a mechanism that enables tunable high-Q BICs and directional radiation through out-of-plane symmetry breaking in all-dielectric metasurfaces. A substrate-free metasurface composed of periodically arranged multilayer cylinders that support overlapping magnetic dipole and electric quadrupole resonances, yielding electric mirror and symmetry-protected BIC responses at 1550 nm. Introducing multilayer substrates breaks out-of-plane symmetry and excites guided modes. When the guided-mode wavelength matches that of the BIC and coupling to the substrate is suppressed, the BIC wavelength remains nearly invariant, while the Q factor increases with layer number. In contrast, spectral detuning and enhanced coupling lead to pronounced blueshifts and rapid Q degradation. The interplay between guided-mode matching and coupling strength thus governs whether a BIC remains robust or becomes tunable. These findings establish a general framework for BIC engineering via out-of-plane symmetry breaking and provide a versatile platform for tunable metasurfaces with potential applications in integrated optics. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.09244 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09244v1 Announce Type: new Abstract: This paper presents a method for estimating the resolution of a digital holographic microscope using neural network analysis of reconstructed images. The spectral bandwidth of the source ($\Delta \lambda$) is used as a controlled image degradation parameter. Numerical simulations were performed within inline Gabor holography. A dataset of reconstructed images was generated for several test objects over a $\Delta \lambda$ range from 0.05 to 20 nm. The model predicts $\Delta \lambda$ from reconstructed images with high precision. The predictions are consistent with standard resolution metrics, including FWHM, MTF, and the USAF resolution criterion. The generalization analysis shows that the model is sensitive to the type of degradation. It captures interferometric distortions and responds selectively to the underlying physical mechanism. The proposed approach enables resolution estimation without explicit modeling of all degradation factors and can be applied to compact holographic systems. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.09219 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09219v1 Announce Type: new Abstract: Miniaturized photonic cavities generating nonlinear optical states of light are central to telecommunications and metrology applications. The emergence of such states is primarily underpinned by the ubiquitous Kerr nonlinearity that is present in all media. However, stimulated Raman scattering (SRS), an additional process inherent to many materials, has been shown to critically hinder the states' formation, imposing fundamental constraints on the choice of photonic platforms. Here, we introduce a novel strategy for the suppression of SRS in nanophotonic devices, adaptable to diverse Raman spectral responses. This is achieved by controlling the coupling and loss among multiple transverse spatial modes of the system, tailored across ultrabroad spectral bandwidths. Specifically, we combine nanometrically-corrugated Bragg gratings and tapered waveguides that, together enable co-directional multimode coupling and mode-selective filtering. We use lithium niobate as an exemplary Raman-active material to realize the concept, and we demonstrate the robust generation of two distinct Kerr nonlinear states (corresponding to coherent optical frequency combs) using the fabricated devices. The simplicity and generality of the concept suggest wide applicability to classical and quantum light generation on many technologically-relevant platforms nominally plagued by SRS (e.g., silicon and diamond photonics). More broadly, our multimode spectral shaping and filtering concept opens a path forward for highly-structured, wavelength-specific losses in nanophotonic waveguides and cavities, with potential applications in ultrafast and nonlinear integrated photonics. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.08939 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08939v1 Announce Type: new Abstract: Integrated microwave photonics (MWP) offers a powerful paradigm for handling high-speed microwave signals within chip-scale optical systems. It provides a cost-effective solution to address bandwidth, tunability, and loss bottlenecks of electronics-based radio frequency (RF) systems. The recently emerged thin-film lithium niobate (TFLN) photonic platform, with its exceptional electro-optic (EO) properties, low loss, and scalability, has shown promise to reshape the MWP landscape. Here, we discuss the performance implications of state-of-the-art TFLN photonic devices for MWP applications and offer insights into the emerging trends for next-generation wireless networks. In particular, the unparalleled EO bandwidth enables direct optical generation, processing, and reception of millimeter-wave or even terahertz (THz) signals, significantly expanding the operation frequency range of MWP systems. The low drive voltages and linearity of TFLN modulators lead to an unprecedented operation regime of radio-over-fiber (RoF) systems, featuring net gain, low noise figure and large dynamic range, simultaneously. The availability of a versatile device toolkit, combined with low optical loss and scalability, further supports the transition from traditional tabletop MWP systems to chip-scale solutions, with advanced functionalities, compact footprint, and enhanced system robustness. As the TFLN industrial ecosystem rapidly matures, TFLN-based MWP technology has the potential to deliver transformative solutions to future 6G integrated sensing and communication networks. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.08890 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08890v1 Announce Type: new Abstract: Atomic trimers constitute the smallest geometry in which collective electric and magnetic responses emerge from coupled electric dipoles. We present a theoretical study of collective mode excitation in atomic trimers as the geometry is continuously tuned from linear to equilateral, using the coupled-dipole method with a multipole expansion formulated about the optimal scattering center. By combining eigenmode analysis and symmetry classification, we provide a complete symmetry-resolved map of the six in-plane and three out-of-plane modes, revealing how symmetry reduction across the $D_{\infty h}$, $C_{2v}$, and $D_{3h}$ configurations governs the evolution of eigenmodes and their spectral features, lifting degeneracies, activating dark modes, and enabling full access to the modal spectrum. Based on this modal understanding, we demonstrate that forward-backward scattering can be switched solely by frequency detuning in a nearly linear trimer, without geometric reconfiguration. Furthermore, a linear trimer under s-polarized excitation supports a magnetic mode with a strongly enhanced magnetic field and a large Purcell factor, making it a promising platform for probing magnetic dipole transitions in atoms, with emission preferentially directed into the transverse plane. These results establish atomic trimers as a minimal platform where symmetry-controlled electric-magnetic mode engineering can be fully resolved and exploited for tailoring light-matter interaction at the atomic level. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.08880 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08880v1 Announce Type: new Abstract: Metasurfaces offer compact flat lenses (metalenses) for miniaturized imaging systems; however, the utmost miniaturization requires not only metalenses but also a substantial reduction of free space. A Spaceplate is a flat-optics element designed to mimic free-space propagation, effectively propagating light over a distance far exceeding its physical thickness, with the induced squeezed length serving as the key figure of merit. Despite substantial progress, most existing spaceplate designs have been fundamentally constrained by a trade-off between squeezed length and numerical aperture, and none has demonstrated a feasible structure supporting both a moderate numerical aperture and a millimeter-scale squeezed length. We report a metasurface spaceplate reaching the milestone of a millimeter-scale squeezed length with a practical numerical aperture. We achieved this by combining advantageous elements from existing approaches: high compression ratios and inverse-design flexibility in optimized multilayer metasurfaces, serving as the spaceplate unit structure, and preserving its numerical aperture by coupling its replicas, to construct a coupled cascaded spaceplate with an increased thickness. For operation in the mid-wave infrared, we demonstrated an optimized spaceplate exhibiting a high compression ratio of ~14 with a physical thickness of ~80 {\mu}m, resulting in a squeezed length of 1.09 mm, for a numerical aperture of 0.13. We developed a general framework for calculating the transmission characteristics of multilayered spaceplates while optimizing their layer thicknesses to accurately reproduce the target free space. Strikingly, millimeter-scale squeezed lengths with practical numerical apertures via metasurface spaceplates pave the way for ultrathin imaging systems through their utmost miniaturization, opening a new paradigm for augmented reality headsets, cellphones, and many more. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.08821 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08821v1 Announce Type: new Abstract: Traditional metasurfaces often face challenges in achieving broadband functionality and dynamic adaptability, limiting their use in advanced electromagnetic systems. This paper presents a triple circular ring metasurface designed for multifunctional electromagnetic applications, including surface wave propagation, beam shaping, and ultra-broadband radar cross-section (RCS) reduction. The proposed structure uses a cost-effective FR-4 substrate and demonstrates strong electromagnetic reflection characteristics across 50-100 GHz. Except near 91 GHz, the metasurface exhibits amplitude and phase responses comparable to a conventional copper plate while maintaining efficient surface wave propagation. Significant electric and magnetic field amplitudes of nearly 1 V/m and 5x10^-3 A/m are sustained across the surface, unlike a standard copper plate. The metasurface also redirects incident energy toward a predefined direction of 67 degrees in the phi plane while minimizing radiation over a 360-degree angular range. In addition, it achieves a stable monostatic RCS reduction from -40 dB to -30 dB across a broad frequency range, outperforming conventional copper structures. Numerical simulations validate the proposed design. The results demonstrate strong potential for stealth technology, radar systems, and next-generation wireless communications. Physics/physics.optics_(Optics) https://arxiv.org/abs/2605.08387 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08387v1 Announce Type: new Abstract: Tip-Enhanced Raman Spectroscopy (TERS) can be used to make nanoscale spatial measurements of 2D materials, such as graphene and transition metal dichalcogenides (TMDs). The TERS theory introduced in [Phys. Rev. X 4, 031054 (2014)], however, was tailored for graphene, whose out-of-plane Raman response is neglected. In the present work, we include the out-of-plane response in the TERS theory. In doing so, we provide an exact analytical expression for the field propagation between the tip and the sample, and show that the contribution to the TERS signal that scatters first at the sample, then at the tip (sample-tip, or TS) is important only when the out-of-plane response is significant. We extensively study the variation of TERS experimental measurements when varying physical parameters of the system, like the tip radius, the out-of-plane response, the TERS coherence length, and others. It becomes evident that the TERS enhancement is very sensitive to the out-of-plane Raman response of the phonon mode, while normalized tip-approach measurements are more sensitive to the coherence length, and we show that the medium refractive index leads to an effective tip enhancement factor $f_e$. Our results lead to the conclusion that, in general, a strong TERS enhancement is a necessary condition for investigating the physics discussed here, which here means surveying the difference in TERS signals between different Raman modes. We use our model to analyze some graphene TERS experiments, showing that they are consistent with a negligible out-of-plane Raman response and a non-zero TERS coherence length in the fitting. Physics/physics.optics_(Optics) https://arxiv.org/abs/2503.17459 Tue, 12 May 2026 00:00:00 -0400 arXiv:2503.17459v2 Announce Type: replace-cross Abstract: Diffuse correlation spectroscopy (DCS) is a noninvasive optical technique that probes microvascular blood flow in deep tissues. Here, we present and validate a new on-chip hardware correlator for high-speed DCS measurements. The correlator is embedded in a custom-built 512 x 512 single-photon avalanche diode (SPAD) array named ATLAS, which computes intensity autocorrelation functions directly on-chip at a sampling rate of 116 Hz - the fastest DCS acquisition reported to date. Unlike conventional DCS systems that suffer from low light throughput and therefore cannot resolve cardiac pulsations at source-detector separations (rho) beyond 30 mm, our massively parallel on-chip architecture computes autocorrelations within each macropixel, eliminating the data-throughput bottleneck. This enables high-SNR, real-time detection of pulsatile blood flow even at rho = 50 mm on the human forehead. In phantom experiments at rho = 25 mm, ATLAS-DCS achieves a 12-fold improvement in signal-to-noise ratio over a conventional single-channel DCS instrument while operating at 116 Hz. In human subjects, we resolve functional hyperemia during a mental arithmetic task at rho = 30 mm. Furthermore, we integrate ATLAS DCS with a frequency-domain near-infrared spectroscopy (FD-NIRS) module, enabling simultaneous monitoring of blood flow and tissue oxygenation. With this combined system, we can concurrently resolve core hemodynamic parameters. The on-chip parallelized DCS design substantially improves detection speed, depth sensitivity, and real-time capability, paving the way for wearable, high-speed cerebral blood flow monitoring in both clinical and research settings. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2604.27418 Tue, 12 May 2026 00:00:00 -0400 arXiv:2604.27418v2 Announce Type: replace Abstract: Spatially fractionated radiation therapy (SFRT) planning requires three coordinated tasks: generation of high-dose sphere structures, position-aware optimization, and peak-valley dose ratio evaluation. We present MAAS-SFRThelper, a shared-source Eclipse Scripting Application Programming Interface (ESAPI) plugin that integrates structure generation, geometric-aware optimization, and peak-valley dose ratio evaluation for SFRT into a single workflow inside Varian's Eclipse treatment planning system. The plugin exposes five task-oriented tabs sharing common services for sphere extraction and objective creation. The SphereLattice tab generates sphere lattices using five placement patterns. The Optimization tab searches over candidate lattice positions using a four-metric geometric surrogate score and triggers VMAT optimization and dose calculation. The Evaluation tab implements four analysis modes; its three-dimensional peak-valley classification recovers sphere centers from the lattice structure through a geometric extraction pipeline rather than relying on dose thresholds. We validated all functionality on digital phantoms against analytic ground truth. The plugin is distributed as source code under the Varian Limited Use Software License Agreement. Source code and documentation are publicly available on GitHub. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2601.05717 Tue, 12 May 2026 00:00:00 -0400 arXiv:2601.05717v2 Announce Type: replace Abstract: Inter-crystal scattering (ICS) in Positron Emission Tomography (PET) is commonly regarded as a degradation effect that might compromise the image spatial resolution. In parallel, the inclusion of ICS events has also been recognized as a potential approach to increase PET sensitivity, which could be especially beneficial in scenarios where the latter is a limiting factor, such as very small animal imaging. Several methods for the recovery of ICS events have been proposed, many of which aim to locate the first interaction, i.e., the Compton scattering site, usually limited by their success rate, computational burden or data and training dependency. Conversely, this work proposes a physics-based model for ICS events, leading to analytical expressions of the sensitivity image and the system matrix (required by statistical reconstruction algorithms), without the need to identify the original line of response. After validating the model, the work shows how ICS events can be integrated into a joint image reconstruction algorithm (based on list-mode MLEM) together with conventional PET events, for which dedicated analytical models are also developed. To assess the performance of the proposed approach, Monte-Carlo simulated and experimental data of an image quality phantom were obtained with the MERMAID small-fish PET scanner prototype. Both simulation and experimental results indicate that, while slightly decreasing the recovery coefficient values, the inclusion of ICS clearly reduces statistical noise and improves uniformity. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2511.20514 Tue, 12 May 2026 00:00:00 -0400 arXiv:2511.20514v4 Announce Type: replace Abstract: Many minimally invasive procedures, such as core needle biopsy of focal liver lesions, nerve blocks, and fetal and vascular interventions, are typically performed under ultrasound guidance, which provides real-time, high-resolution visualisation of tissue anatomy. Accurate and efficient localisation of the needle tip relative to patient anatomy is essential for guiding the needle towards the procedure target, avoiding adverse events and reducing the need for repeat procedures. However, the 3D nature of the procedure and poor image contrast of the needle in heterogeneous tissue or at steep insertion angles often lead to confusion over the true location of the tip within the 2D guidance images, and existing methods to enhance needle visibility largely remain limited to 2D. Here, we present a novel interventional ultrasound system capable of 2D B-mode imaging and 3D needle tracking. The tip location is determined from the time-of-flight of ultrasound generated by a photoacoustic beacon embedded in the needle bevel and received by a sparse receiver array distributed around the imaging system's curvilinear ultrasound probe. The measured tracking accuracy was better than 2 mm for depths up to 140 mm in water, and approximately 2 mm on average in an ex vivo tissue phantom, with referenced positions derived from X-ray computed tomography. In a usability study involving 12 clinicians performing biopsy procedures in a ex vivo tissue phantom, the failure rate was reduced by 35%, from 15.8% to 10.3% after only a few minutes of training. These results demonstrate that the proposed system has strong potential to support a wide range of minimally invasive procedures by enabling clinicians to accurately target small anatomical structures, improving the efficiency and effectiveness of diagnostic sampling and therapeutic delivery or ablation, and reducing the risk of adverse events. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.08517 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08517v1 Announce Type: cross Abstract: We describe an approach for estimating the statistical risk of deep networks that contain a mix of learned and known operators. Building on the maximal training error bounds previously established for known operator learning, we derive a deep risk estimator that connects the expected error of a layered network to the size of the training sample. The estimator decomposes the total risk into a sum over learned layers; every known operator contributes zero to this sum, while every learned layer adds an approximation term inspired by Barron's classic work and an estimation term that decreases with the number of training samples. We are able to show that the bound shrinks whenever a learned layer is replaced by a known operator and that the corresponding sample requirement scales with the number of trainable parameters of the layer that is replaced. As an application, we use computed tomography as an example and compare an operator-aware filtered backprojection network with a fully connected substitute that collapses the entire reconstruction pipeline into a single learned dense matrix. The predicted parameter ratio coincides with the structural sparsity that the analytic decomposition into a circulant filter and a sparse backprojection exposes. We confirm the predicted scaling on CPU at small image scale and on GPU at medium image scale, all on the same scaling law. Beyond CT reconstruction, the estimator applies to physics-informed neural networks that hardcode a known physical operation in its architecture, and we expect the result to be of interest for a broad community working on operator-aware deep learning. Calibrating the per-layer constants on each sweep yields a bound that tracks the empirical test MSE within a factor of two at every training-set size, so the estimator can be inverted to predict how many training samples are required to reach a target error. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.10871 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10871v1 Announce Type: new Abstract: This work proposes Attractor-Vascular Coupling Theory (AVCT), a mathematical framework showing that cardiac attractor geometry encodes blood pressure (BP) information sufficient for AAMI-standard estimation, and validates the theory through a calibrated cuffless BP model using photoplethysmography (PPG). AVCT is grounded in Cardiac Stability Theory and operationalized using Takens delay embedding and attractor morphology extraction. Two theorems, one proposition, and one corollary formally justify the use of PPG attractor features for BP estimation and predict the feature-importance hierarchy. A LightGBM model trained on pulse transit time (PTT) and Cardiac Stability Index (CSI) attractor features under single-point calibration was evaluated using strict leave-one-subject-out cross-validation (LOSO-CV) on 46 subjects from BIDMC ICU (n = 9) and VitalDB surgical data (n = 37), comprising 29,684 windows. The model achieved systolic BP (SBP) mean absolute error (MAE) of 2.05 mmHg and diastolic BP (DBP) MAE of 1.67 mmHg, with correlations r = 0.990 and r = 0.991, satisfying the AAMI/IEEE SP10 requirement of MAE below 5 mmHg. Median per-subject MAE was 1.87/1.54 mmHg, and 70%/76% of subjects individually satisfied AAMI criteria. A PPG-only ablation using nine smartphone attractor features matched the ECG+PPG model within 0.05 mmHg, demonstrating that clinical-grade BP tracking is achievable using only a smartphone camera while surpassing prior generalized LOSO-CV results using fewer sensors. All four AVCT predictions were quantitatively confirmed, with 91.5% error reduction from uncalibrated to calibrated estimation (epsilon_cal = 0.915). Unlike post-hoc explainable AI methods, AVCT predicts features satisfying the architectural faithfulness criterion of the Explainable-AI Trustworthiness (EAT) framework and grounding BP estimation in nonlinear dynamical systems theory. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.09267 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09267v1 Announce Type: new Abstract: Current magnetic resonance imaging (MRI) requires the subject to remain stationary to limit motion artifacts and avoid unwanted field-induced brain stimulation. However, imaging during large-scale motion could enable studies in which motion itself is central. One example is the study of brain networks involved in vestibular function, which senses head motion. Here, we demonstrate Moving MRI (mMRI), a system that enables imaging during large-scale motion by moving the subject and scanner together to minimize relative motion. We implemented a proof-of-concept platform using a compact, cryogen-free superconducting magnet mounted on a pneumatically actuated tilt mechanism that moves the magnet, gradients, and RF coil as a unit during scanning. Phantom and in vivo rat brain scans were acquired during repetitive tilting. We characterized artifacts arising from tilt-induced field shifts and residual subject-scanner motion, and partially reduced these effects. mMRI enables imaging during large-scale movement and may broaden access to naturalistic vestibular paradigms while providing a foundation for future human systems. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.09091 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09091v1 Announce Type: new Abstract: Quantifying muscle tissue properties is crucial for understanding pathophysiological changes occurring in skeletal muscle (SM). In particular, T2 relaxation and diffusion MRI (dMRI) are promising techniques. However, typical methods measure T2 and diffusion separately, making them less specific to microstructure than emerging combined diffusion-relaxation techniques. Here we demonstrate a combined diffusion-relaxation MRI approach for disentangling T2 and diffusivity properties in SM. A diffusion-relaxation acquisition was implemented on a 3 T scanner, combining six b-values and four echo times within a 12-min single-slice protocol. Five healthy participants were enrolled. Data were analysed with six microstructural diffusion and diffusion-relaxation models. Mean parameter values were extracted from manually segmented calf muscles. Models neglecting T2 relaxation showed strong TE dependence: mean diffusivity (MD) decreased by up to 47\%, fractional anisotropy (FA) increased by up to 75\%, and vascular fraction fv increased by up to 297\% when TE increased from 50 to 90 ms. Diffusion-relaxation models produced TE-independent estimates. Tissue and vascular relaxation times ranged 31-36 ms T2t and 66-86 ms T2v, respectively. Simulations confirmed improved accuracy for fv estimation (r=0.95; RMSE=0.03) and reduced TE-related bias. Combined diffusion-relaxation MRI provides robust, TE-independent estimates of muscle microstructural and perfusion-related biomarkers. The quantitative improvements observed - particularly in the estimation of fv - show its potential to provide non-invasive biomarkers for the assessment of muscle physiology, exercise adaptation, rehabilitation, and neuromuscular pathology. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.08957 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08957v1 Announce Type: new Abstract: Purpose: Diffusion MRI has shown promise for breast cancer screening, lesion characterization,and treatment response monitoring without contrast agents, but further translation is constraint by the gradient performance of conventional systems. The aim of this work is to develop a single-axis high performance bilateral plug-and-play breast gradient insert to enable strong-gradient diffusion MRI. Methods: An in-house breast gradient insert and bed-tabletop was constructed entirely from commercially available materials, providing a cost-effective solution compatible with existing MRI systems. Its wiring pattern was optimized for torque and force balancing, power dissipation, and target field performance. Evaluation included gradient field characterization, peripheral nerve stimulation simulation verification, and temperature and eddy current assessment. The setup was used for imaging of a diffusion phantom based on soy lecithin across a range of b-values. Results: Gradient efficiency reached 2.8 mT/m/A, enabling local strengths up to 1850 mT/m (660 A). No peripheral nerve stimulation was observed during tests on five healthy volunteers. Eddy currents were successfully characterized employed in standard correction methods. Imaging showed the feasibility of $b = 10 000 s/mm^2$ acquisitions at TE = 78 ms versus 161 ms with scanner gradients. Conclusion: This work demonstrates a dedicated bilateral breast gradient insert for safe and feasible strong-gradient breast diffusion MRI, and represents a first step toward dedicated hardware for breast cancer detection and characterization without contrast agents. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2605.08711 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08711v1 Announce Type: new Abstract: White matter hyperintensities (WMH) are bright regions on T2-weighted magnetic resonance imaging (MRI) scans and are associated with cerebrovascular pathology and neurodegeneration, including myelin loss. While Luxol Fast Blue histopathology provides visualization of myelin integrity, quantitative analysis requires measuring Optical Density as a proxy for myelin concentration. However, differences in laboratory protocols and tissue processing introduce staining variability that acts as systematic noise, obscuring the biological signal and preventing consistent comparison across histology runs. To address this, we developed an automated pipeline that identifies reference (non-pathologic) regions in whole-slide images to compute normalized Optical Density heatmaps. We validated this approach through two complementary evaluations: (1) comparison against expert ratings of myelin loss severity, and (2) cross-modal spatial comparison with co-registered 7T ex vivo MRI for voxel-wise evaluation within white matter regions. The pipeline's reference selection showed strong concordance with expert-identified reference regions, and normalized Optical Density demonstrated a substantially stronger correlation with MRI signal intensity than raw measurements. This correlation persisted within WMH, confirming that the pipeline captures continuous myelin pathology rather than merely the presence or absence of myelin loss contrast. By mitigating staining artifacts, this pipeline provides a robust, validated framework for quantitative cross-modal comparison, establishing a critical methodological foundation for future translation to in vivo myelin mapping and biomarker discovery. Physics/physics.med-ph_(Medical_Physics) https://arxiv.org/abs/2501.04664 Tue, 12 May 2026 00:00:00 -0400 arXiv:2501.04664v2 Announce Type: replace-cross Abstract: Quantum paradoxes show that the outcomes of different quantum measurements cannot be described by a single measurement-independent reality. Any theoretical description of a quantum measurement implies the selection of a specific measurement context. Here, we investigate generalised quantum measurements, in order to identify the mechanism by which this specific context is selected. We show that external quantum fluctuations, represented by the initial state of the measurement apparatus, play an essential role in the selection of the context. This has the non-trivial consequence that, when considering measurements other than just idealised projection-valued measures, different outcomes of a single measurement setup can represent different measurement contexts. We further show this result underpins recent claims that contextuality can occur in scenarios without measurement incompatibility. Physics/physics.hist-ph_(History_and_Philosophy_of_Physics) https://arxiv.org/abs/2603.04159 Tue, 12 May 2026 00:00:00 -0400 arXiv:2603.04159v2 Announce Type: replace Abstract: Can we infer whether all of physical reality began to exist? Several novel results are offered suggesting a negative verdict. First, a common strategy for defending a cosmic beginning involves showing that individual beginningless cosmological models are implausible. This strategy is shown to make an elementary error in confirmation theory. Second, two necessary (but not necessarily sufficient) conditions are offered for a cosmic beginning. Third, three extensions are offered to the Malament-Manchak theorems. The three extensions show that in almost all classical spacetimes, observers cannot collect sufficient data to determine whether the application conditions for the classic singularity theorems are satisfied or whether their spacetime satisfies the two necessary conditions for a cosmic beginning. Lastly, a reply is offered to the objection that the skeptical consequences of the three extensions can be overcome with induction. Importantly, all past singular dust FLRW spacetimes have observationally indistinguishable counterparts which, while sharing a number of important local properties, either do not include a singularity to the past of every point or else do not have the sort of time ordering intuitively required for a cosmic beginning. Physics/physics.hist-ph_(History_and_Philosophy_of_Physics) https://arxiv.org/abs/2605.09558 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09558v1 Announce Type: cross Abstract: Contextuality is considered as one of the most distinctive features of nonclassical systems. Here we show that a Spekkens contextual system (nonclassical) under decoherence becomes noncontextual (classical) after a certain threshold. We show also that some quasiprobability representations are more effective than others in showing nonclassical features. This will help us understand the relationship between decoherence, Spekkens' generalised contextuality, and quantum advantage from universality for quantum computation. Physics/physics.hist-ph_(History_and_Philosophy_of_Physics) https://arxiv.org/abs/2605.01273 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.01273v2 Announce Type: replace Abstract: Relative Geologic Time (RGT) estimation from seismic data is a cornerstone of subsurface structural modeling, depositional evolution analysis, and reservoir characterization, supporting horizon correlation and depositional system reconstruction. Yet accurate RGT estimation remains challenging: RGT is intrinsically a topologically constrained continuous field, in which local errors readily propagate globally and distort the overall result. Conventional methods rely heavily on priors, attribute extraction, and manual interaction, leading to cumbersome workflows. Existing deep-learning approaches mostly use a regression formulation with pixel-wise MSE/MAE losses, which struggle to capture thin horizons and fail to model the stratigraphic semantics of the RGT field, yielding limited generalization and unstable ordering across diverse structural and depositional settings. We propose RGT-Est, a deep-learning framework that transfers the optimization target from the topologically constrained continuous field into a differentiable sinusoidal space, which explicitly encodes the periodic stratigraphic semantics of RGT and alleviates over-smoothing of fine horizons. Pointwise, perceptual, and adversarial losses are jointly imposed in this space to enforce local fidelity, inter-layer consistency, and global structural plausibility, providing both fine-horizon discrimination and global stratigraphic awareness. An optional horizon-guidance module further accepts sparse 2D or 3D horizons as priors. Trained on synthetic data and evaluated on field surveys with densely faulted zones, large unconformities, steeply dipping strata, folded deformations, and clinoforms, RGT-Est achieves state-of-the-art performance among AI-based methods without horizon constraints, and attains substantially higher horizon-correlation accuracy and global topological consistency once sparse priors are incorporated. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2412.17685 Tue, 12 May 2026 00:00:00 -0400 arXiv:2412.17685v2 Announce Type: replace Abstract: Space weather risk assessment is constrained by the lack of available asset information needed to model Geomagnetically Induced Currents (GICs) in electricity transmission infrastructure. We propose a reproducible method that enables risk analysts to collect their own open-source substation data. Utilizing an innovative web-browser platform for annotation, we convert OpenStreetMap substation locations to high-resolution, component-level mappings of electricity transmission assets. For example, we convert an initial 1,313 high-voltage (>115 kV) substations to 52,273 substation components via Google Earth APIs utilizing low-altitude, satellite, and streetview imagery. Approximately 41,642 substation components (79.6%) connect to the highest substation voltage levels (>345 kV) and are potentially susceptible to GICs, with 7,949 identified transformers. Compared to the OpenStreetMap baseline, this approach provides detailed insights on voltage levels, line capacities, and substation configurations. We then construct a geospatial GIC network for the Tennessee Valley Authority region, comparing May 2024 results with the UIUC150 synthetic network and with measured ground GICs at 13 monitoring devices. Importantly, the two open-source networks produce 95th-percentile peak ground GIC values within 4% of each other, and the modeled time series broadly capture the temporal morphology of the storm at the monitoring sites. This method shows promise for spatially explicit GIC screening and regional nowcasting without requiring access to operator data. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2605.10342 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10342v1 Announce Type: new Abstract: Abyssal hills, arguably the most extensive coherent pattern in Earth's surface topography, record the spacing of normal faults formed at mid-ocean ridges. At fast-spreading ridges, high-resolution bathymetry shows a pronounced spectral peak near 41 ky, coincident with obliquity-paced Pleistocene sea-level variability. The origin of this apparent orbital imprint on seafloor structure remains unresolved. We hypothesise that glacial-interglacial sea-level variability influences fault spacing by modulating plate thickness and the flexural stresses produced during plate unbending. Sea-level change alters mantle melting rates and magma supply at ridge axes, generating variations in the properties of the accreting plate. As the plate moves off axis, it unbends from its ingrown curvature, producing tensile fibre stresses that drive normal faulting. We hypothesise that small perturbations in elastic plate thickness modulate these stresses and thereby influence fault spacing. To test this, we extend the elastic unbending theory of Buck (2001) to include spatially variable plate thickness and yield-weakening viscoplastic flexure, which localises deformation into discrete kinks interpreted as faults. Linearised analysis shows that plate-thickness perturbations generate proportional fibre-stress variations. Numerical solutions demonstrate that perturbations as small as approximately 0.1 percent can phase-lock faulting to the imposed forcing. When driven by plate-thickness perturbations derived from the Pleistocene oxygen-isotope record, the model predicts fault spacings concentrated near 41 ky in the early Pleistocene and near 100 ky in the late Pleistocene, consistent with observed abyssal-hill spectra. These results provide a quantitative mechanism by which glacial-interglacial sea-level variability can be transmitted into tectonic structure. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2605.09960 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09960v1 Announce Type: new Abstract: Travel-time tomography forces a trade-off between mesh resolution and stability in which the regularizer choice dominates what can be recovered. We introduce MIMIR, a differentiable framework that represents the 2D velocity field as a Fourier-feature neural network, replacing the grid-based slowness vector with a continuous, infinitely differentiable function. Prior neural-field tomography has staircased smooth fields under total-variation (TV) priors or oscillated near interfaces under $L^2$ Laplacian smoothing. We adopt second-order total generalized variation (TGV$^2$) and parametrize its auxiliary vector field as a second neural network jointly optimized with the velocity field, eliminating the inner Chambolle-Pock primal-dual loop that classically dominates TGV computation. On three synthetic benchmarks (Gaussian, horizontally layered, curved-fault inspired by OpenFWI) using cross-well acquisition, 5% travel-time noise, and five seeds, MIMIR-TGV$^2$ ties a classical FMM-LSMR baseline with auto-tuned hyperparameters on the Gaussian ($p=0.134$, paired $t$-test) and significantly outperforms it on layered ($p<0.0001$, 44% RMSE reduction) and curved-fault ($p=0.0002$, 33% reduction). Replacing TGV$^2$ with TV degrades performance on Gaussian ($p=0.004$) and layered ($p=0.003$); curriculum-annealed TV improves Gaussian RMSE by only 5.4%, confirming that TV's staircase bias is intrinsic to the regularizer rather than a scheduling artifact. The results empirically validate the Bredies-Kunisch-Pock prediction that piecewise-affine priors are better suited to subsurface velocity recovery than piecewise-constant TV priors. We argue that the central design choice in physics-informed neural-field inversion is not the network architecture but the regularizer. The full pipeline reproduces in under one hour on consumer hardware. Physics/physics.geo-ph_(Geophysics) https://arxiv.org/abs/2509.14497 Tue, 12 May 2026 00:00:00 -0400 arXiv:2509.14497v2 Announce Type: replace Abstract: Methods for predicting material properties often rely on empirical models or approximations that overlook the fundamental topological nature of quantum interactions. We introduce a topological framework based on string theory and graph geometry that resolves ultraviolet divergences as topological obstructions regularized via Calabi-Yau mappings while preserving symmetries and causal structures, where molecular and condensed matter systems are represented combinatorially through a graph where M-branes form vertices and open strings are twistor-valued edges, holomorphically encoding geometric data from the dynamical system. The resulting effective action is governed by a graph Laplacian whose spectrum dictates stability, excitations, and phase transitions. Applied to uniaxial nematic liquid crystals, the model not only recovers the phenomenological virtual volumes of the Jiron-Castellon model from first principles but also predicts anisotropic thermal expansion coefficients and refractive indices with precision exceeding 0.06\%. The quantitative agreement with experiment, achieved without fitted parameters, demonstrates that principles from quantum gravity and string theory can directly yield accurate predictions for complex materials. Physics/physics.gen-ph_(General_Physics) https://arxiv.org/abs/2407.14533 Tue, 12 May 2026 00:00:00 -0400 arXiv:2407.14533v4 Announce Type: replace Abstract: Introduction: molecular geometry, the three-dimensional arrangement of atoms within a molecule, is fundamental to understanding chemical reactivity, physical properties, and biological activity. The prevailing models used to describe molecular geometry include the Valence Shell Electron Pair Repulsion (VSEPR) theory, hybridization theory, and molecular orbital theory. While these models provide significant insights, they also have inherent limitations. Applying string theory and graph theory with topological and macrotensorial methods could improve the understanding of molecular behavior. Objective: explore the potential applications of string and graph theory to material science, focusing on molecular geometry, electron domains, and phase changes via symmetries. Molecular geometry: each molecule is associated with a simple graph with an orthonormal representation inducing metrics via the usage of macrotensor operators, allowing the calculation of angles between molecules and following the equations of motion. Phase changes: a series of inequalities are proposed depending on the energy-momentum densities of bonds and the edges of the associated graph where electrons or atoms are located, its topology, and isometries, exploring possible new states of matter. Conclusions: application of macrotensors, graphs, string theory, partitions, and correlation functions of dimensions to material science, specifically to molecular geometry and phase changes, allows for a more dynamic and flexible description of natural phenomena involving matter and the prediction of possible new states of matter as other forms of condensates. This presents a different perspective, opening possibilities for Experimental confirmation, applications, simulations of examples and further refinement of the presented approach are anticipated, which could be transformative for material science. Physics/physics.gen-ph_(General_Physics) https://arxiv.org/abs/2605.10868 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10868v1 Announce Type: new Abstract: The Law of Universal Gravitation is part of middle and high school's general physics and astronomy curricula. This topic is included in the most popular physics textbooks available as a fact whose origin remains in the detailed work of Sir Isaac Newton 300 years ago. Consequently, its mathematical form is presented as an equation without any deductive process. Nevertheless, deduction of the mathematical form of this law is an opportunity to discuss how a deductive process can be performed using the data available on the Internet from reliable sources. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2605.09602 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09602v1 Announce Type: new Abstract: AI chatbots are increasingly used by students as study tools in physics, raising practical questions about their reliability on conceptual tasks. Existing evaluations of large language models (LLMs) on physics concept inventories rely almost exclusively on instruments that have been publicly available for years and likely appear in model training data, making it difficult to disentangle physics competence from familiarity with the test items themselves. We address this issue by evaluating three frontier LLMs (GPT-5.2, Gemini 3 Pro, Gemini 3 Flash) on the Classical Relativity Concept Inventory (CRCI), a recently developed and validated 21-item instrument on Galilean relativity that was not publicly available at the time of testing. Each item was administered 30 times per model, and all 1890 responses were qualitatively coded along three dimensions: visual interpretation, physics reasoning, and coordination. Mean accuracy was 97% for Gemini 3 Flash, 89% for Gemini 3 Pro, and 73% for GPT-5.2, compared to 62% for the student sample (N = 267). However, all three models fail completely on a small number of items. The qualitative analysis shows that these failures stem predominantly from misinterpretations of visual content rather than from deficits in physics knowledge, and that LLM errors differ structurally from those of students: when models err, they converge on a single distractor with high consistency, whereas student errors are more broadly distributed. These findings indicate that chatbot reliability on conceptual physics is item-dependent and unpredictable, with direct implications for how concept inventories are administered. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2605.09520 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09520v1 Announce Type: new Abstract: For a long time, the cloud chamber was the only educational tool available for measuring radiation. In recent years, simple radiation detectors combining scintillators with silicon photomultipliers have become increasingly common for these purposes. However, students are not able to see the scintillation light, the core process of radiation measurements with scintillators. Therefore, we explored the possibility of detecting scintillation light using two general-purpose cameras. In addition, we examined how differences in the spatial distribution relate to radiation types and energies. Scintillation light were able to be measured by a general-use camera, and their spatial distribution indicates radiation energy. This method could be utilized as an accessible imaging setup to compare radiation properties in a classroom. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2605.08510 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08510v1 Announce Type: new Abstract: Since 2019, eighteen NSF Research Traineeship (NRT) awards in quantum information science and engineering (QISE) and adjacent fields have been funded, constituting the largest NSF-coordinated investment in graduate QISE training in the United States. Synthesizing lessons from our programs, we work through the central tensions that every QISE graduate program must negotiate: between depth in a home discipline and breadth across the field, between structured instruction and open-ended experiential and hands-on learning, and between training individual specialists and cultivating teams that collectively cover all areas of QISE. We describe the structural and pedagogical innovations the NRT programs have developed in response, assess what is working and what remains unresolved, and sketch 12 open problems the community will need to address as QISE graduate education scales beyond the well-resourced research universities where it has up till now been mainly concentrated. Eight concrete recommendations follow: (1) adopt the startup model of team-based training as an organizing philosophy; (2) invest immediately in sensing and communication curriculum development; (3) build student agency into program governance, not just activities; (4) establish structural mechanisms for industrial engagement rather than depending on goodwill; (5) design for sustainability from year one; (6) develop graduate-level textbooks spanning all three QISE pillars: computing, sensing, and communications; (7) establish shared outcome assessment instruments across programs; and (8) develop structured mechanisms for faculty professional development in QISE. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2605.08361 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08361v1 Announce Type: new Abstract: Aspects of quantum physics are no longer confined to the upper years of a physics degree. Concepts like superposition or entanglement that were once reserved for second- or third-year undergraduate courses now deserve attention earlier in a student's curriculum. Technology is changing at a pace that requires engaged citizens to understand some of the quantum basics if they are to make sense of the world. This paper offers a cartoon building analogy that teachers can use to introduce quantum numbers to their students. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2605.08227 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08227v1 Announce Type: new Abstract: This study presents a classroom-friendly method for measuring the coefficient of viscosity of a liquid using a smartphone s accelerometer sensor. A metallic ball tied with a spring-mass system and submerged in mustard oil undergoes damped oscillations due to viscous forces. The Phyphox app is used to record the temporal variation of acceleration, from which the damping constant is calculated to determine the coefficient of viscosity of the oil. The experimentally obtained value is further validated using the Tracker app, and this value is shown to be in close agreement with the standard literature. This method provides an accurate, low-cost experiment ideal for educational settings, utilizing smartphone sensors for viscosity measurement. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2605.08204 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08204v1 Announce Type: new Abstract: In this paper, we have proposed a simple method of measuring the density of a solid material. We have utilized the pressure sensor of a smartphone as a pressure-measuring device. By measuring the values of pressure when a solid object is in air and also in the fully immersed condition in a non-reactive liquid, we have determined the density of the object. Physics/physics.ed-ph_(Physics_Education) https://arxiv.org/abs/2603.20423 Tue, 12 May 2026 00:00:00 -0400 arXiv:2603.20423v4 Announce Type: replace-cross Abstract: A generalisation of Takens' delay-coordinate embedding theorem to stochastic systems, the Stochastic Embedding Sufficiency Theorem, is an inverse methodology enabling non-parametric recovery of both drift and diffusion fields from scalar time series without prior assumptions about the governing physics. A blind protocol using only time series data is applied to nine domains: classical mechanics, statistical mechanics, nuclear physics, quantum mechanics, chemical kinetics, electromagnetism, relativistic quantum mechanics, quantum harmonic oscillator dynamics, and quantum electrodynamics. Fundamental constants (the Boltzmann constant, the Planck constant, the speed of light, the Fano factor, and the Van Kampen scaling exponent) emerge in both drift and diffusion channels without prior specification. The recovered diffusion coefficients, viewed across domains, constitute an empirical pattern, the $\sigma$-continuum, in which $k_B$, $\hbar$, and $c$ play structurally distinct roles. The Gravitational Diffusion Theorem, derived from the fluctuation-dissipation theorem, massless mode structure of linearised gravity, and gravitational self-coupling via the equivalence principle, determines the gravitational diffusion coefficient as one Planck length per square root of Planck time. Four canonical axioms formalise the framework, within which the noise character, drift, covariance operator, and fluctuation amplitude are uniquely determined by theorem, yielding the superspace diffusion hypothesis: $\mathrm{d}g_{ij} = \mathcal{D}_{ij}[g]\,\mathrm{d}\tau + \ell_P\,\mathrm{d}W_{ij}$ where all coefficients are non-parametric, first-principles consequences of the axioms. An implication of the hypothesis is that coarse-graining of the superspace Fokker-Planck equation via Mori-Zwanzig projection yields predictions for galactic-scale gravitational acceleration testable against kinematic data. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2602.07165 Tue, 12 May 2026 00:00:00 -0400 arXiv:2602.07165v2 Announce Type: replace-cross Abstract: We introduce an R package for Bayesian modeling and uncertainty quantification for problems involving count ratios. The modeling relies on the assumption that the quantity of interest is the ratio of Poisson means rather than the ratio of counts. We provide multiple different options for retrieval of this quantity for problems with and without spatial information included. Some added capability for uncertainty quantification for problems of the form $Z=(mT+z_0)^{p}$, where $Z$ is the intensity ratio and $T$ the quantity of interest, is included. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.10856 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10856v1 Announce Type: cross Abstract: In discrete-variable black-box optimization, the number of candidate solutions grows combinatorially, while each evaluation is often expensive. Therefore, it is important to identify promising solutions efficiently within a limited number of trials. Bayesian Optimization of Combinatorial Structures (BOCS), an existing parametric method, works effectively when only a small amount of data is available. However, as the number of observations increases, BOCS tends to repeatedly propose points that have already been evaluated, which leads to search stagnation. A random-point addition strategy has been proposed to address this issue when an evaluated point is proposed, but it cannot sufficiently exploit information from promising data obtained so far. In this study, we propose a hybrid method that uses BOCS as the main search framework and generates alternative unevaluated points using a Gaussian process only when search stagnation is detected. In the Gaussian-process-based component, multiple Lower Confidence Bound (LCB) acquisition functions are adaptively selected to dynamically control the balance between exploitation and exploration. Numerical experiments using fully connected Quadratic Unconstrained Binary Optimization (QUBO) and Higher-order Unconstrained Binary Optimization (HUBO) as black-box functions show that the proposed method finds solutions with better objective values than the conventional random-point addition method in both settings. Additional analyses show that its effectiveness comes from selecting points that promote search progress within Hamming-distance neighborhoods, rather than simply adding low-energy points near promising solutions. Experiments with sparse surrogate models for quantum annealer applications further suggest the importance of retaining near-fully connected representational capacity. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.09927 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09927v1 Announce Type: cross Abstract: The rapid advancement of Large Language Models has transformed scientific research workflows, including enabling the automated extraction of data directly from published literature. Most existing efforts, however, focus on extracting simple labeled key-value entities, whereas many scientific applications require more complex, hierarchically structured data. A representative example is Quantum Cascade Lasers, whose device architectures are defined by tens of interdependent parameters organized in nested layer sequences. In this work we propose a \emph{JSON-Schema Guided Information Extraction Pipeline} (JSG-IE) that enables reliable extraction of deeply structured device data without model fine-tuning. By transforming extraction into a schema-constrained generation task, our approach significantly improves structural consistency and accuracy. Across 12 state-of-the-art LLMs, a properly designed JSON Schema improves performance by 5.7\% over conventional prompting, with the highest $F_1$ score up to 83.4\%, achieved by the reasoning-enabled Kimi-k2-thinking model. Importantly, this performance enhancement is most significant for mid-tier and open-source models, where $F_1$ gains reach as high as 24.1\%, effectively enabling these widely accessible models to achieve extraction fidelity previously restricted to much larger architectures. This framework provides a scalable path toward automated construction of high-fidelity device databases, accelerating data-driven optoelectronic design. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2605.09843 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09843v1 Announce Type: cross Abstract: We present a non-destructive, spatially resolved thickness characterization method for rhombohedral (3R) molybdenum disulfide (MoS$_2$) on polydimethylsiloxane (PDMS) substrates. Unlike broadband spectroscopic approaches, the proposed method reduces the measurement to a small number of discrete intensity images, enabling direct thickness mapping with a conventional microscope architecture and commercially available bandpass filters. Our approach combines a systematic framework for selecting optimal discrete wavelength samples of the material's reflectance with a robust thickness retrieval algorithm based on a multivariate Gaussian probability model. By sampling the reflectance with just five strategically chosen near-infrared bandpass filters, we demonstrate thickness characterization up to 691 nm with a mean 95% confidence-interval width of 8.3 nm. The method is adaptable to other van der Waals materials and conventional optical thin-film systems. It therefore provides a foundation for scalable, real-time thickness characterization in, e.g., dry-transfer fabrication workflows, where thickness screening remains a critical bottleneck for the production of van der Waals heterostructure devices. Physics/physics.data-an_(Data_Analysis,_Statistics_and_Probability) https://arxiv.org/abs/2507.11276 Tue, 12 May 2026 00:00:00 -0400 arXiv:2507.11276v3 Announce Type: replace-cross Abstract: Spatial entanglement of quantum states has become a central paradigm of many-body physics. Here, we unearth a fundamentally different form of entanglement, the entanglement between imaginary time scales. This time-scale entanglement is accessible through quantics tensor train diagnostics (QTTD), where the bond dimension of an $n$-particle correlator encodes the coupling between temporal scales. Our central result is that time-scale entanglement is generically enhanced in the vicinity of phase transitions and crossovers. At quantum critical points, it becomes scale-invariant. We demonstrate time-scale entanglement across a range of systems, including finite-size Hubbard rings, the transverse-field Ising model, the single-impurity Anderson model, and the Mott transition in the Hubbard model. Remarkably, the enhanced time-scale entanglement is largely independent of the specific observable, establishing QTTD as a universal and unbiased diagnostic of criticality. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2505.18511 Tue, 12 May 2026 00:00:00 -0400 arXiv:2505.18511v2 Announce Type: replace-cross Abstract: Stochastic Partial Differential Equations (SPDEs) driven by random noise play a central role in modeling physical processes with rough spatio-temporal dynamics, such as turbulence flows, superconductors, and quantum dynamics. Although machine learning (ML)-based surrogate models have shown promise for efficiently approximating such dynamics, progress remains limited by the lack of a unified benchmark with controlled data generation and comprehensive evaluation. This gap is particularly significant for singular SPDEs, for which benchmark datasets are largely unavailable and reliable simulation requires numerically delicate schemes based on renormalization. Moreover, subtle differences in data-generation procedures, such as noise approximation, basis choice, and the inclusion of renormalization, can significantly affect the resulting datasets and, consequently, model evaluation. We introduce SPDEBench, the first unified benchmark for ML-based SPDE learning. SPDEBench provides ready-to-use datasets for physically and mathematically significant SPDEs on 1-3D domains with periodic or Dirichlet boundary condition. Both regular and singular SPDEs are taken into consideration. SPDEBench also incorporates representative ML baselines in operator learning, together with 7 evaluation metrics, including Sobolev and distributional metrics beyond the standard $L^2$-error. Supported by SPDEBench, we conduct systematic evaluations of model accuracy, robustness, and out-of-distribution generalization under controlled data variations. Our numerical results show that SPDE-aware architectures generally achieve stronger performance than generic operator-learning baselines. These findings establish SPDEBench as a reproducible and extensible resource, paving pathway for principled benchmarking and architecture design for stochastic spatio-temporal dynamics. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2604.00149 Tue, 12 May 2026 00:00:00 -0400 arXiv:2604.00149v2 Announce Type: replace Abstract: While large language models (LLMs) promise to revolutionize automated scientific discovery, their application in rigorous real-world physical research is stalled by two critical barriers: a lack of realistic evaluation benchmarks and systemic LLM hallucinations. Here, we address both problems. We introduce QMP-Bench, a pioneering end-to-end research-level benchmark in quantum many-body simulation consisting of $100$ tasks extracted from $21$ high-impact prestigious journals, presenting a challenge even for current frontier LLMs. To establish a paradigm for reliable and transparent AI physicists, we present PhysVEC, a multi-agent framework that enforces self-verifiable and error correction in AI research. PhysVEC seamlessly integrates programming and scientific verifiers to guarantee coding correctness and principle-based physical validity, yielding interpretable evidence and error correction at each step. PhysVEC significantly outperforms existing LLM baselines on various scenarios in QMP-Bench and presents a favorable inference-time scaling, successfully transforming unreliable AI generations into accurate physical reproductions, paving a robust and trustworthy path towards future automated scientific discovery. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2512.03706 Tue, 12 May 2026 00:00:00 -0400 arXiv:2512.03706v2 Announce Type: replace Abstract: Coarse graining (CG) is an important task for efficient modeling and simulation of complex multi-scale systems, such as the conformational dynamics of biomolecules. This work presents a projection-based coarse-graining formalism for general underdamped Langevin dynamics. Following the Zwanzig projection approach, we derive a closed-form expression for the coarse grained dynamics. In addition, we show how the generator Extended Dynamic Mode Decomposition (gEDMD) method, which was developed in the context of Koopman operator methods, can be used to model the CG dynamics and evaluate its kinetic properties, such as transition timescales. Finally, we combine our approach with thermodynamic interpolation (TI), a generative approach to transform samples between thermodynamic conditions, to extend the scope of the approach across thermodynamic states without repeated numerical simulations. Using a two-dimensional model system, we demonstrate that the proposed method allows to accurately capture the thermodynamic and kinetic properties of the full-space model. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2506.12893 Tue, 12 May 2026 00:00:00 -0400 arXiv:2506.12893v4 Announce Type: replace Abstract: Cellulose nanocrystals (CNCs) are a type of cellulose with excellent mechanical performance and other merit attributes. According to previous reports, hydrogen bonds play a pivotal role in the anisotropic structure of the CNC. Understanding the structure and mechanical behavior of CNC on a mesoscopic scale is critical for the development and manufacture of cellulose materials. However, experimental observations and atomistic simulations are not appropriate on the mesoscopic scale. In this study, we introduce an analytical coarse-grained (CG) potential following an extended bottom-up approach that is directly parameterized using Reinforcement Learning (RL). RL is a powerful tool for industrial and academic applications in various fields. Nevertheless, the potential of RL has not yet been fully exploited in the field of molecular dynamics. The RL and Boltzmann inversion methods were employed to develop a novel CG model of cellulose to represent its anisotropy and polymer stiffness. The resultant CG model is not limited to the target properties for training, and can reproduce the dynamics mechanical properties under other circumstances without additional training. This model confirms that RL can construct a CG potential that is both physically explainable and powerful. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2308.13222 Tue, 12 May 2026 00:00:00 -0400 arXiv:2308.13222v3 Announce Type: replace Abstract: We introduce an evidence-driven Bayesian formulation of physics-informed neural networks that enables automatic optimization of loss weights between PDE residuals, boundary conditions, and observational data. Unlike existing Bayesian PINN approaches based on sampling or variational inference, the proposed method uses a Laplace approximation to compute model evidence analytically, enabling efficient hyperparameter tuning and model comparison without posterior sampling. We demonstrate the method on the heat, wave, and Burgers' equations, obtaining solutions in agreement with exact or reference results. In the Burgers' equation example, we further show that the framework naturally integrates information from governing equations and noisy measurements, providing predictive uncertainties within a unified Bayesian setting. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.10786 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10786v1 Announce Type: cross Abstract: We explore Krylov complexity in the BMN matrix model following a systematic reduction of it, known as the pulsating fuzzy sphere model. We present an analytical setup that allows us to calculate Lanczos coefficients in both large and small deformation limits of the matrix model. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.10465 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10465v1 Announce Type: cross Abstract: Reliable modeling and control of core density is essential for reactor-relevant magnetic confinement fusion operation, motivating cryogenic pellet injection as a primary fueling actuator and the need for predictive pellet source models in integrated modeling. Here we present an upgrade of the physics-based pellet code HPI2 in which the plasmoid release spatial step is determined self-consistently from ablation physics, $dx_{var}=v_{\mathrm{pel}}\,t_{\mathrm{exit}}$ (optionally rescaled to trade accuracy for computational cost), removing an ad-hoc discretization parameter and improving numerical robustness across injection conditions. The upgraded model is first validated in stand-alone against a high-field-side pellet-fueled, ohmic, WEST discharge (#58656) by comparing synthetic and measured interferometry line-integrated density increments, obtaining a mean error of $\sim 10\%$. We then perform full-radius, time-dependent integrated modeling validation by coupling the new HPI2 within the High Fidelity Pulse Simulator (HFPS) workflow (JINTRAC/IMAS), combining JETTO with SANCO for the impurity/radiation evolution and TGLF-SAT2 for the turbulent transport. The coupled simulations reproduce the main density rise and relaxation after pellet injection and the associated electron-temperature transient, while taking into account the strong influence of tungsten radiation in WEST, supporting the consistency of HPI2 as a predictive pellet particle source in integrated modeling frameworks. Ultimately, this validation study supports the use of pellet modeling tools in integrated modeling studies for larger devices such as ITER. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.10159 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10159v1 Announce Type: cross Abstract: jNO (jax Neural Operators) is a JAX-native library for neural operators and foundation models with unified support for both data-driven and physics-informed training. Its core design is a tracing system in which domains, model calls, residuals, supervised losses, and diagnostics are written in one symbolic language and compiled into one optimization pipeline. This allows users to move between operator regression, mesh-aware residual evaluation, and PDE-constrained training without restructuring the surrounding code. jNO also supports multi-model compositions, fine-grained control at parameter level (model, optimizer, and learning rate), hyperparameter tuning, and JAX-native workflows for translated PDE foundation-model families. The source repository is available at https://github.com/FhG-IISB/jNO. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.09720 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09720v1 Announce Type: cross Abstract: This paper expands on the TRANSP description given in Computer Physics Communications 312 (2025) 109611 by describing recent progress in TRANSP's predictive functionality and emphasizing the development of the PT_SOLVER module and integration of the high-fidelity T3D/GX framework for plasma profile prediction using a high-fidelity gyrokinetic model for turbulent transport. PT_SOLVER is a modular, multi-region, parallel solver for coupled transport equations of particle density, electron and ion energy, and toroidal angular momentum that uses an implicit Newton method to advance the solution of these equations. The numerical formulation includes source coupling, moving-geometry terms, and nonlinear stabilization based on modified Peclet numbers, thereby enabling the PT_SOLVER to handle the stiffness associated with gradient-dependent transport models. Stabilization occurs via a nonlinear function controlling discretization in zones of steep gradients or rapidly changing transport coefficients. Source terms that account for heating, current drive, alpha-particle effects, and collisional energy exchange are handled thoroughly, and both residual norms and profile-change measures are used to assess convergence. Verification is carried out using analytical benchmark solutions, manufactured solution benchmarks, convergence studies of stiff gradient-dependent diffusivities, and code-to-code comparisons of TGYRO using the TGLF/NEO models for anomalous and neoclassical transport. This paper also describes the TRANSP Interface to the modular T3D/GX workflow and presents verification examples related to the interface for coupled prediction simulations. The results in this paper confirm that the predictive TRANSP framework has a robust numerical implementation for time-dependent predictive transport simulations, and it provides a basis for future hybrid reduced and high-fidelity workflows. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.09470 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09470v1 Announce Type: cross Abstract: We present a systematic accuracy assessment of the thin-element approximation (TEA), the beam propagation method (BPM), and the wave propagation method (WPM) for binary diffractive gratings, using the rigorous Fourier modal method (FMM) as a reference. Random binary gratings are generated over a range of spatial frequency cutoffs and thicknesses, and the transmitted field overlap between each scalar method and the reference is measured. The results are summarized as accuracy maps in the spatial frequency-thickness parameter space, revealing the domain of validity of each method and providing practical guidelines for the choice of forward model in diffractive optics inverse design pipelines. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.09097 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09097v1 Announce Type: cross Abstract: We propose an overlapping Schwarz space-time refinement framework for the material point method (OS-MPM) to improve computational efficiency in problems with strongly localized deformation, contact, and large geometric nonlinearity. The method decomposes the domain into overlapping coarse and fine subdomains with heterogeneous spatial and temporal resolutions, while retaining standard MPM discretizations within each subdomain. Coarse-fine coupling is achieved through an MPM-specific Schwarz iteration combining mass-weighted spatial transmission and temporal interpolation for sub-cycling. In contrast to refinement strategies based on modified basis functions, transition kernels, or strongly enforced interface constraints, the proposed approach preserves the modular structure of standard MPM and shifts the coupling complexity to nonmatching-grid interface operators within the Schwarz alternating procedure. Numerical examples, including a gravity-driven cantilever beam, Hertzian contact, and an elastic inclusion problem, show that the method reproduces analytical or fine-resolution reference solutions with good accuracy and convergence behavior. In the inclusion benchmark, the proposed framework achieves comparable or slightly lower error than single-domain fine simulations at the finest tested resolutions, while reducing computational cost by up to 9.15 times. A three-dimensional folding example further demonstrates the generality of the framework. These results indicate that the proposed method provides an accurate, modular, and efficient route for local space-time refinement in MPM. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.08436 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08436v1 Announce Type: cross Abstract: We introduce a meshfree exterior calculus (MEEC) for learning structure-preserving descriptions of physics on point clouds, and use it to build MEEC-Net, a data-efficient surrogate that transfers across resolutions, geometries, and physical parameters. MEEC equips an $\varepsilon$-ball graph with virtual node and edge measures via a single sparse Schur complement solve; the resulting complex satisfies discrete conservation exactly, is end-to-end differentiable in the point positions, and exposes a direct geometry-to-physics link without the mesh-generation step required by conventional structure-preserving discretizations. MEEC-Net learns unknown physics as a shared edge-wise flux law in an SO($d$)-invariant local frame, so the same kernel produces compatible fluxes on any point cloud whose features lie in the training range. We prove a solution-error bound that splits into discretization and kernel-approximation terms which is independent of problem geometry, explaining the observed transfer from very few examples. We show that single-solution training transfers to unseen geometries, boundary conditions, and physical parameters. On five canonical PDE benchmarks MEEC-Net achieves 1-2 orders of magnitude lower out-of-distribution error than baseline neural-operator approaches. On the SimJEB structural-bracket benchmark it achieves competitive error while using substantially fewer training geometries. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.08318 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08318v1 Announce Type: cross Abstract: We study the problem of \emph{architecture selection} for deep learning models trained to solve partial differential equations (PDEs), asking when transformer-based architectures with learned attention outperform Fourier-domain neural operators. We introduce the \textbf{Multi-Scale Attention Transformer} (\msat{}), a deep learning architecture that encodes spatiotemporal solution histories as token sequences and trains end-to-end via a composite supervised objective with optional physics-informed regularization terms. We conduct a comprehensive empirical evaluation against nine baselines -- including physics-informed neural networks (PINNs), neural operators (FNO, DeepONet, GNOT), and state-space models (Mamba-NO) -- across five benchmark problems from the PINNacle suite, using identical train/test splits and reference data for all methods. \msat{} achieves state-of-the-art generalization on complex geometry problems ($L^2_\mathrm{rel} = 0.0101$ on Heat2D-CG, a $3.7\times$ improvement over FNO) at $34\,\mathrm{s}$ total inference vs.\ $120{,}812\,\mathrm{s}$ for Mamba-NO. Ablation studies over the physics regularization component reveal a precise inductive bias tradeoff: physics priors reduce test error on diffusion-dominated problems but degrade generalization on chaotic and recirculating-flow regimes, directly characterizing the prior misspecification boundary. Approximation error bounds as a function of domain boundary complexity $\kappa$ provide a theoretical basis for these empirical findings and a principled rule for architecture selection. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.08232 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08232v1 Announce Type: cross Abstract: High-fidelity experimental characterization of turbulent premixed flames remains limited by the cost and complexity of advanced diagnostics, particularly under elevated pressures and intense turbulence where measurements of coupled flame morphology and burning dynamics are sparse. Here, we develop a hierarchical multi-fidelity neural network framework (MuFiNNs) to address this challenge by integrating sparse high-fidelity experimental data with structured low-fidelity representations encoding dominant physical trends. The framework combines hierarchical low-fidelity construction with nonlinear multi-fidelity correction to learn coupled geometric and reactive flame behavior while recovering discrepancies that simplified models alone cannot capture. The methodology is applied to expanding turbulent premixed flames to predict three-dimensional flame wrinkling dynamics and turbulent mass burning velocity across varying fuels, pressures, and turbulence intensities. Using experimentally informed low-fidelity trend models with sparse high-fidelity measurements, MuFiNNs accurately reconstruct observed flame behavior, enable interpolation across unseen operating conditions, and demonstrate robust extrapolation beyond the training domain. Importantly, the framework remains effective in noisy, weakly structured, or experimentally inaccessible regimes where conventional data-driven approaches often fail. These results show that hierarchical multi-fidelity learning provides a scalable and physically grounded strategy for predictive combustion modeling in data-limited regimes. More broadly, this work establishes multi-fidelity scientific machine learning as a practical framework for extracting physically meaningful predictive models from sparse experiments, particularly for instability-dominated and turbulence-sensitive reactive flows where high-fidelity data acquisition is demanding. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.10028 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10028v1 Announce Type: new Abstract: Manifold-based combustion models decrease the cost of turbulent combustion simulations by projecting the thermochemical state onto a lower-dimensional manifold, allowing the thermochemical state to be computed separately from the flow solver. The solutions to the manifold equations have traditionally been precomputed and pretabulated, but this results in large memory requirements and significant precomputation cost even for simple models. One approach to alleviate the memory requirements is to use In-Situ Adaptive Manifolds (ISAM), which only stores solutions that are encountered during a simulation in a database built with In-Situ Adaptive Tabulation (ISAT). Even with ISAM, as the manifold complexity increases, the memory requirements can still grow too large. Another approach to reduce memory of these databases are machine learning methods, for they represent functions in a highly memory-compact manner. However, current implementations of these methods require the pregeneration of training datasets with little knowledge of the states present in a simulation. This work develops the Neural In-Situ Adaptive Manifolds (Neural-ISAM) method, which is designed to address the drawbacks of both adaptive tabulation and machine learning methods, and leverage their benefits by coupling neural networks to manifold databases on-the-fly. ISAM databases are built via ISAT, which stores the manifold solutions in a binary tree, and Neural-ISAM periodically searches this tree to identify regions that can be pruned. Neural networks are trained on the candidate regions, and these portions of the binary tree are then replaced by the trained neural network, reducing the memory requirements of the database. Neural-ISAM memory usage, computational performance, and accuracy is evaluated in LES of two turbulent flames with increasing manifold model complexity: Sandia Flame D and the Sandia Sooting flame. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.09307 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09307v1 Announce Type: new Abstract: This work introduces an end-to-end framework for inverse design of elastic networks directly in the space of constitutive behaviors. A constitutive prior is constructed from noisy stress-strain data using a latent representation that defines a manifold of admissible material laws while enforcing thermodynamic consistency. The inverse problem is formulated as a PDE-constrained optimization problem over latent constitutive variables that parameterize spatially varying material behavior. To improve robustness in the resulting nonconvex optimization, a homotopy-based continuation strategy is introduced using intermediate target point clouds generated through affine registration. Geometry matching is performed using the Chamfer distance, enabling optimization without requiring mesh correspondence between the target and reference configurations. To account for manufacturing constraints limiting abrupt spatial variation in material properties, the framework additionally incorporates a neural-network-based smoothness prior together with a graph-based smoothness metric. The proposed approach is demonstrated on several inverse design problems for elastic networks and compared against alternative optimization strategies. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.09058 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09058v1 Announce Type: new Abstract: We introduce Nonlinear GENERIC Informed Neural Networks (N-GINNs), a deep learning framework for discovering evolution equations of systems governed by the nonlinear GENERIC formalism (General Equation for Non-Equilibrium Reversible-Irreversible Coupling). Such systems exhibit coupled conservative and dissipative dynamics, and can be described via the superposition of a Hamiltonian flow and a generalized gradient flow. In contrast to existing approaches, our formulation incorporates generalized gradient flows via convex dissipation potentials, enabling the identification of a broader class of thermodynamically consistent dynamics, including systems with non-quadratic dissipation potentials. Thermodynamic structure is strongly enforced by construction through suitable reparameterizations of both the bivector operator and the dissipation potential, ensuring exact compliance with the first and second laws of thermodynamics. We validate the proposed approach on three representative examples: a harmonic oscillator coupled to a heat bath, an idealized chemical motor, and a one-dimensional viscoplastic model of Perzyna type. These results demonstrate the method's ability to accurately infer thermodynamically consistent models from data for systems incorporating both conservative and nonlinear dissipative dynamics. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2605.08105 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08105v1 Announce Type: new Abstract: In wall-modelled large-eddy simulations of hypersonic boundary-layer transition, Hoffmann, Chamarthi and Frankel reported that characteristic reconstruction based on conservative-variable eigenvectors produced markedly better results than the corresponding primitive-variable implementation. The observation was empirical. A subsequent wave-appropriate conservative reconstruction (WA-CR) algorithm used a rank-one entropy correction based on the premise that contact-discontinuity error lies in a single conservative entropy/contact direction. This note gives the algebraic foundation for both observations. For the standard conservative curvilinear eigenvectors, the density row of the right-eigenvector matrix contains exact, metric-free zeros in the shear columns, so shear waves carry no density perturbation and a contact discontinuity is represented by the conservative entropy eigenvector alone. The conservative left eigenvectors provide the dual projection property: the entropy amplitude is obtained with a metric-independent left eigenvector and has unit contact scaling, while total-energy perturbations have zero projection onto the shear amplitudes. In the standard primitive curvilinear eigenvectors, by contrast, shear right eigenvectors contain metric-dependent density components and the primitive entropy left eigenvector contains metric-weighted tangential-velocity terms. Thus the conservative formulation supplies the two algebraic requirements for an exact, sufficient, metric-invariant, rank-one entropy correction: metric-independent entropy projection and a metric-independent entropy update direction. Curvilinear metrics make the distinction explicit, but the conservative state-space contact direction is already the natural direction underlying WA-CR even on Cartesian grids. Physics/physics.comp-ph_(Computational_Physics) https://arxiv.org/abs/2603.04574 Tue, 12 May 2026 00:00:00 -0400 arXiv:2603.04574v2 Announce Type: replace-cross Abstract: A monograph on the mathematical aspects of Special Relativity, focusing on the Lorentz group and the properties of relativistic transformations in mechanics and electrodynamics. Manuscript of published book, with added appendices. Physics/physics.class-ph_(Classical_Physics) https://arxiv.org/abs/2602.02281 Tue, 12 May 2026 00:00:00 -0400 arXiv:2602.02281v2 Announce Type: replace-cross Abstract: Backpropagation is typically presented as a symbolic procedure: a backward pass topologically distinct from inference, with non-local error signals and synchronous global clocking, features with no clear analog in physical reality. Existing physics-inspired alternatives recover gradients only approximately, in vanishing-perturbation limits, or under weight-symmetry constraints incompatible with feedforward architectures. In this paper, we address this gap by deriving exact backpropagation from Hamilton's least-action principle. By recasting the forward dynamics in continuous time and adapting a Lagrangian formalism for non-conservative systems to the resulting flow, we unify inference and gradient computation within a single variational framework on a doubled phase space, whose two conjugate fields jointly encode activations and sensitivities. A single global Lagrangian governs the dynamics: the task loss enters as a symmetry-breaking perturbation of the forward manifold, and credit assignment emerges as the tension that develops between the conjugate states. Inference and gradient computation thus unfold simultaneously through local interactions, requiring no separate backward circuit. Ultimately, standard backpropagation is recovered exactly as the discrete-time projection of this continuous flow. This perspective unifies the formalism of physics with backpropagation, opening a principled pathway for applying tools from classical mechanics - symplectic geometry, Noether's theorem, path-integral methods - to the analysis of learning dynamics. As a downstream consequence, it also points toward analog and neuromorphic substrates in which learning is embodied in the hardware itself. Physics/physics.class-ph_(Classical_Physics) https://arxiv.org/abs/2507.05095 Tue, 12 May 2026 00:00:00 -0400 arXiv:2507.05095v2 Announce Type: replace-cross Abstract: The bulk-boundary correspondence, which relates topological properties of a material in the bulk to the presence of robust modes localized on the edge, is at the core of the now mature field of topological wave physics. More recently, it was realized that in crystalline structures, certain types of defects can host localized modes, in which case the bulk-boundary correspondence has to be replaced by a bulk-defect correspondence. These defect-localized modes are expected to have robust properties owing to their topological origin. In this work, we show how to obtain topological defect modes in a lattice possessing both mirror and chiral symmetry. The defect is obtained by endowing a plaquette with a non-trivial gauge flux. We show that the bulk-defect correspondence is satisfied by introducing appropriate topological invariants. Moreover, the topological defect modes are shown to be highly robust to the introduction of symmetry-preserving disorder. The model is then realized in an acoustic system made of a bilayer network of tubes, and the presence of topological defect modes is experimentally clearly demonstrated. Physics/physics.class-ph_(Classical_Physics) https://arxiv.org/abs/2604.22717 Tue, 12 May 2026 00:00:00 -0400 arXiv:2604.22717v2 Announce Type: replace Abstract: The Hahn-Banach Theorem, a cornerstone of modern functional analysis, is a natural companion of the Second Law of Thermodynamics. From a Kelvin-Planck version of the Second Law, the Hahn-Banach Theorem delivers, immediately and simultaneously, entropy and thermodynamic-temperature functions of the local material state such that the Clausius-Duhem inequality is satisfied for every process a particular material might admit. For \emph{existence} of such functions there is no need at all to require that their domain be restricted to states of equilibrium. However, the Hahn-Banach Theorem also indicates that for \emph{uniqueness} of such a pair of functions across the entire state-space domain, every state must be visited by a reversible process. This review is intended to help make accessible to both thermodynamics scholars and mathematicians the remarkable interplay of the Hahn-Banach Theorem and the Second Law. Physics/physics.class-ph_(Classical_Physics) https://arxiv.org/abs/2601.09761 Tue, 12 May 2026 00:00:00 -0400 arXiv:2601.09761v2 Announce Type: replace Abstract: It is shown that equations describing the Galilean electromagnetism in the presence of sources hold invariant under the l-conformal Galilei group for an arbitrary (half)integer parameter l. The group contains transformations which link an inertial frame of reference to those moving with constant accelerations of order up to 2l-1, thus pointing at potential dynamical instability. Physics/physics.class-ph_(Classical_Physics) https://arxiv.org/abs/2507.02736 Tue, 12 May 2026 00:00:00 -0400 arXiv:2507.02736v2 Announce Type: replace Abstract: We present a pedagogical introduction to Floquet-Magnus theory through the classical example of Kapitza's pendulum - a simple system exhibiting nontrivial dynamical stabilization under rapid periodic driving. By deriving the equations of motion and analyzing the system using Floquet theory and the Magnus expansion, we obtain analytical stability conditions and effective evolution equations. While grounded in classical mechanics, the techniques are directly applicable to periodically driven quantum systems as well. The approach is fully analytical, using only tools from theoretical mechanics, linear algebra, and ordinary differential equations, and is suitable for instruction at the advanced undergraduate or graduate level. Physics/physics.class-ph_(Classical_Physics) https://arxiv.org/abs/2605.10458 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10458v1 Announce Type: cross Abstract: Atomic properties such as partial charges or multipoles encode chemically meaningful information that can inform downstream molecular property prediction, but their evaluation as machine learning targets has been complicated by the absence of a principled out-of-distribution evaluation protocol at the atomic level. In this work, we propose a held-out evaluation protocol that clusters atomic environments by SOAP descriptors and computes metrics accounting only for cluster labels unseen during training. Following this procedure, we use 5$\times$5 cross-validation and Tukey's HSD to run a statistically rigorous comparison of E(3)-equivariant against non-equivariant, rotationally augmented models for predicting electron populations and multipoles of H, C, N, and O atoms. Building on our results, we introduce the Quantum Topological Neural Network (QT-Net), a rotationally augmented, non-equivariant graph neural network. We show that QT-Net can be used to infer properties of atoms in molecules from QM9 outside our training set, and that these inferred properties can yield improvement when used as input features for downstream molecular property prediction. To further validate the framework, molecular dipole moments computed from QT-Net's per-atom outputs recover the ground-truth values reported in QM9. We release all code and data, including a JAX implementation of QT-Net, to support the broader use of learned QTA properties as inductive biases for atomic-scale molecular machine learning. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.08675 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08675v1 Announce Type: cross Abstract: We present OBDF-SQD, a hybrid quantum-classical method that combines one-body downfolding~(OBDF) based on one-body M\o{}ller--Plesset second-order perturbation theory (OBMP2) with sample-based quantum diagonalization~(SQD) for use in quantum-centric supercomputing~(QCS). In this approach, OBMP2 is executed classically to fold dynamical correlation from external orbitals into a renormalized one-body operator, yielding an effective active-space Hamiltonian that retains the same operator structure as the bare Hamiltonian and therefore requires no additional quantum circuit resources. SQD is then applied to this effective Hamiltonian, where, in this work, the quantum sampling is performed via the Qiskit Aer simulator rather than actual quantum hardware. We benchmark OBDF-SQD on dissociation curves of \ce{H6} chain, ring, and lattice systems and the \ce{N2} molecule in the cc-pVDZ basis, comparing against standard methods and active-space SQD (CAS-SQD). We observed that OBDF-SQD consistently improves upon CAS-SQD with the same active space. The simplicity of the one-body downfolding correction also makes the approach straightforwardly extensible to periodic solids within existing quantum embedding frameworks Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10838 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10838v1 Announce Type: new Abstract: Null points in synthetically tunable molecular aggregates are predicted to generate flat energy bands analogous to those known in strongly correlated condensed-matter physics. For chemistry, null points provide a powerful design principle for photovoltaic materials with selective charge filtering similar to photosynthesis. However, null points have never been experimentally verified because their defining prediction - state localization with selective electron or hole transfer - has remained unobserved. Here, using a donor-acceptor dyad as a minimal model, we provide the first experimental observation of a null point. Impulsive pump-probe measurements reveal charge separation through a near-instantaneously generated locally excited-charge transfer (LE-CT) intermediate that emerges upon solvent stabilization of CT states. Polarization anisotropy directly reveals state localization and selective charge-filtering, spanning balanced electron-hole transfer to selective hole filtering consistent with synthetic design. A generalized vibronic theory of null points explains these observations and identifies the ideal synthetic parameters for achieving null points which are protected from the vibrational bath. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10429 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10429v1 Announce Type: new Abstract: Nuclear magnetic resonance (NMR) spectroscopy provides an experimental readout of local chemical environments, but its use in molecular representation learning has been constrained by heterogeneous data and incomplete atom-level assignments. Here we construct complementary high-fidelity experimental and computational 13C NMR resources, which reveal a recurrent form of representational collapse: atoms that are equivalent in molecular topology can remain experimentally distinct in their real chemical environments, whereas explicit 3D descriptions are further limited by static conformations in dynamic regimes. To alleviate this bottleneck, we develop CLAIM (Contrastive Learning for Atom-to-molecule Inference of Molecular NMR), a framework that aligns efficient topological molecular inputs with atom-resolved NMR observables. Through hierarchical chemical priors and cross-level contrastive learning, CLAIM restores lost chemical resolution and markedly improves atom-level molecule-spectrum retrieval. CLAIM remains robust in flexible and tautomeric systems for 13C NMR prediction, improves stereoisomer discrimination without explicit 3D modelling, and transfers to broader molecular property tasks including ADMET prediction and fluorescence estimation. These results establish physically grounded spectral alignment as an effective strategy for alleviating chemical-environment collapse and for guiding experimentally grounded molecular representation learning. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10348 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10348v1 Announce Type: new Abstract: The accurate description of electron correlation is a central challenge in computational chemistry, with selected configuration interaction (SCI) emerging as a powerful tool to approach the full CI limit. While recent machine learning (ML) integrations have accelerated determinant selection, existing regression and classification approaches suffer from a fundamental objective-loss mismatch: they evaluate the importance of determinants in isolation without explicitly accounting for their relative importance ranking. Here, we introduce ranking configuration interaction (RCI), a novel ML-supported SCI framework that reframes determinant selection as a pairwise ranking problem. Building upon a Transformer-based architecture to capture complex, non-local orbital dependencies, RCI progressively optimizes the partial ordering of determinants. By doing so, RCI aligns the training objective more closely with the intrinsic ranking nature of SCI. Extensive benchmarks across both plane-wave and Gaussian basis sets, including the molecules N$_2$, CO, H$_2$O, NH$_3$, and C$_2$, demonstrate the substantial efficiency of RCI. Compared to previously reported classification baselines, RCI consistently accelerates convergence-reducing overall computational time by 23% to over 50% depending on the system, and requiring only 55% of the determinant count in representative cases such as N$_2$ and CO. Furthermore, RCI exhibits robust performance and reaches chemical accuracy on the highly challenging iron-sulfur using only 12% of the full CI space. Notably, RCI outperforms recent regression-based SCI methods by delivering either further 15% improvement in accuracy at comparable determinant counts, or 15% gain in compactness at similar accuracy. This pairwise learning-to-rank model provides a lightweight and modular plugin that can be seamlessly incorporated into other supervised-learning frameworks. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10331 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10331v1 Announce Type: new Abstract: We study a simple but useful test for neural exchange-correlation (XC) functionals: can a neural model reproduce an established XC functional when it is used self-consistently? We call this test functional cloning. The model is trained at the GGA level to reproduce a known semilocal functional, using either a constrained or an unconstrained architecture. The motivation is that an XC functional is not used on a fixed input. In a Kohn-Sham self-consistent-field calculation it contributes to the potential, and the resulting density is part of the outcome of the same calculation. A good pointwise fit to sampled density descriptors is therefore not by itself enough. Because the target functional is known, the error can be measured directly. We compare the clones on sampled descriptors, molecular total energies, energy differences, transfer between PySCF and SIESTA, and equations of state for crystalline solids. The constrained models reproduce the reference functional more accurately in molecular self-consistent calculations. They also give better initial parameters for later optimization against correlated molecular energies. An additional observation is that the constrained architecture already gives a reasonable solid-state baseline before cloning, as seen from randomly initialized constrained models. Clones trained only on molecular densities transfer well to solids, reproducing reference lattice constants and bulk moduli across metallic, covalent, ionic, oxide, and layered systems. Cross-code tests show that energy differences are relatively robust, while total energies depend strongly on whether the cloning descriptors come from all-electron or pseudopotential densities. These results make functional cloning a useful diagnostic before full self-consistent training of neural XC functionals. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10266 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10266v1 Announce Type: new Abstract: In density functional theory, simpler exchange-correlation (XC) approximations such as the local density approximation (LDA) are favored for computational speed but rely on limited information, leading to a trade-off between accuracy and generality. Machine-learned XC approximations have seen a lot of interest to address this problem. Here, we train a neural network LDA using a differentiable Kohn-Sham solver, imparting system-specific expertise for water and sacrificing generality for accuracy. Our model achieves 1 kcal / mol errors on gold standard coupled cluster ionization and atomization energies, and improves predictions of spectral lines, electron density distribution, and equilibrium geometry from as few as eight configurations used for training. We proceed to perform transfer learning and obtain results comparable to higher-rung PBE and B3LYP functionals on the WATER27 subset of the GMTKN55 database, even when only a single two-molecule binding energy is used in the transfer process. This result opens the door for specialist functionals to be trained on different systems from little data, enhancing predictions while maintaining low training costs. Our approach of training a modified XC density functional approximation (DFA) furthermore allows for a highly interpretable result, as the neural network directly corresponds to a correction of the XC energy per electron. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.10209 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10209v1 Announce Type: new Abstract: The nuclear Schiff interaction (NSI) arises from a nuclear force that simultaneously violates spatial parity (P) and time reversal (T) symmetries, where T symmetry is equivalent to CP symmetry under CPT invariance. Detecting the NSI experimentally is important because CP violation is critical for explaining why the amount of matter in the Universe is far greater than that of antimatter. Measuring the NSI in molecules requires both precise experiments and theoretical calculations that incorporate electronic and nuclear wavefunctions. Conventionally, the electronic terms have been approximated using a first-order power series expansion of the electronic radial function-an approach that yields the well-known nuclear Schiff moment (NSM) -but this approximation may not be sufficiently accurate. In this study, we introduce a new, accurate analytical expression for the electronic terms based on Gaussian basis sets, which avoids any truncation of the power series. We find that the previous numerical approach overestimates the values for RaO and LrF by more than 50% and 300%, respectively, in the nuclear-radius region. In contrast to the numerical calculations, the analytical expression-based calculations show less sensitivity to choice of the basis-functions. Furthermore, we develop a new basis set that describes accurate behavior of wave functions both interior and exterior regions of nucleus. It also demonstrates that an even-tempered basis set is more preferrable over energy optimized basis set for calculating the NSI electronic term in molecules. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.09978 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09978v1 Announce Type: new Abstract: We study steady-state resonance light scattering from ensembles of noninteracting molecules, both in free space and inside optical cavities, while accounting for local thermal relaxation. The scattering spectra are obtained from steady-state solutions of either the Schr\"{o}dinger equation or a Liouville-space master equation. In the absence of a cavity, the spectra exhibit an elastic peak at the incident-photon energy and an inelastic fluorescence peak near the molecular excitation energy. Inside a cavity, the fluorescence peak splits into upper- and lower-polaritonic peaks in the strong-coupling regime. We analyze how the elastic and inelastic spectral features scale with the number of molecules under fixed cavity-molecule coupling and identify distinct collective trends in the Rayleigh peak intensity and in the integrated polaritonic or fluorescence spectral weight. The two theoretical approaches yield qualitatively consistent results while highlighting different aspects of thermally induced relaxation and dephasing. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.09752 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09752v1 Announce Type: new Abstract: A general polarizable embedded (PE) quantum mechanics/molecular mechanics scheme for periodic systems is presented, describing mutual polarization of the two subsystems. The QM system, described with density functional theory (DFT), is coupled to a single center multipole expansion (SCME) model, characterising H$_2$O molecules in the MM region. In SCME the H$_2$O molecules are ascribed anisotropic dipole and quadrupole polarizabilities and permanent multipoles up to and including the hexadecapole. Our embedding scheme illustrates a smooth and efficient convergence pattern of the periodic interaction potential by introducing a single and clustered multipole expansion points in the far-field. By choosing the near- and far-field expansion of the potential carefully the PE-QM/MM calculation matches the level of accuracy of a the QM calculation. In the short range, the electrostatic interaction between the QM and MM subsystems is damped with a real-space and pair-wise isotropic damping functions - resulting in a screened interaction and preventing over-polarization. In molecular dynamics simulations the two subsystems are separated with the elastic scattering assisted flexible inner region [Kirchhoff et. al. JCTC, 2021, 17, 9, 5863] - ensuring a smooth transition in the radial distribution at the boundary between the two subsystems. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.09495 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09495v1 Announce Type: new Abstract: Machine learning-based simulators offer the potential to model the dynamics of complex systems more efficiently than classical approaches, while retaining differentiability, a key property for materials design. Graph neural network (GNN)-based simulators have shown strong performance across a range of physical domains, including molecular dynamics. However, their reliance on temporal context for accurate prediction limits their use in inverse design settings, where simulations must be initialized from a single static configuration. Moreover, inverse design requires robust out-of-distribution (OOD) generalization, as candidate structures typically lie outside the training domain. Here, we address both challenges by introducing two complementary strategies that enable stable and accurate structure-only initialization of GNN-based simulations. To directly target OOD generalization, we propose an inference-time physics-based optimization framework that constrains model predictions to remain physically consistent during rollout. In addition, we introduce a differentiable, GNN-based barostat that enables accurate tracking of system dimensions and pressure, critical for capturing macroscopic responses and supporting OOD generalization. We evaluate these approaches in the context of uniaxial compression of disordered elastic networks spanning a broad range of geometries, Poisson ratios, and microscopic behaviors. We find that, together, these methods substantially improve rollout stability and enable reliable OOD generalization, including regimes with distinct, more complex dynamics than those in the training data. These results show that, when properly initialized and constrained, GNN-based simulators can serve as efficient and generalizable tools for materials discovery and structural optimization, advancing their use in materials, molecular, and dynamical system design. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.09394 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09394v1 Announce Type: new Abstract: Once trained, machine-learned interatomic potentials (MLIPs) provide a fast and accurate way to study catalytic reaction pathways, but their performance strongly depends on the training set. Here, we compare nine MLIPs trained with different data sets and strategies, including from-scratch (FS) training and fine-tuning (FT) of large foundation models. The models are evaluated on reaction energies, $E_{r}$, and reaction energy barriers, $E_{a}$, for 141 reactions, including CO$_2$ reduction to C$_2$ and C$_3$ products, propane dehydrogenation, hydrogen intercalation on Pd, and out-of-distribution oxygen evolution reaction (OER) on metal oxides. FS models trained with 5%--10% perturbed high-energy configurations from molecular dynamics or contour exploration reduce the error by more than twofold compared with models trained only on relaxation trajectories. In contrast, FT MLIPs are less sensitive to sampling and transfer well to out-of-distribution reactions. An MLIP fine-tuned on metallic catalysts achieves a 0.30 eV MAE for OER on iridium oxide polymorphs, outperforming out-of-the-box MACE-MH-1 by 0.08 eV and the best FS model by 0.14 eV. A model fine-tuned to O and OH adsorption on metal oxides gives a 0.19 eV reaction-barrier MAE for out-of-distribution CO$_2$RR on Cu, comparable to an FS model trained on in-distribution C--C bond-breaking reactions. Finally, a large MLIP fine-tuned on 49,860 configurations gives the best overall performance across metallic and metal-oxide catalysts and was used to screen a large left-out set of bimetallic alloys, achieving a 0.15 eV MAE for $E_{r}$, even for adsorbates on unseen Miller-index surfaces such as (532). This work identifies the training configurations needed for accurate FS and FT MLIPs for catalytic reaction modeling. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.08994 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08994v1 Announce Type: new Abstract: The current catalyst discovery and development pipeline for energy-intensive applications like methane conversion remains bottlenecked by expensive trial-and-error experimentation, irreproducible chemical intuition, and a lack of frameworks linking complex catalytic design spaces to performance. This work presents an interpretable machine learning framework that integrates SHAP-based feature importance analysis (Explainable AI) with tree-based ensembles (Random Forest and Bayesian-optimized CatBoost) to characterize Fe-zeolite and oxide-supported catalysts for the partial oxidation of methane (POM). Despite limited data, the framework decodes complex structure-performance relationships by identifying and ranking thermodynamic, structural, and geometric microdescriptors that influence the electronic band gap and govern macroscale performance metrics such as selectivity, activity, and stability. This work explicitly demonstrates that thermodynamic lattice stability and geometric factors are the primary drivers of electronic band gap (a critical proxy for redox reactivity) rather than bulk stoichiometry. Non-linear models achieve an R2 of 0.61 - 0.77, significantly outperforming traditional linear baselines (R2 = 0.32). This workflow provides both a light-weight generalizable methodology and a prioritized list of physical features for accelerated catalyst screening - and these features can subsequently be integrated into microkinetic and reaction engineering models to create digital twins of complex reactor systems and to enable predictive optimization in autonomous R&D laboratories. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.08708 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08708v1 Announce Type: new Abstract: The homogeneous spectral linewidth associated with light-matter interactions is a fundamental descriptor of the optical properties of materials, governed by the quantum dynamics of the condensed-matter system. We discuss here that the homogeneous linewidth measured by means of two-dimensional electronic spectroscopy depends not only on microscopic coherence loss, but also on the observable through which the nonequilibrium dynamics are projected onto the measurement. In this Perspective, we develop a unified framework showing that changing the detection operator changes the operational definition of dephasing. For coherent emitted-field measurements, the observed linewidth largely retains its conventional connection to the optical coherence time $(T_2$). By contrast, in population-detected modalities such as photoluminescence-, photocurrent-, and other action-detected two-dimensional spectroscopies, the apparent linewidth can additionally encode excited-state population redistribution dynamics, leading naturally to an effective coherence time \(T_{2,\mathrm{eff}}\). Using a coupled-mode model propagated under a common Liouvillian, we show that identical microscopic dynamics yield distinct apparent dephasing times when projected onto coherent-emission and population-derived observables. We posit that the detection observable is not merely how a two-dimensional spectrum is measured, but part of what the spectrum fundamentally means as a materials probe. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.08691 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08691v1 Announce Type: new Abstract: Recent real-time TDDFT calculations have reported an unexpected delayed growth of molecular dipole oscillations some time after an extreme-ultraviolet (XUV) pulse is applied. We show that numerical and analytical arguments suggest that this instability is an artifact of an incorrect non-linearity introduced by the computational approach: Propagation with an adiabatic exchange-correlation approximation within the time-dependent Kohn-Sham equations of time-dependent density functional theory (TDDFT) tends to amplify initially small and pure sinusoidal oscillations in a system. On the other hand, when this same adiabatic approximation is used within the recent response-reformulated RR-TDDFT,the instability is absent. The absorbing boundary condition plays a crucial role consistent with our argument. We demonstrate this explicitly on the N2 molecule subject to an XUV pulse, with a range of adiabatic functionals. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.08619 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08619v1 Announce Type: new Abstract: The recently developed Doubles Connected Moments (DCM) expansion offers a tractable approach for computing correlation energy, exhibiting an noniterative O(N^6) scaling with system size N. Benchmark calculations on a set of molecules demonstrate that the DCM can outperform CCSD in terms of accuracy. To further enhance its efficiency, we present a stochastic variant of DCM by introducing a stochastic resolution-of-identity (sRI) technique, which decomposes the essential four-index intermediates. The resulting sRI-DCM scheme only involves one O(N^6) step, while all other steps do not exceed O(N^4) at each recursion, and reliably reproduces the results of conventional DCM. Our sRI-DCM achieves an overall experimental scaling of O(N^{4.46}) for series hydrogen dimer chains, demonstrating that it is attractive and practical for large systems containing hundreds of electrons. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2605.08494 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08494v1 Announce Type: new Abstract: Oriented external electric fields are ubiquitous in chemistry; however, the effects of fields applied in different directions on molecular systems remain underexplored. A major challenge is that an applied field exerts a torque on a molecule, reorienting the molecular frame and complicating the interpretation of orientation-dependent electric-field effects. Thus, free polar molecules experience orienting rather than oriented fields. In this work, we explore a new regime of distinct molecular equilibrium configurations, differing in the relative direction of the external field and the molecular frame, enabled by exploiting molecular polarizability rather than static dipole moment. These distinct "directomers" exhibit unique electronic and nuclear configurations, particularly in their low-lying excited states. We employ oriented electric field vectors referenced to a molecule-fixed principal axis frame along with hybrid analytical-numerical geometry optimization in order to explore the rotational potential energy surface (rRES), as well as a simply analytic model based on equilibrium electrical properties which captures the double-well character of the rPES, including some geometry relaxation effects. Physics/physics.chem-ph_(Chemical_Physics) https://arxiv.org/abs/2504.11329 Tue, 12 May 2026 00:00:00 -0400 arXiv:2504.11329v2 Announce Type: replace-cross Abstract: The paradox of Maxwell's demon motivated the development of information thermodynamics and the creation of nanoscale information engines. We now understand that machines such as the molecular motors within cells can in principle harvest fluctuations and thereby operate as a Maxwell demon -- but do they? Answering this question would seemingly require simultaneous measurement of all system degrees of freedom, which is generally intractable in single-molecule experiments. Here, we derive a simple statistical estimator to infer both the direction and magnitude of subsystem heat flows, and thus determine whether -- and how strongly -- a motor operates as a Maxwell demon. The estimator uses only trajectory measurements for a single degree of freedom. Simulating both colloidal information engines and kinesin molecular motors, we show that our estimator can precisely and accurately detect Maxwell-demon behavior with experimentally accessible resolution and quantities of data. Moreover, we find that kinesin transitions to a Maxwell-demon mechanism in the presence of nonequilibrium noise, with a corresponding increase in velocity consistent with experiments. These findings suggest that molecular motors may have evolved to leverage active fluctuations within cells. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2605.10420 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10420v1 Announce Type: cross Abstract: Complex microbial habitats see the spatial competition of different clonal bacterial populations that switch between different phenotypes. Here, we determine the effect of this subpopulation structure on the invasion of one species by another in a minimal model of two competing species: one species switches, both stochastically and in response to its competitor, to a persister phenotype resilient to competition. Surprisingly, our combined analytical and numerical results show that this phenotypic switching has no effect on the speed of the travelling wave by which the competitors invade the first population. Conversely, we discover that phenotypic switching can speed up the wave by which this population invades their competitors. Our results thus suggest, counterintuitively, that bacterial persistence can be an offensive, rather than defensive ecological strategy. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2605.08953 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08953v1 Announce Type: cross Abstract: Background: BP180, also known as collagen XVII and BPAG2 (bullous pemphigoid antigen 2), is a 180-kDa transmembrane protein within the hemidesmosomal plaque complex, and which is known to be a major antigen in bullous pemphigoid, gestational pemphigoid, cicatricial (mucous membrane) pemphigoid, and linear IgA bullous disease. Objective: At present, the 3D structure of BP180 is not known. The goal is to predict a reasonable structure for BP180 through machine learning and molecular dynamics. Methods: In this work, we use the recent Boltz-2 model to predict a putative structure for the intracellular, transmembrane, and proximal extracellular domains, including the NC16A antigenic region and a portion of its first extracellular collagenous domain, Col-15. We computationally embed BP180 in a simple phospholipid bilayer, demonstrate that the putative structure is stable using molecular dynamics, and analyze its allosteric properties. Results: The structures presented satisfy symmetry and secondary structure properties which are expected from homology modelling. Over three 500 ns trajectories, there is minor instability of the predicted globular head domain, but the homotrimer otherwise stays mostly folded. The putative NC16A domain is stiff, whereas the truncated Col-15 domain is highly flexible. There does not appear to be a nearby stable conformation distinct from the initial state. Conclusion: The structure presented is a useful starting point for targeting BP180 pharmacologically, for further experimental characterization of BP180, and for generating hypotheses regarding the relevant epitopes contributing to bullous disease. Diffusion models such as Boltz-2 and AlphaFold3 are useful, but their results must be evaluated carefully. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2508.18710 Tue, 12 May 2026 00:00:00 -0400 arXiv:2508.18710v2 Announce Type: cross Abstract: Microbial adaptation to extreme stress, such as starvation, antimicrobial exposure, or freezing often reveals fundamental trade-offs between survival and proliferation. Understanding how populations navigate these trade-offs in fluctuating environments remains a central challenge. We develop a quantitative model to investigate the adaptation of populations of yeast (Saccharomyces cerevisiae) subjected to cycles of growth and extreme freeze-thaw stress, focusing on the role of quiescence as a mediator of survival. Our model links key life-history traits: growth rate, lag time, quiescence probability, and stress survival, to a single underlying phenotype, motivated by the role of intracellular trehalose in the adaptation of yeast to freeze-thaw stress. Through stochastic population simulations and analytical calculation of the long-term growth rate, we identify the evolutionary attractors of the system. We find that the strength of the growth-survival trade-off depends critically on environmental parameters, such as the duration of the growth phase. Crucially, our analysis reveals that populations optimized for growth-stress cycles can often maintain viability alongside growth-optimized populations even in the absence of stress. This demonstrates that underlying physiological trade-offs do not necessarily translate into fitness trade-offs at the population level, providing general insights into the complex interplay between environmental fluctuations, physiological constraints, and evolutionary dynamics. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2605.10444 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10444v1 Announce Type: new Abstract: Understanding the molecular mechanism by which denaturants modulate protein structure remains a central challenge in protein biophysics. In this work, molecular dynamics simulations were employed to investigate the effects of urea on the structural stability of bovine serum albumin, its F isoform at pH 3.7, over a broad range of urea concentrations (0 M to a fully urea/solvated system). The results reveal that urea induces a concentration/dependent dehydration/rehydration mechanism within the protein hydration shell. At low urea concentrations, a marked reduction in protein/water hydrogen bonds is observed, accompanied by a corresponding increase in protein/urea interactions, consistent with a competitive solvation process. At higher concentrations, urea/urea self-association becomes significant, limiting direct protein/urea interactions and promoting partial rehydration of the protein surface. Despite these solvent rearrangements, the secondary structure of BSA remains largely preserved, whereas local and tertiary structural features, particularly in Domain III, exhibit increased solvent exposure and conformational flexibility. These findings support a dynamic compensation mechanism in which urea partially replaces water in the solvation shell without fully disrupting the hydrogen-bonding network. Overall, this study provides molecular-level insight into the interplay between preferential interactions, solvation dynamics, and protein stability under denaturing conditions. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2605.09704 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09704v1 Announce Type: new Abstract: Multi-nucleated cells exist in all domains of life, ranging from animals, plants and fungi to single-celled organisms such as the slime mold Physarum polycephalum. The large cell size, in the case of Physarum reaching centimeters and more, challenges the coordination of nuclei activity as signals need to cross large distances. In search for a mechanism for fast long-ranged communication among nuclei, we quantify nuclei dynamics and cytoplasmic flows in Physarum's tubular network. We observe nuclei in two interchangeable, dynamic states: mobile, flowing within the cytoplasmic shuttle flow, or trapped in the tube's porous cell cortex. As we find nuclei to accumulate at the tube's inner fluid-porous interface we theoretically explore and confirm, with physiological parameters, that slowing down of mobile nuclei during flow is sufficient for diffusible signal exchange between mobile and trapped nuclei. We analytically derive that communication akin to pigeon-post with mobile nuclei serving as pigeons shuttling between trapped nuclei acting as waypoints, gives rise to signaling velocities that account for the rapid intracellular reorganization observed in Physarum. Since signal transfer by flow-transported nuclei outcompetes the mere diffusion of signals encoded in cytosolic proteins, pigeon-post communication surpasses alternative signaling mechanisms, even diffusive relay signaling up to twenty-fold in velocity. The key ingredients of pigeon-post communication, namely alternating flows and waypoints, exist in other multi-nucleated cells and may also be generalized beyond intracellular signaling. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2605.08469 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08469v1 Announce Type: new Abstract: We study the effects of weak magnetic fields (around 2 mT) on the growth of Staphylococcus aureus (S. aureus) in the presence of a few sweeteners (monosaccharides, disaccharides, sugar alcohols, and consumer-grade sweeteners). Bacterial growth rates were compared in various magnetic fields at room temperature. Bacterial growth was estimated using optical absorbance measurements at various wavelengths, and pH values were manually estimated using pH strips. Absorbance was measured at 492 nm and 630 nm, which are wavelengths comparable to the size of a cell of S. aureus after division. This comparability plays a vital role in the scale of measured absorbance values. The results imply that bacterial growth may be reduced due to acidic byproducts formed by metabolizing sugars or sugar alcohols, as an increasingly acidic solution is less ideal for bacterial growth. Magnetic fields were also found to have a minor effect on pH estimates. These results reveal potential effects on microorganisms in the presence of sugars and sugar alcohols in addition to weak magnetic fields, demonstrating the contribution of various environmental conditions with increasing prevalence in the modern day. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2605.08307 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08307v1 Announce Type: new Abstract: Triplet formation and its regulation have always been of central interest in understanding the photophysical behavior of living systems. In organic systems, excessive triplet formation poses significant challenges, as it can promote photochemical damage and reduce the efficiency of charge separation processes, making its regulation critically important.Here, we present a theoretical investigation of the intrinsic quantum spin dynamics governing triplet formation in the heliobacterial reaction center, a system that operates without any internal magnetic field. Using an open quantum systems approach based on the Lindblad formalism, we simulate the spin-correlated radical pair dynamics occurring during charge separation in the heliobacterial reaction center. The study systematically examines how triplet formation is regulated by variations in two key parameters, hyperfine coupling strengths and recombination rates, and how this regulation is further influenced by the inclusion of chirality-induced spin selectivity (CISS) in conjunction with the radical pair mechanism (RPM). Our results demonstrate that the CISS effect significantly suppresses triplet formation across the parameter space relevant to the heliobacterial molecular environment, revealing an intrinsic quantum protective mechanism operating through spin control in heliobacterial photosynthesis. Physics/physics.bio-ph_(Biological_Physics) https://arxiv.org/abs/2506.13371 Tue, 12 May 2026 00:00:00 -0400 arXiv:2506.13371v3 Announce Type: replace-cross Abstract: V-type three-level systems, where two excited states share a common ground state, serve as fundamental models for exploring coherent light-matter interactions in a range of quantum systems, from atomic gases to semiconductor nanostructures. In this work, we investigate the coherent evolution of such a system under strong femtosecond-pulse excitation by numerically solving the optical Bloch equations. Our analysis shows that the coherent evolution of a three-level system critically depends on the product of the excitation-pulse duration and energy separation between the excited states. Building on this understanding, we extend our analysis to simulate two-dimensional coherent spectra in a high-intensity regime. We demonstrate a control over the coherent pathway contributions to the nonlinear optical response of a V-type system by varying the intensity of the excitation pulses. This control is manifested through the ability to selectively turn individual spectral features on or off in the 2D spectra, each corresponding to distinct quantum pathways. Furthermore, the pulse intensities are varied to precisely adjust the phase of these peaks. Our approach provides a simple and robust framework for achieving control of coherent response of multilevel systems. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.05100 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.05100v2 Announce Type: replace Abstract: In this work, we calculate the hyperfine-structure constants of the $^{45}$Sc$^{+}$ ion using a relativistic hybrid approach that combines configuration-interaction and coupled-cluster singles-and-doubles methods. Magnetic-dipole and electric-quadrupole hyperfine-structure constants are determined for the states arising from the $3d4s$, $3d^{2}$, $4s^{2}$, $4s4p$, $3d4p$, $3d5s$, $3d4d$, and $3d5p$ configurations. For most of these states, our magnetic-dipole hyperfine-structure constants agree well with available experimental data and represent a substantial improvement over previous theoretical results. By combining our calculated electric-field gradients with the measured electric-quadrupole hyperfine-structure constants for the $^{3}F_{2,3,4}$, $^{3}P_{1,2}$, and $^{1}G_{4}$ states within the $3d^{2}$ configuration, we derive a nuclear quadrupole moment $Q = 0.222(2)$ b, which is fully consistent with the value recently obtained from molecular data ( J. P. Dognon and P. Pyykk\"{o}, Phys. Chem. Chem. Phys. 27, 20453 (2025).). Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2603.05859 Tue, 12 May 2026 00:00:00 -0400 arXiv:2603.05859v3 Announce Type: replace Abstract: Optical pumping is fundamental to high-precision measurement using thermal alkali-metal atoms in vapor cells. In applications such as atomic magnetometry, buffer gases (e.g., $\mathrm{N}_2$ or $\mathrm{He}$) at specific pressures are introduced to quench fluorescence and mitigate wall relaxation. In the high-pressure limit (e.g., the $\mathrm{N}_2$ pressure $p_{\mathrm{N}_2}> 1$~atm), where collisional broadening exceeds hyperfine splittings of the atoms, optical pumping theory provides a clear description of the angular momentum exchange between photons and atomic spins. However, in many magnetic sensing scenarios, the high-pressure approximation becomes inadequate as its pressure conditions are not strictly satisfied. Consequently, an explicit description of optical pumping under realistic pressures is critical for selecting operating points and enhancing system performance. To address this, we develop a unified theoretical framework of optical pumping in the quasi-high-pressure regime, where collisional broadening is comparable to the ground-state hyperfine splitting. We demonstrate that light absorption, spin polarization, and magnetic-resonance linewidth in this regime differ significantly from those predicted by the high-pressure limit and offer favorable operating conditions. Our study extends conventional modeling and offers critical guidance for atomic magnetometry operating under realistic buffer gas pressures. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.10924 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10924v1 Announce Type: cross Abstract: The ability to locally control and measure subsets of ancilla qubits in an efficient and crosstalk-free manner is a key ingredient in quantum error correction (QEC). Dual-species neutral atom arrays offer an ideal implementation of these capabilities, enabling independent state preparation, manipulation, and detection on each species. In this work, we realize such a dual-species Rydberg array of Na and Cs atoms trapped in co-localized 2D optical tweezer arrays, using Na as an ancilla to measure stabilizers of surrounding Cs data qubits. We identify the finite interspecies Rydberg-Rydberg interaction strength as a practical obstacle to high-fidelity multi-body entanglement and show that, by tuning the Rabi frequency and the detuning of the Rydberg driving field, the resulting geometric phase error can be compensated. This yields a protocol for simultaneous, non-destructive, in situ stabilizer readout of multiple data qubits via global pulses alone. Using this protocol, we demonstrate non-destructive measurement of Pauli-Z stabilizers on four-qubit Cs plaquettes via a single global Rydberg pulse sequence. Our results demonstrate dual-species tweezer arrays as a promising route towards scalable QEC and open the door to new quantum control protocols leveraging both interspecies and intraspecies interactions. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.10321 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10321v1 Announce Type: cross Abstract: Parity-nonconserving (PNC) effects in atoms produced by $Z$-boson exchange between the electron and the nucleus grow rapidly with the nuclear charge $Z$. If a hypothetical additional $Z'$ boson is light, however, its contribution does not exhibit the same strong enhancement with $Z$. As a result, the ratio of the low-mass $Z'$ contribution to the Standard Model $Z$-boson contribution increases rapidly with decreasing $Z$, in fact faster than $1/Z^2$. Hydrogen has a further important advantage: its theoretical description is substantially cleaner than that of heavy atoms, allowing a more accurate interpretation of experimental results. For these two reasons, hydrogen and deuterium PNC experiments may provide an especially favorable setting in which to disentangle a possible $Z'$ contribution from the Standard Model background. In this paper we calculate the ratio of the $Z'$-boson contribution, for arbitrary $Z'$ mass, to the Standard Model $Z$-boson contribution to parity violation in hydrogen and deuterium, including both nuclear-spin-independent (NSI) and nuclear-spin-dependent (NSD) interactions. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.09851 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09851v1 Announce Type: cross Abstract: Ball lightning is one of the most mysterious atmospheric phenomena, whose long lifetime, penetrative ability, and stability are difficult to explain with traditional physical models. This paper proposes a novel theoretical framework, interpreting ball lightning as a projection of a high-dimensional topological soliton into three-dimensional space. Its essence is described by a nonlinear Schr\"odinger equation with attractive interaction, protected by a non-zero topological charge. Through numerical simulation of the three-dimensional Gross-Pitaevskii equation, we verify the core predictions of this model: in a Bose-Einstein condensate with attractive interactions, solitons carrying topological charge exhibit: (1)long-lived stability (topological charge conserved under perturbations); (2)low transmission probability (due to minimal overlap integral resulting from orthogonality with the ground state wavefunction); (3)energy and size scales consistent with actual observations. Theoretical analysis indicates that the soliton lifetime is governed by the system's decoherence rate, providing a natural explanation for the observed second-scale lifetimes. This work not only offers a self-consistent physical explanation for ball lightning but also provides a concrete scheme for the experimental preparation and observation of three-dimensional topological solitons. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.09715 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09715v1 Announce Type: cross Abstract: Quantum systems with more than two levels $-$ so-called qudits $-$ offer increased computational density and reduced circuit complexity compared to qubit-based architectures, but achieving universal and scalable control remains challenging. We propose an all-optical scheme for universal qudit control in trapped neutral atoms in moderate to high magnetic fields, focusing on the fermionic isotope $^{173}$Yb ($I=5/2$). The strong hyperfine interaction in the $^3P_1$ manifold enables fast and selective Raman transitions between nuclear-spin states in the $^1S_0$ ground-state manifold using a single linearly polarized laser. For each neighboring transition in the qudit manifold, we identify a magic polarization angle that enables coherent, state-selective control while suppressing off-resonant excitations, with operation frequencies exceeding 100~kHz. Combined with phase-shift operations, this provides universal control of the full single-qudit space. We further discuss compatible two-qudit gates based on the Rydberg blockade mechanism, completing a universal gate set, and analyze state-selective readout schemes compatible with the proposed protocol. Our results identify $^{173}$Yb as a promising platform for high-fidelity, all-optical qudit-based quantum information processing. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.09532 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09532v1 Announce Type: cross Abstract: Strong atom-photon interactions on scalable photonic platforms hold significant potential for both atomic and photonic quantum information platforms. In particular, trapping of a single atom on a planar photonic integrated resonator at the subwavelength distances required for strong coupling to the guided modes has remained an outstanding challenge. Here we demonstrate efficient trapping of a single ultracold rubidium atom within the evanescent field of an integrated silicon-nitride microring resonator, at distances of 150-200 nm from the chip surface. Efficient, single-stroke loading process is achieved using an evanescent-field mechanism related to Sisyphus cooling, in which a single scattering event dissipates the atom's kinetic energy and transfers it into a near-surface trap. We observe logarithmic scaling of trapping durations spanning from sub-millisecond timescales up to 1 second, without continuous cooling. The trapped atom couples efficiently to the resonator, enabling on-chip photon collection, photon antibunching, and Purcell-enhanced spontaneous emission with single-atom cooperativity exceeding unity. Our results establish the potential of CMOS-compatible chip-based atom-photon interfaces for scalable quantum photonic circuits. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.09311 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09311v1 Announce Type: cross Abstract: Unlike most static material properties widely studied in the machine learning literature, ionic transport properties are inherently dynamic, making their fast and accurate prediction from static atomic structures challenging. The current standard approach, molecular dynamics (MD) simulations, suffers from prohibitively high computational cost. Recent autoregressive learning-based MD acceleration methods requiring sequential inference remain slow and prone to error accumulation; in contrast, existing non-autoregressive material property prediction models are less accurate because they fail to exploit dynamics. Moreover, existing methods typically benefit from datasets either with or without atomic trajectories, but not both. To overcome these limitations, we propose a non-autoregressive learning framework based on auxiliary modality learning, which treats atomic trajectories as an auxiliary modality during training but does not require them at inference. This enables the predictor to learn dynamics without sequential inference while benefiting from both types of datasets. As a result, our framework achieves over 200 times speedup compared to autoregressive models on the dataset with atomic trajectories while substantially reducing prediction error relative to non-autoregressive benchmarks across both types of datasets. Our code is available at https://github.com/jykim-git/MD. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.08875 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08875v1 Announce Type: cross Abstract: The Bloch Siegert shift, a hallmark correction arising from counter-rotating interactions in driven two-level systems, has an exact counterpart in binary lattices under static forcing, where it governs resonant long-range tunneling between sites separated by odd lattice spacings. Here we report the first experimental realization of this correspondence using a 12 mode programmable photonic integrated circuit. By implementing a reconfigurable binary lattice with sub-percent control of on-site detuning, we observe coherent periodic jumps across four resonance orders and quantitatively verify the predicted period law over the full parameter space. The measured dynamics exhibit the extreme resonance sensitivity characteristic of Bloch Siegert physics and agree closely with the level-anticrossing picture of the semiclassical Rabi model. Exploiting the underlying parity structure, we further convert intrinsically bidirectional oscillations into cascaded unidirectional transport through adaptive sign reversal of the staggered potential, achieving fidelities exceeding 0.95 and 0.98 on the same hardware platform. Our results establish programmable photonic lattices as a scalable testbed for strongly driven quantum-optical phenomena and Floquet-engineered transport. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.10669 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10669v1 Announce Type: new Abstract: The one-centre Coulomb-Sturmian convergent close-coupling method is applied to proton collisions with the boron atom and singly charged carbon ion. Here we report an update to our target-structure implementation, in which configuration state functions are constructed using the method of coefficients of fractional parentage. To assess the quality of the structure models for the two targets, we present the excitation energies, oscillator strengths, and dipole polarisabilities obtained from the present configuration interaction calculations. Cross sections for total and state-selective target excitation and electron loss are calculated from 10 keV to 1 MeV. For both systems, the total excitation cross section is found to be dominated by excitation of the $2s$ subshell. This emphasises the importance of a multi-electron description of the target in such scattering calculations. Comparisons with previous theoretical and experimental data are presented and discussed. In particular, we find that the present calculation for the electron-loss cross section in $p$ + C$^{+}$ collisions is in good agreement with the available measurements across the entire overlapping incident-energy range. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2605.09596 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09596v1 Announce Type: new Abstract: Finite nuclear size (FNS) effects on the magnetic-dipole hyperfine splitting in muonic hydrogenlike ions are investigated within a fully relativistic Dirac framework. The FNS contribution is quantified through the correction factor $\delta$, defined by $\Delta E_{\mathrm{ext}} = \Delta E_{\mathrm{point}}(1 - \delta)$, where $\Delta E_{\mathrm{ext}}$ is evaluated using Dirac wavefunctions computed for an extended nuclear charge distribution. Two nuclear models are considered: a homogeneously charged sphere and a two-parameter Fermi distribution. Bound-state energies and radial wavefunctions are obtained using a numerical iterative solver, while a semi-analytic matching scheme provides reference values and initial seeds. We present a systematic dataset of $\delta$ values for the $1s$, $2s$, and $2p_{1/2}$ states over a wide range of nuclear charge numbers $Z$. Nuclear-model dependence is quantified, including uncertainties induced by the nuclear radius in the uniform-sphere model. The results show that $\delta$ increases monotonically with $Z$ and exhibits clear state dependence, with reduced magnitude for the $2p_{1/2}$ state relative to $s$ states. A pronounced sensitivity to the nuclear charge distribution is observed, highlighting the importance of realistic nuclear modeling in precision hyperfine studies of muonic atoms. Physics/physics.atom-ph_(Atomic_Physics) https://arxiv.org/abs/2508.19124 Tue, 12 May 2026 00:00:00 -0400 arXiv:2508.19124v2 Announce Type: replace-cross Abstract: The mobility of both Fe and Ni atoms in ferromagnetic Fe$_x$Ni$_{1-x}$ alloys ($0.4 \leq x \leq 0.6$) is investigated within the framework of ab initio electronic structure calculations, using the nudged elastic band (NEB) method to accurately quantify energetic barriers to lattice vacancy migration. Both the atomically disordered (A1) fcc phase, as well as the atomically ordered, tetragonal $\mathrm{L}1_0$ phase - which is under consideration as a material for a rare-earth-free 'gap' magnet for advanced engineering applications - are investigated. Across an ensemble of NEB calculations performed on supercell configurations spanning a range of compositions and containing disordered, partially ordered, and fully ordered structures, we find that Ni atoms are consistently significantly less mobile than Fe atoms. Crucially, we are able to interpret these findings in terms of the ferromagnetic alloy's underlying spin-polarised electronic structure. Specifically, we report a coupling between the size of local lattice distortions and the magnitude of the local electronic spin polarisation around vacancies. This causes Fe atoms to relax into lattice vacancies, while Ni atoms remain rigidly fixed to their original lattice positions. This effect plays a key role in determining the reduced mobility of Ni atoms compared to that of Fe atoms. These results shed atomic-scale insight into the longstanding experimental observation that Ni exhibits remarkably slow atomic diffusion in Fe-Ni alloys. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2312.16376 Tue, 12 May 2026 00:00:00 -0400 arXiv:2312.16376v3 Announce Type: replace-cross Abstract: Flow generated noise are caused shear flows and, hence, they can be used as feedback to control the flow. Existing flow control uses state variables like velocity, pressure, or vorticity, none use acoustic observables as the primary control signal. It is tough to model a classical control algorithm using sound level but data-driven approaches are not as do not have to explicitly model the physics. We present an acoustics-driven framework for active control of unsteady wake dynamics behind a circular cylinder, in which sound is used as the primary feedback signal for flow regulation. The approach integrates deep reinforcement learning (DRL) with synthetic jet actuation, using acoustic measurements acquired from a downstream hydrophone array to inform control decisions in real time. Unlike conventional flow control strategies that rely on velocity or pressure field sensing, the proposed method establishes a direct link between far-field acoustic emissions and near-field actuation. Within this formulation, the DRL agent learns control policies that exploit acoustic signatures of vortex shedding to modulate synthetic jet actuation on the cylinder surface. The resulting control suppresses coherent wake structures and mitigates flow-induced disturbances. Quantitative results show reductions of up to 9.5\% in radiated noise and 23.8\% in drag under the tested conditions, accompanied by a marked attenuation of wake oscillations, for a DFG 2D benchmark flow with Reynolds number 100. These findings demonstrate that acoustic sensing alone can provide sufficient information for effective closed-loop flow control and highlight its potential as a non-intrusive feedback modality for coupled aerodynamic and aeroacoustic optimization in bluff-body flows. The codes for the algorithm can be found here: https://github.com/Siddharth-Rout/FlowControlDRL. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2603.02734 Tue, 12 May 2026 00:00:00 -0400 arXiv:2603.02734v2 Announce Type: replace Abstract: The human brain achieves exceptional energy efficiency by co-locating memory and processing, yet reproducing this principle in hardware remains challenging because many neuromorphic devices require standby power, offer limited programmability, or separate state storage from nonlinear computation. Here we demonstrate a multifunctional spintronic platform based on storage-layer-enabled vortex magnetic tunnel junctions (MTJs) that unifies non-volatile weight storage, optoelectrically driven nonlinear computation, and multilevel readout within a single nanopillar. A thermally programmable FM/AFM storage layer retains analog synaptic weights with zero standby power and enables non-volatile tuning of the vortex gyrotropic resonance over ${\sim}15$~MHz. Under optoelectrical operation, combined laser heating and dc bias drive the junction into the bias-enhanced tunnel magneto-Seebeck (bTMS) regime, where the thermoelectric response exhibits a pronounced cubic nonlinearity providing a compact, hardware-native transfer function for weighted analog computation. The electrical and thermoelectric channels switch at matched coercive fields but with distinct amplitudes, yielding an effective four-level readout space. Crossbar-array simulations parameterized by measured device response maps evaluate two neuromorphic modes -- a bTMS mode (optical input, dc-bias weights) and a spin-diode mode (RF-frequency input, RF-power weights) -- achieving image-classification accuracies of $95.4\%$ and $94.9\%$, comparable to a digital single-layer network with sigmoid activations. Smaller 600~nm devices consistently outperform larger ones, identifying nonlinear-response engineering as a key device-level lever. Because bTMS and spin-diode rectification coexist in the same junction, a combined regime could enable nonlinear multi-input interactions, including quadratic cross-terms, within a single nanoscale element. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2511.08103 Tue, 12 May 2026 00:00:00 -0400 arXiv:2511.08103v3 Announce Type: replace Abstract: Highly correlated photon sources can be realized through cooperative coupling among quantum systems, giving rise to superradiant collective emission. In solid-state ensembles, however, such collective behaviour is confined to subwavelength dimensions and is strongly suppressed at room temperature by inhomogeneous broadening and rapid dephasing, limiting practical implementations. Here, we show that molecular J-aggregates sustain room temperature superradiant emission and enter a highly collective regime when strongly coupled to delocalized photonic modes of a silicon bound-state-in-the-continuum (BIC) metasurface, extending J-exciton interactions far beyond the subwavelength limit. This enhanced cooperativity produces a photonic-fraction-dependent increase in emission rate and intensity and drives the system into a highly superbunched photon emission regime with g^((2))(0)>13. Spatial coherence measurements and stochastic modelling reveal that metasurface-mediated synchronization of ~10^3 J-excitons occurs within coupled superradiant domains spanning up to 6.7 um in diameter, corresponding to a 50-fold increase in inter-aggregate cooperative distance. These results establish exciton-polaritons in resonant dielectric metasurfaces as a platform to enhance superradiant emission and engineer temporally correlated light sources with picosecond-scale emission dynamics operating at room temperature. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.10324 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10324v1 Announce Type: cross Abstract: Dynamic atom gravimeters enable absolute gravity measurements on moving platforms. However, their performance is severely degraded due to the complex dynamic environment. This paper finds that the amplitude modulation noise (AMN) is a key factor contributing to the degradation of gravity measurement performance. We find that the AMN is induced by the cold atomic cloud trajectory and velocity variation. We build a model to illustrate the principles and magnitude of AMN arising from various experiment processes. Then we propose a method to fit the normalized AMN respect to the kinematic parameters of the cold atomic cloud, and successfully suppress this noise from 0.11 to 0.038 using the fitting result. With this method, we improve the fringe phase resolution from 0.244 rad to 0.092 rad, and reduce the dynamic gravity measurement noise from 2.69 mGal to 1.68 mGal. This study finds and suppresses a key noise source for the dynamic atom gravimeters, which is important for further improving its precision. The proposed method can be also applied for precision enhancement for other dynamic atom interferometer-based sensors, such as the atom gradiometers and gyroscopes. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.09753 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09753v1 Announce Type: cross Abstract: Symmetry strongly impacts wave transport in complex media. In this Letter, we demonstrate that the phenomenon of symmetry-induced through-barrier transmission enhancement enables quantitative sensing across barriers in complex media. We consider two mirror-symmetric chaotic cavities coupled through a narrow slit and containing point scatterers at mirror-symmetric positions. The characteristics of the scatterers in one cavity are unknown, whereas those of the scatterers in the other cavity are programmable. By tuning the programmable scatterers to maximize broadband total transmission, we recover the unknown scatterers' characteristics across the barrier. We show that reliable sensing requires a sufficiently large bandwidth, because otherwise a narrowband asymmetric resonant enhancement can dominate over the desired symmetry-induced enhancement. We further examine how absorption and barrier opacity influence the minimum required bandwidth. Our results establish a symmetry-empowered principle for through-barrier sensing in complex media, suggesting a route toward through-wall imaging in complex environments. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.09624 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09624v1 Announce Type: cross Abstract: Artificial intelligence (AI) is reshaping education, scientific training, and materials discovery. In materials science, AI models increasingly support property prediction, experiment prioritization, and hypothesis generation; however, the limiting factor is no longer only algorithmic capability but also whether students and educators can use AI with domain-specific scientific judgment. This workshop-informed white paper and curriculum-oriented position article argues that AI education for AI-powered materials discovery must move beyond tool access and surface-level interaction with generative AI systems toward a workflow-aligned model of AI literacy. We connect AI literacy to materials-informatics competencies: data provenance, domain-specific featurization, model validation, uncertainty quantification, physics informed reasoning, reproducibility, and experimental feedback. We also emphasize outcome-oriented equity: institutions should evaluate not only access, participation, and engagement, but also whether AI-enabled instruction produces comparable learning gains, transfer of learning, confidence calibration, defined as the alignment with students confidence and the quality or correctness of their work, persistence, and research readiness across student subgroups. The paper synthesizes relevant evidence, identifies risks for learners such as cognitive off-loading and cognitive surrender, and provides a dual-track curriculum model and implementation recommendations such as curriculum guides and an assessment plan for courses, bootcamps, workshops, and program-level reform. The central goal is to prepare students to become better scientists, not merely more efficient users of AI tools. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.09324 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09324v1 Announce Type: cross Abstract: Noise is a significant challenge in imaging. Conventional intensity-based techniques mitigate noise through various filtering methods, but they often require prior knowledge of noise characteristics and struggle, especially under low-light conditions and with spatially structured noise. Quantum distillation provides enhanced noise rejection; however, its applicability is limited as it requires specialised illumination and substantial modifications to existing imaging setups. In this article, we introduce a coherence-based image distillation approach that separates object from noise by leveraging the difference in their temporal coherence properties. We implement this through our interferometric protocol, which enables imaging based on spatial coherence while simultaneously filtering out noise via temporal coherence. This overcomes the limitations of both intensity-based and quantum distillation methods. We experimentally demonstrate noise resilience by successfully recovering feature-rich objects, such as QR codes and grayscale wheels, obscured by spatially uniform and structured noise 20 times as intense as the object. We further show that our method remains effective for fields with substantial spectral overlap, outperforming spectral filtering in regimes where the latter provides little noise suppression. This approach provides a robust framework for noise-resilient imaging with applications in optical communication, fluorescence microscopy, and biological imaging at both high and low light levels. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.09284 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09284v1 Announce Type: cross Abstract: Mesh-based simulations provide high-fidelity solutions to partial differential equations (PDEs), but achieving such accuracy typically requires fine meshes, leading to substantial computational overhead. Super-resolution techniques aim to mitigate this cost by reconstructing high-resolution (HR), high-fidelity solutions from low-cost, low-resolution (LR) counterparts. However, training neural networks for super-resolution often demands large amounts of expensive HR supervision data. To address this challenge, we propose SuperMeshNet, an HR data-efficient super-resolution framework for mesh-based simulations aided by message passing neural networks (MPNNs). At its core, SuperMeshNet introduces complementary learning, a semi-supervised approach that effectively leverages both 1) a small amount of paired LR-HR data and 2) abundant unpaired LR data via two jointly trained, complementary MPNN-based models. Additionally, our model is enriched by inductive biases, which are empirically shown to further improve super-resolution performance. Extensive experiments demonstrate that SuperMeshNet requires 90% less HR data to achieve even lower root mean square error (RMSE) than that of the fully supervised benchmark without the inductive biases. The source code and datasets are available at https://github.com/jykim-git/SuperMeshNet.git. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.08791 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08791v1 Announce Type: cross Abstract: Solid-state nanopores offer a powerful platform for nanoscale analysis of individual analytes, including biomolecules and functionalized nanoparticles, by confining them within a precisely defined sensing region. However, their inherently passive operation restricts practical applications, as they cannot precisely control particle position or dynamics inside the pore. Here, we introduce magnetic nanopore architectures that integrate a ferromagnetic layer into the nanopore system. Acting as a magnetic discontinuity within an otherwise uniformly magnetized film, the nanopore generates localized stray magnetic fields that enable magnetic tweezing of magnetic nanoparticles, which can be functionalized with fluorescent biomolecules. Importantly, the nanopore geometry is designed to reversibly switch between a nearly uniform magnetization state and a magnetic flux-closure state through the application of short magnetic field pulses of controlled amplitude. This capability allows the magnetic tweezing effect to be selectively activated or deactivated, enabling controlled capture and release of tagged biomolecules on demand. As a proof of concept, we demonstrate the selective magnetic trapping of fluorescent magnetic particles. These findings pave the way for reconfigurable, on-chip magnetic nanopore platforms capable of selective trapping and high-throughput single-particle detection. KEYWORDS: Nanopores, magnetic tweezers, fluorescence microscopy, vortex state, active control, magnetic nanoparticles Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.08779 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08779v1 Announce Type: cross Abstract: Plasmonic nanopores hold a significant promise for molecular sequencing, but their sensitivity and temporal resolution are constrained by limited signal strength and rapid translocation of molecules through the pore. Here we report an experimentally developed hybrid magnetoplasmonic nanopore platform based on bull's-eye geometry that concentrates surface plasmon polaritons into the pore, resulting in significant electric-field enhancement and improved signal readout. The addition of a ferromagnetic layer allows for magnetic tweezing of magneto-plasmonic nanoparticle-tagged molecules, providing active control over their translocation dynamics. Simulations reveal a further boost in enhancement arising from mirror-on-mirror plasmonic coupling between the nanopore and wall-aligned tagged nanoparticles. Together, experimental realization and simulation-guided insights establish a magnetically configurable, plasmonically enhanced nanopore platform that combines signal amplification with controlled translocation for advanced single-molecule sensing and sequencing. KEYWORDS: Nanopores, plasmonics, single-molecule sequencing, magneto-plasmonics, active control, magnetic tweezing. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.04402 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.04402v1 Announce Type: cross Abstract: The LaAlO$_3$/SrTiO$_3$ (LAO/STO) interface hosts a gate-tunable superconducting two-dimensional electron gas (2DEG) which can be programmed to create quantum devices such as ballistic electron waveguides and quantum dots. To fully exploit this platform for quantum transport, a key requirement is the ability to shuttle single electrons, electron pairs, and other exotic states between spatially separated devices with precision. Surface acoustic waves (SAWs), which travel along the surface of a solid, offer a powerful route to achieve this through their moving electrical potential that captures and transfers electrons. %acoustoelectric coupling. In particular, SAWs in the GHz regime enable fast, controlled transport of individual quantum particles. Although this approach is well-explored in GaAs-based 2DEG, SAW generation in STO remains largely unexplored due to the lack of intrinsic piezoelectricity at room temperature. Here, we investigate room-temperature SAWs in LAO/STO and observe SAW modes up to 2.2 GHz with very low propagation loss of the order $10^{-3}$ dB per wavelength. To directly visualize these modes, we employ Atomic Acoustic Force Microscopy (AAFM), achieving sub-micron resolution imaging of the SAW wave forms, providing insight into the electrostriction-induced SAW generation mechanism. Our measurements indicate a shear horizontal-type mode, which provides the ability to couple to in-plane degrees of freedom for future acoustoelectric and quantum device applications. This work studies the fundamentals of SAW excitation and propagation on STO, a widely used and commercially available substrate, enabling straightforward coupling of SAWs to a broad range of materials that can be grown or transferred onto STO. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.10736 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10736v1 Announce Type: new Abstract: This paper proposes a new integrated magnetics (IM) design for an isolated zero-voltage-switching (ZVS) Cuk converter (IZCC). In this design, six magnets are wound onto a single magnetic core, and to minimize magnetic core size and losses, both direct current (DC) and alternating current (AC) flux cancellations are considered. The DC flux is fully cancelled, and the AC flux must be cancelled until a limited value such that the input and output inductor currents have enough ripple to provide the conditions for achieving ZVS on all switches. Therefore, the value of the coupling coefficients (CC) between the windings should be considered such that the minimum ripple to achieve ZVS for all the switches is available. The design is implemented on a simple magnetic U-core, and the CC values are specified based on the winding locations and arrangement. To validate the idea experimentally, a hardware prototype is proposed with a power of 0.5 kW, a switching frequency of 150 kHz, and a peak efficiency of 97.25%. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.10545 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.10545v1 Announce Type: new Abstract: We develop a unified spectral-semigroup framework that connects real-time and imaginary-time quantum dynamics through analytic continuation. Within this formulation, evolution is expressed as an exponential reweighting of spectral components generated by a single operator $\mathcal{G}$, placing unitary and dissipative dynamics on equal footing within a common spectral structure. The mapping naturally induces a nonlocal fractional operator in time, giving rise to a contractive semigroup governed by a square-root spectral deformation and identifying imaginary-time evolution as an effective fractional low-pass filter. While exponential attenuation suppresses high-frequency components, the inverse transformation remains systematically controllable within a well-defined spectral window. In this regime, stable reconstruction of low-energy and coarse-grained dynamical features is achieved, establishing a predictive relation between imaginary-time evolution and recoverable information. This leads to a quantitative description of a bandwidth-resolved asymmetry between forward propagation and inverse recovery. Across systems with continuous and discrete spectra, few-level coherence, and non-Hermitian generators, we demonstrate that spectral structure governs reconstruction fidelity in a unified manner. In particular, non-Hermitian and open-system settings reveal that irreversibility emerges as a geometry- and scale-dependent feature of the spectrum, tied to both damping and eigenstate non-orthogonality. These results recast analytic continuation as a structured, scale-dependent filtering process with quantifiable and systematically accessible reconstruction limits, providing a unified perspective on the interplay between dynamics, spectral geometry, and information recovery. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.09980 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09980v1 Announce Type: new Abstract: The Cold-Neutron Inelastic Spectrometer (CNIS) is a direct-geometry, time-of-flight instrument designed for China Spallation Neutron Source (CSNS) and optimized to probe low-energy lattice and magnetic excitations. The instrument integrates a long flight path with bent supermirror guides and an elliptical-focusing geometry to suppress high-energy background while improving cold-neutron delivery to the sample. A flexible multi-disk chopper suite provides pulse shaping, band selection and monochromatization, enabling multi-$E_\textrm{i}$ operation. Modular features, including an interchangeable high-focusing guide insert, radial collimation and a vacuum ``airbox'' for simplified sample-environment integration, enhance signal-to-noise and operational versatility. Through combined flight-path and chopper optimization, CNIS achieves excellent routine-mode energy resolution and can reach approximately $\sim 1\%$ in a dedicated high-resolution configuration. CNIS is planned to commence user operation in 2029, offering a highly flexible platform for cold-neutron inelastic scattering studies. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.09371 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.09371v1 Announce Type: new Abstract: The calibration of discrete element method (DEM) models is commonly performed by tuning model parameters to match an experimental measurements, most commonly the angle of repose (AOR). Although widely used, AOR-based calibration metrics do not adequately characterize the full heap morphology, particularly when dealing with cohesive granular materials. As a result, AOR-based calibrations often leads to non-unique parameter sets. In this work, we propose a DEM calibration procedure based on full-field image analysis of static powder heaps rather than scalar AOR measurements. The method compares an average experimental heap profile (AEHP), obtained from repeated GranuHeap experiments, with an average numerical heap profile (ANHP) generated from DEM simulations. This comparison is performed using pixel-wise grayscale intensity values of both average heap profiles. Two metal powders commonly used in additive manufacturing, Ti6Al4V and Al6061, are used to evaluate the proposed methodology. This work highlights the limitations of traditional AOR-based approaches and demonstrates that full-field heap morphology offers a more reliable framework for DEM calibration. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.08768 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08768v1 Announce Type: new Abstract: This work introduces a semi-analytical frequency-domain framework for the analysis of two-dimensional, time-modulated (2+1)-D metasurfaces controlled by PIN diodes. The formulation focuses on the unit-cell level, modeled as a waveguide discontinuity problem, where the space-time periodicity of the structure enables the representation of scattered fields via Floquet expansions. After appropriate mathematical treatment, these expansions lead to an equivalent circuit description of the metasurface, providing physical insight into its spatiotemporal scattering behavior and facilitating the design of reconfigurable electromagnetic devices. The model is employed to explore key phenomena present in space-time systems, such as frequency mixing and spatiotemporal scattering. In addition, dynamic tuning is explored in resonant metasurfaces, where time becomes an additional degree of freedom for the design. The dynamic control of resonances opens a new way to explore multi-band and wideband behaviors from very thin metasurfaces under temporal coupling. Physics/physics.app-ph_(Applied_Physics) https://arxiv.org/abs/2605.08667 Tue, 12 May 2026 00:00:00 -0400 arXiv:2605.08667v1 Announce Type: new Abstract: We present an analytical framework capable of describing spin-waves dynamic in magnetic hetero-structures composed of a pair of exchange-decoupled magnetic layers separated by a nonmagnetic spacer, focusing in particular on garnet-based multilayers. The model captures the formation of collective spin-wave modes, namely symmetric and antisymmetric, arising from dipolar coupling and provides direct access to the dispersion relation of the system and consequent interference phenomena. This formalism establishes a versatile theoretical tool for the predictive design of dipolarly coupled magnonic devices, providing access to their eigenfrequencies and mode shapes. Physics/physics.app-ph_(Applied_Physics)