Computational Physics
Efficient GPU-computing simulation platform JAX-PF for differentiable phase field model
Fanglei Hu, Jiachen Guo, Stephen Niezgoda et al. (+2 more)
We present JAX-PF, an open-source, GPU-accelerated, and differentiable Phase Field (PF) software package, supporting both explicit and implicit time stepping schemes. Leveraging the modern computing architecture JAX, JAX-PF achieves high performance through array programming and GPU acceleration, delivering ~5x speedup over PRISMS-PF with MPI (24 CPU cores) for systems with ~4.19 million degrees of freedom using explicit schemes, and scaling efficiently with implicit schemes for large-size problems. Furthermore, a key feature of JAX-PF is automatic differentiation (AD), eliminating manual derivations of free-energy functionals and Jacobians. Beyond forward simulations, JAX-PF demonstrates its potential in inverse design by providing sensitivities for gradient-based optimization. We demonstrate, for the first time, the calibration of PF material parameters using AD-based sensitivities, highlighting its capability for high-dimensional inverse problems. By combining efficiency, flexibility, and full differentiability, JAX-PF offers a fast, practical, and integrated tool for forward simulation and inverse design, advancing co-designing of material and manufacturing processes and supporting the goals of the Materials Genome Initiative.
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All authors Fanglei Hu, Jiachen Guo, Stephen Niezgoda, Wing Kam Liu, Jian Cao
Atmospheric and Oceanic Physics · Cross-listed from cs.CV
OptFormer: Optical Flow-Guided Attention and Phase Space Reconstruction for SST Forecasting
Yin Wang, Chunlin Gong, Zhuozhen Xu et al. (+2 more)
Sea Surface Temperature (SST) prediction plays a vital role in
climate modeling and disaster
forecasting. However, it remains challenging due to its nonlinear spatiotemporal dynamics and extended prediction horizons. To address this, we propose OptFormer, a novel encoder-decoder model that integrates phase-space reconstruction with a motion-aware
attention mechanism guided by optical flow. Unlike conventional
attention, our approach leverages inter-frame motion cues to highlight relative changes in the spatial field, allowing the model to focus on dynamic regions and capture long-range temporal dependencies more effectively. Experiments on NOAA SST
datasets across multiple spatial scales demonstrate that OptFormer achieves superior performance under a 1:1 training-to-prediction setting, significantly outperforming existing baselines in accuracy and robustness.
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All authors Yin Wang, Chunlin Gong, Zhuozhen Xu, Lehan Zhang, Xiang Wu
Optics
Scattering at Interluminal Interfaces
Zhiyu Li, Klaas De Kinder, Xikui Ma et al. (+1 more)
Scattering at interluminal modulation interfaces, where a sharp space-time perturbation moves at a velocity lying between the wave velocities of the two surrounding media, has remained an open problem for decades. This regime is somewhat reminiscent of the Cherenkov regime, in which the velocity of a charged particle exceeds the phase velocity of light in a medium. However, because it involves two media and a moving interface, it gives rise to richer and more complex scattering dynamics, with a single scattered wave when the incident wave propagates in the same direction as the interface and three scattered waves when they propagate in opposite directions. Existing studies address only limited non-
magnetic configurations, and a general formulation has yet to be established. In this paper, we present a complete and general solution to scattering in the interluminal regime using a symmetric decomposition approach based on subluminal and superluminal limit interfaces, together with a space-time impulse response. This approach provides clear physical insight into the scattering features of the interluminal regime. Our results bridge the long-standing gap between the subluminal and superluminal regimes and elucidate the fundamental mechanisms underlying interluminal scattering.
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All authors Zhiyu Li, Klaas De Kinder, Xikui Ma, Christophe Caloz
Chemical Physics
Scale-Dependent Velocity Fluctuations Generated by Molecular Collisions
Tristan Barkman
A discrete binomial random-walk description of molecular collisions is used to quantify the variance of coarse-grained velocity fields arising solely from collision-induced momentum exchange. Closed-form expressions for the growth of velocity variance as functions of coarse-graining scale and time are derived and shown to imply a power-law decay of variance with averaging scale. Particle-based ensemble simulations validate the predicted scaling and temporal behaviour; surrogate ensemble tests demonstrate that phase/temporal coherence is required for the observed integrated transfer diagnostics. The analysis is intentionally restricted to collision-generated fluctuations in quiescent fluids and does not model cascade dynamics; implications for possible amplification under inertial dynamics are discussed cautiously. All data and the minimal verification instructions required to reproduce the summary tables are embedded in Appendix A.
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Physics and Society
The hidden sustainability bottleneck in high-entropy alloy design
Alexandre Nominé, Ayyoub El-Kasmi, Danielle Beaulieu et al. (+21 more)
Because of the enormous number of possible compositions, comparable to the number of
stars in the universe, high-
entropy alloys (HEAs) constitute a virtually inexhaustible materials space with highly versatile properties. Among these systems, HEAs are often proposed as potential substitutes for critical elements such as rare earths or platinum group metals. However, random or incremental exploration strategies are neither practical nor efficient at this scale. Targeted materials selection guided by sustainability considerations is therefore essential, yet identifying sustainable HEA compositions remains highly challenging. Here, we perform a comprehensive sustainability assessment of 30,201 equimolar HEA compositions and identify a resilient shortlist (approximately 5%) that consistently exhibits favorable sustainability profiles across multiple evaluation schemes. Our analysis integrates complementary criteria including carbon footprint, environmental, social and governance (ESG) risks, production compatibility, and resource availability. The resulting sustainability-based ranking provides a strategic roadmap for HEA research, enabling experimental efforts to be focused on compositions that are not only functionally promising but also scalable and resource-responsible. By aligning materials discovery with sustainability and supply constraints, this framework supports more efficient use of experimental resources while contributing to long-term industrial sustainability goals.
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All authors Alexandre Nominé, Ayyoub El-Kasmi, Danielle Beaulieu, Outhmane Ouahri, Nguyen Thuy Huong, Wassim Amzil, Aymane Droussi, Oleksandra Kuksa, Eirini Katsarou, Chahrazed Labba, Anne Boyer, Hani Henein, Thierry Belmonte, François Rousseau, Tuncay Gurbuz, Elena Mitrofanova, Agnès Samper, Pascal Bolz, Valentin Milichko, Olga Chernoburova, Alexandre Chagnes, Michel Cathelineau, Uroš Cvelbar, Janez Zavašnik
Instrumentation and Detectors
Autonomous battery research: Principles of heuristic operando experimentation
Emily Lu, Gabriel Perez, Peter Baker et al. (+21 more)
Unravelling the complex processes governing battery degradation is critical to the energy transition, yet the efficacy of operando characterisation is severely constrained by a lack of Reliability, Representativeness, and Reproducibility (the 3Rs). Current methods rely on bespoke hardware and passive, pre-programmed methodologies that are ill-equipped to capture
stochastic failure events. Here, using the Rutherford Appleton Laboratory's multi-modal toolkit as a case study, we expose the systemic inability of conventional experiments to capture transient phenomena like dendrite initiation. To address this, we propose Heuristic Operando experiments: a framework where an AI pilot leverages physics-based digital twins to actively steer the beamline to predict and deterministically capture these rare events. Distinct from uncertainty-driven active learning, this proactive search anticipates failure precursors, redefining experimental efficiency via an
entropy-based metric that prioritises scientific insight per
photon,
neutron, or
muon. By focusing measurements only on mechanistically decisive moments, this framework simultaneously mitigates beam damage and drastically reduces data redundancy. When integrated with FAIR data principles, this approach serves as a blueprint for the trusted autonomous battery laboratories of the future.
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All authors Emily Lu, Gabriel Perez, Peter Baker, Daniel Irving, Santosh Kumar, Veronica Celorrio, Sylvia Britto, Thomas F. Headen, Miguel Gomez-Gonzalez, Connor Wright, Calum Green, Robert Scott Young, Oleg Kirichek, Ali Mortazavi, Sarah Day, Isabel Antony, Zoe Wright, Thomas Wood, Tim Snow, Jeyan Thiyagalingam, Paul Quinn, Martin Owen Jones, William David, James Le Houx
Physics and Society
A new kind of science
Alex Hansen and Sauro Succi
We discuss whether science is in the process of being transformed from a quest for causality to a quest for correlation in light of the recent development in artificial intelligence. We observe that while a blind trust in the most seductive promises of AI is surely to be avoided, a judicious combination of computer simulation based on physical insight and the machine learning ability to explore ultra-dimensional spaces, holds potential for transformative progress in the way science is going to be pursued in the years to come.
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Instrumentation and Detectors
Ion Optics for quasi-free $(p,p\alpha)$ reactions with Grand Raiden Spectrometer
Taichi Miyagawa and Junki Tanaka
The quasi-free $(p,p\alpha)$ reaction is a powerful tool to probe preformed $\alpha$ clusters in
nuclei, but it requires accurate reconstruction of both momentum and scattering angles at the reaction point. In this work, ion-optical analysis for $(p,p\alpha)$ measurements with the Grand Raiden spectrometer is presented. An under-focus optical setting was adopted to preserve sensitivity to the vertical scattering angle while maintaining high momentum resolution. The focal-plane geometry was determined independently as a purely geometrical reference. Momentum calibration was performed using elastic scattering of $^{206}$Pb$(p,p)$ at a fixed spectrometer angle. Scattering angles were reconstructed using ion-optical relations, and residual higher-order effects were corrected by a multidimensional fit. The dominant contributions to the reconstruction were found to arise from terms up to third order within the experimental acceptance. This ion-optical framework enables consistent event-by-event reconstruction of the reaction kinematics and provides a reliable basis for quasi-free $(p,p\alpha)$ analyses.
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Fluid Dynamics
Closed-Form Expressions for Five-Digit Reflex Camber-Line Design Parameters
Kio M. Lovric
Despite nearly a century of use in tailless and flying-wing aircraft, the NACA five-digit reflex camber-line family lacks published closed-form expressions for the governing design integrals; practitioners have instead relied on numerical quadrature and tabulated constants available only for a limited set of standard configurations. This paper addresses that gap by deriving closed-form analytical expressions for all lift and zero-moment integrals in terms of elementary functions of the breakpoint and maximum-camber-location parameters. A trigonometric substitution eliminates the endpoint singularities introduced by the Glauert transformation, yielding integrals expressible as inverse trigonometric functions combined with explicit
polynomials. The breakpoint parameter is determined by solving a single transcendental equation, and the remaining camber-line constants follow from direct evaluation without numerical integration. Independent verification by numerical quadrature confirms agreement with the analytical expressions to machine precision. Comparison with historical tabulations shows that the closed-form values satisfy the zero-moment design condition to machine precision, whereas substituting the tabulated breakpoints back into the same condition yields residuals nine to thirteen orders of magnitude larger, consistent with the rounding and computational precision available when the original tabulations were produced.
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Optics
Edge emission from 265~nm UV-C LEDs grown by MBE on bulk AlN
Shivali Agrawal, Hsin-Wei S. Huang, Debaditya Bhattacharya et al. (+6 more)
UV-C LEDs pseudomorphically grown by MBE on bulk AlN substrates emitting at 265 nm are demonstrated. High current density up to 800 A/cm$^2$, 5 orders of on/off ratio, and low differential on-resistance of 2.6 m$\Omega\cdot$cm$^2$ at the highest current density is achieved. The LED
heterostructure has a high refractive index waveguide core surrounded by n- and p-cladding layers similar to a
laser diode designed for mode confinement at 270 nm to facilitate edge emission and collection of
photons. Edge-emitting devices are made by cleaving the fabricated LEDs along the $m$-plane of the wurtzite
crystal. Electrical injection results in emission of high energy 4.7 eV
photons that are collected from the cleaved edge of the LEDs corresponding to the optical bandgap of the AlGaN active region. The contribution of power dissipation across the n- and p-regions of the diode is discussed. The n-contact resistance to n-AlGaN is identified as the largest contributor to the series resistance of the LED in the present generation of devices.
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All authors Shivali Agrawal, Hsin-Wei S. Huang, Debaditya Bhattacharya, Madhav Ramesh, Krzesimir Szkudlarek, Henryk Turski, Vladimir Protasenko, Huili Grace Xing, Debdeep Jena
Fluid Dynamics
Exact analysis of potential flow past bodies of irregular shapes
Ankur Jain
Fluid flow past one or more solid bodies is a fundamental problem of much practical importance. Standard solutions of simplified problems involving incompressible inviscid irrotational flow past common geometries such as circular cylinders and airfoils are commonly available. This work presents exact analysis of a potential flow problem involving fluid flow past one or more bodies of irregular shapes. The problem is solved by expressing the shape of each body using Heaviside functions, and writing the potential function as an eigenfunction-based series. Using the properties of Heaviside functions, the series coefficients are determined by deriving a set of linear algebraic equations that govern the coefficients. Benchmarking of the analytical technique against well-known solutions of standard problems is carried out, showing excellent agreement. Good agreement with past work on the specific problem of potential flow past multiple circular cylinders further establishes the accuracy of the analytical technique. Illustrative problems of flow past complicated geometries are solved. Implementation aspects and limitations of the analytical technique are discussed.
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Fluid Dynamics
Turbulence Kinetic Energy Distribution and Heat Transfer in a Porous Layer Induced by Bluff Body Vortex Shedding
Thibaut K Kemayo, Justin Courter, Vishal Srikanth et al. (+3 more)
When a turbulent
vortex impinges on a porous layer, it creates a complex multiscale interaction: the wake structures that form in the free fluid engage with the intricate geometry of the pores, and this interplay governs both the turbulent energy budget and the rate of heat transfer. Here we use interface-resolved two-dimensional direct numerical simulations (DNS) to examine how a bluff-body wake impinges on an in-line porous array heated to maintain a constant wall temperature. The Reynolds number is fixed at Re = 10000, and the porosity is varied between $\phi$ = 0.80 and $\phi$ = 0.95. In all cases, the incoming von Kármán
vortices undergo rapid breakdown at the porous/fluid interface and do not persist as coherent macroscale structures within the porous layer. The interface instead acts as a spectral filter: large-scale wake energy is strongly attenuated, while
turbulence is regenerated locally within the
matrix via shear layers and microscale
vortex shedding around individual obstacles. Thermal statistics show that the lower-porosity medium produces higher local and surface-averaged Nusselt numbers across representative interface and interior locations. This is consistent with the stronger shear and enhanced fluid/solid thermal interaction associated with the larger surface-area-to-volume ratio. These results clarify the mechanisms by which wake-driven
turbulence is converted into pore-scale motions and how porosity tunes the balance between
turbulence attenuation and convective heat transfer in porous coatings and inserts.
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All authors Thibaut K Kemayo, Justin Courter, Vishal Srikanth, Chadwick Jetti, Rodrigo R Caballero, Andrey V Kuznetsov
Instrumentation and Detectors
Control and read-out of the HEPD-02 tracking system onboard CSES-02 satellite
S. Bartocci, R. Battiston, S. Beolè et al. (+42 more)
The High Energy Particle Detector (HEPD-02) is a payload of the second China Seismo-Electromagnetic Satellite (CSES-02), designed and built by the Italian Limadou collaboration. Its purpose is to detect
cosmic rays and trapped particles of radiation belts, in the kinetic energy range 3-100 MeV for electrons, 30-200 MeV for
protons. HEPD-02 is the first space detector to use a tracking detector based on Monolithic Active Pixel Sensors (MAPS). The MAPS provides high spatial resolution, low noise, increased robustness, and low production costs. Operating MAPS in space presents a significant challenge due to strict power consumption requirements. To meet such constraints, a custom Tracker Data Acquisition (TDAQ) board and firmware have been designed and implemented, by using a commercial low-power Field Programmable Gate Array (FPGA). This paper addresses the design features of the TDAQ unit, enabling the tracking detector to be operated efficiently, with particular focus on the power consumption performance.
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All authors S. Bartocci, R. Battiston, S. Beolè, F. Benotto, P. Cipollone, S. Coli, A. Contin, M. Cristoforetti, C. De Donato, C. De Santis, A. Di Luca, F. Dumitrache, F. M. Follega, S. Garrafa Botta, G. Gebbia, R. Iuppa, A. Lega, M. Lolli, G. Masciantonio, M. Mergè, M. Mese, R. Nicolaidis, F. Nozzoli, A. Oliva, G. Osteria, F. Palma, F. Palmonari, B. Panico, S. Perciballi, F. Perfetto, P. Picozza, M. Pozzato, E. Ricci, M. Ricci, S. B. Ricciarini, Z. Sahnoun, U. Savino, V. Scotti, E. Serra, A. Sotgiu, R. Sparvoli, P. Ubertini, V. Vilona, S. Zoffoli, P. Zuccon
Plasma Physics
Autoregressive long-horizon prediction of plasma edge dynamics
Hunor Csala, Sebastian De Pascuale, Paul Laiu et al. (+3 more)
Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing
plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limits broad parameter scans and long transient studies. We present
transformer-based, autoregressive surrogates for efficient prediction of 2D, time-dependent
plasma edge state fields. Trained on SOLPS-ITER spatiotemporal data, the surrogates forecast electron temperature, electron density, and radiated power over extended horizons. We evaluate model variants trained with increasing autoregressive horizons (1-100 steps) on short- and long-horizon prediction tasks. Longer-horizon training systematically improves rollout stability and mitigates error accumulation, enabling stable predictions over hundreds to thousands of steps and reproducing key dynamical features such as the motion of high-radiation regions. Measured end-to-end wall-clock times show the surrogate is orders of magnitude faster than SOLPS-ITER, enabling rapid parameter exploration. Prediction accuracy degrades when the surrogate enters physical regimes not represented in the training
dataset, motivating future work on data enrichment and physics-informed constraints. Overall, this approach provides a fast, accurate surrogate for computationally intensive
plasma edge simulations, supporting rapid scenario exploration, control-oriented studies, and progress toward real-time applications in fusion devices.
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All authors Hunor Csala, Sebastian De Pascuale, Paul Laiu, Jeremy Lore, Jae-Sun Park, Pei Zhang
Chemical Physics
Surface adsorption at the thermodynamic limit using periodic DLPNO-MP2 theory: A study of CO on MgO at dilute and dense coverages
Andrew Zhu, Poramas Komonvasee, Arman Nejad et al. (+1 more)
We apply periodic domain-based local pair natural orbital second-order Møller–Plesset perturbation theory (DLPNO-MP2) to probe the adsorption energy of CO on MgO(001), the consensus toy model system for surface adsorption. A number of robust correlated wavefunction methods now achieve excellent agreement with experiment for the adsorption of a single CO molecule onto the MgO surface. However, studies probing denser coverage ratios are scarce because of the increased computational expense and the larger configuration space to optimize. We leverage the computational efficiency of periodic DLPNO-MP2 to perform simulations beyond a single unit
cell. By using large supercells, we highlight the importance of accurately representing the thermodynamic limit of the surface, and demonstrate in turn that different coverage ratios can be consistently probed. In the dilute regime, we show that adsorption energies obtained from periodic DLPNO-MP2 agree with existing
benchmarks. We then obtain adsorption energies at increasing densities approaching full monolayer coverage. Our results show a reduction in binding strength at full coverage, agreeing with experimental observations, which is explained by the increasing lateral repulsions between the COs. This study demonstrates the efficacy of periodic DLPNO-MP2 for probing increasingly sophisticated adsorption systems at the thermodynamic limit.
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All authors Andrew Zhu, Poramas Komonvasee, Arman Nejad, David P. Tew
Atomic Physics
Investigation of the benefits and disadvantages of using double-pair anti-Helmholtz coils in BEC-producing MOT setups and optimizing their design
Şenol Tarhan and Gabriel Goetten de Lima
This work has investigated the Magneto-Optical Trap (MOT) system used to produce Bose-Einstein Condensate (BEC). A primary challenge addressed in this study concerns the
geometric limitations of traditional single-pair anti-Helmholtz coil configurations, where the
magnetic field peaks occur outside the accessible inter-coil region. To overcome this limitation, we have explored the use of double-pair anti-Helmholtz coil configurations that create well-shaped
magnetic field potentials centered at the experimentally accessible $z=0$ location. This investigation encompasses the three sequential processes of atom cooling: cooling in a linear external
magnetic field through Doppler cooling, cooling in a well-shaped
magnetic field through trapping, and evaporative cooling of atoms to achieve sub-microkelvin temperatures. Through theoretical analysis and numerical simulation, we have determined optimal
geometric parameters for the coil configuration and operational parameters including
laser detuning, saturation intensity, and initial atom populations for ${}^{87}\text{Rb}$ BEC production. The results indicate that with the optimized configuration, the system can achieve final temperatures of approximately $T_f \sim 60\,\mathrm{nK}$ and produce condensate populations of $\sim 10^5$ atoms with a mean density of $n_0 = 4.9 \times 10^{15}\,\mathrm{m}^{-3}$, providing systematic design guidance for experimental BEC systems
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Fluid Dynamics
A Relative Liutex Method for Vortex Identification
Jiawei Chen, Yifei Yu and Chaoqun Liu
A relative Liutex
vortex identification method is proposed in this study, together with its explicit mathematical formulation. The method is designed to identify vortical structures based solely on local flow-field information and is inherently Galilean invariant, ensuring robustness under different reference frames. To validate the proposed approach, a three-dimensional flat-plate boundary-layer transition case is investigated, in which the relative Liutex is systematically compared with conventional
vortex identification methods, including the Q-criterion and the original Liutex method. The results show that the relative Liutex is capable of simultaneously capturing both strong and weak vortical structures. Importantly, its behavior cannot be interpreted as a simple superposition of Liutex iso-surfaces obtained using different threshold values. Instead, the relative Liutex provides a more selective and physically coherent identification of weak
vortices, particularly in regions above the $\Lambda$-
vortex and in the downstream hairpin-
vortex structures, while effectively suppressing spurious and noise-induced features. These advantages arise from its formulation based on local velocity-gradient strength rather than a global vortical-intensity measure. Owing to its ability to consistently identify
vortices across a wide range of intensities, the relative Liutex demonstrates strong potential for revealing complex
vortex structures and underlying flow mechanisms in
vortex-dominated flows.
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Computational Physics
Learning Density Functionals to Bridge Particle and Continuum Scales
Edoardo Monti, Peter Yatsyshin, Konstantinos Gkagkas et al. (+1 more)
Predicting interfacial thermodynamics across molecular and continuum scales remains a central challenge in computational science. Classical density functional theory (cDFT) provides a first-principles route to connect microscopic interactions with macroscopic observables, but its predictive accuracy depends on approximate free-energy functionals that are difficult to generalize. Here we introduce a physics-informed learning framework that augments cDFT with neural corrections trained directly against molecular-dynamics data through adjoint optimization. Rather than replacing the theory with a black-box surrogate, we embed compact neural networks within the Helmholtz free-energy functional, learning local and nonlocal corrections that preserve thermodynamic consistency while capturing missing correlations. Applied to Lennard-Jones fluids, the resulting augmented excess free-energy functional quantitatively reproduces
equilibrium density profiles, coexistence curves, and surface tensions across a broad temperature range, and accurately predicts contact angles and droplet shapes far beyond the training regime. This approach combines the interpretability of statistical mechanics with the adaptability of modern machine learning, establishing a general route to learned thermodynamic functionals that bridge molecular simulations and continuum-scale models.
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All authors Edoardo Monti, Peter Yatsyshin, Konstantinos Gkagkas, Andrew B. Duncan
Biological Physics · Cross-listed from q-bio.MN
Sheaf-theoretic representation of the proteolipid code
Troy A. Kervin
Membrane particles such as
proteins and lipids organize into zones that perform unique functions. Here, I introduce a topological and category-theoretic framework to represent particle and zone intra-scale interactions and inter-scale coupling. This involves carefully demarcating between different presheaf- or sheaf-assigned data levels to preserve functorial structure and account for particle and zone generalized poses. The framework can accommodate
Hamiltonian mechanics, enabling dynamical modeling. This amounts to a versatile mathematical formalism for membrane structure and multiscale coupling.
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Fluid Dynamics · Cross-listed from quant-ph
Euler-Korteweg vortices: A fluid-mechanical analogue to the Schrödinger and Klein-Gordon equations
D.M.F. Bischoff van Heemskerck
Quantum theory and relativity exhibit several formal analogies with fluid mechanics. This paper extends upon known analogies by showing that under specific assumptions, an Euler-Korteweg
vortex model can be cast into equations that are mathematically equivalent to the Schrödinger and Klein-Gordon equations. By assuming that the angular momentum of an irrotational
vortex in an inviscid, barotropic, isothermal fluid with sound speed c is equal in magnitude to the reduced Planck constant, and incorporating Korteweg capillary stress, a complex wave equation describing the momentum and continuity equations of an Euler-Korteweg
vortex is obtained. When uniform convection is introduced, the weak field approximation of this wave equation is formally equivalent to Schrödinger's equation. The model is shown to yield analogues to de Broglie wavelength, the Einstein-Planck relation, the Born rule and the uncertainty principle. Accounting for the retarded propagation of the wave field of a
vortex in convection requires the Lorentz transformation and yields a wave equation mathematically equivalent to the Klein-Gordon equation, with Schrödinger's equation appearing as the low-Mach-number limit.
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Optics · Cross-listed from quant-ph
Quantum Geometric Bounds in Non-Hermitian Systems
Milosz Matraszek, Wojciech J. Jankowski and Jan Behrends
We identify
quantum geometric bounds for observables in non-Hermitian systems. We find unique bounds on non-Hermitian
quantum geometric tensors, generalized two-point response correlators, conductivity tensors, and optical weights. We showcase these findings in topological systems with non-Hermitian Chern numbers. We demonstrate that the non-Hermitian
geometric constraints on response functions naturally arise in open
quantum systems governed by out-of-
equilibrium Lindbladian dynamics. Our findings are relevant to experimental observables and responses under the realistic setups that fall beyond the idealized closed-system descriptions.
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Fluid Dynamics
Compressibility Effects on Leading-Edge Dynamic Stall Criteria at High Reynolds Number
Sarasija Sudharsan and Anupam Sharma
This study examines the applicability of two leading-edge dynamic stall criteria, namely, the maximum magnitudes of the leading-edge suction parameter (LESP) and the boundary enstrophy flux (BEF), in a moderately compressible flow regime. While previously shown to predict stall onset ahead of dynamic stall
vortex (DSV) formation in incompressible and mildly compressible regimes, these criteria are assessed here at a Reynolds number of $1 \times 10^6$ and freestream Mach numbers between 0.3 and 0.5. Unsteady RANS simulations indicate that DSV formation occurs in close temporal proximity to the attainment of the stall criteria. However, at the highest Mach number considered, stronger shock interaction effects with the shear layer leads to DSV formation prior to the criteria being reached, reducing their predictive accuracy. These findings suggest that while the criteria remain effective at lower Mach numbers, their definitions require modification in compressible regimes where strong shock interactions significantly influence the stall process.
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Optics
Rethinking conditioning in polarimetry: a new framework beyond $\ell^2$-based metrics
Yuxi Cai, An Aloysius Wang and Chao He
A standard procedure to achieve accurate, precise, and fast polarization measurement is to choose analyzing and generating polarization states that yield an $\ell^2$-condition number optimized instrument
matrix. This strategy works well for rotating-waveplate systems, where the accessible polarization states trace a curve on the Poincaré sphere and the corresponding optimization problem is generally well posed. However, it becomes degenerate for
liquid-
crystal-based systems, which can generate arbitrary polarization states, and whose additional degrees of freedom allow the optimization of metrics beyond the $\ell^2$-condition number. Leveraging this unique advantage of
liquid-
crystal polarimeters, we introduce additional performance measures derived from alternative norms and error distributions computed via Monte Carlo simulations to inform the design of measurement schemes. We then experimentally demonstrate their effectiveness in suppressing errors, paving the way for more robust and efficient polarization measurements.
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Plasma Physics
Predicting core transport in ITER baseline discharges with neon injections
Dmitri M Orlov, Joseph McClenaghan, Jeff Candy et al. (+4 more)
Achieving self-consistent performance predictions for ITER requires integrated modeling of core transport and divertor power exhaust under realistic
impurity conditions. We present results from the first systematic power-flow and
impurity-content study for the ITER 15 MA baseline scenario constrained directly by existing SOLPS-ITER neon-seeded divertor solutions. Using the OMFIT STEP workflow, stationary temperature and density profiles are predicted with TGYRO for $1.5 \le Z_{\rm eff} \le 2.5$, and the corresponding power crossing the separatrix $P_{\rm sep}$ is evaluated. We find that $P_{\rm sep}$ varies by more than a factor of 1.7 across this scan and matches the $\sim 100$~MW SOLPS-ITER prediction when $Z_{\rm eff} \simeq 1.6$ or when auxiliary heating is reduced to $\sim 75\%$ of nominal. Rotation-sensitivity studies show that plausible variations in toroidal flow magnitude modify $P_{\rm sep}$ by $\lesssim 20\%$, while AURORA modeling confirms that charge-exchange radiation inside the separatrix is dynamically negligible under predicted ITER neutral densities. These results identify a restricted compatibility window, $Z_{\rm eff} \approx 1.6$–1.75 and $0.75 \lesssim f_{P_{\rm aux}} \le 1.0$, in which core transport predictions remain aligned with neon-seeded divertor protection targets. This self-consistent, model-constrained framework provides actionable guidance for
impurity control and auxiliary-heating scheduling in early ITER operation and supports future whole-device scenario optimization.
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All authors Dmitri M Orlov, Joseph McClenaghan, Jeff Candy, Jeremy D Lore, Nathan T Howard, Francesco Sciortino, Christopher Holland
Optics · Cross-listed from quant-ph
Gauge-Invariant Phase Mapping to Intensity Lobes of Structured Light via Closed-Loop Atomic Dark States
Nayan Sharma and Ajay Tripathi
We present an analytical model showing how the gauge-invariant loop phase in a three-level closed-loop atomic system imprints as bright-dark lobes in Laguerre Gaussian probe beam intensity patterns. In the weak probe limit, the output intensity in such systems include Beer-Lambert absorption, a scattering term and loop phase dependent interference term with optical depth controlling visibility. These systems enable mapping of arbitrary phases via interference rotation and offer a platform to measure Berry phase. Berry phase emerge as a
geometric holonomy acquired by the dark states during adiabatic traversal of LG phase defined in a toroidal parameter space. Manifesting as fringe shifts which are absent in open systems, experimental realization using cold atoms or solid state platforms appears feasible, positioning structured light in closed-loop systems as ideal testbeds for
geometric phases in
quantum optics.
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Optics
Angular momentum flux of twisted light in paraxial and nonparaxial regimes
N.A. Vlasov, N.V. Filina and S.S. Baturin
We present a theoretical framework for the derivation of the $z$-directed total angular momentum density of a Bessel wave and of the corresponding intercepted angular momentum flux in an ideal perfectly absorbing disk model. Exact expressions for these quantities are obtained in both paraxial and nonparaxial regimes. We then analyze several experimentally relevant setups in the large-argument asymptotic of the Bessel functions. By varying the beam wavelength, polarization, and cone angle, we identify several distinct regimes of the intercepted angular momentum flux. Within the ideal absorber model, this intercepted flux may be identified with the corresponding mechanical torque. The results suggest potential applications for size-sensitive probing and controlled flux manipulation within the idealized macroscopic model.
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Applied Physics · Cross-listed from cs.AI
Physics-Informed Neural Networks for Device and Circuit Modeling: A Case Study of NeuroSPICE
Chien-Ting Tung and Chenming Hu
We present NeuroSPICE, a physics-informed neural network (PINN) framework for device and
circuit simulation. Unlike conventional SPICE, which relies on time-discretized numerical solvers, NeuroSPICE leverages PINNs to solve
circuit differential-algebraic equations (DAEs) by minimizing the residual of the equations through backpropagation. It models device and
circuit waveforms using analytical equations in time domain with exact temporal derivatives. While PINNs do not outperform SPICE in speed or accuracy during training, they offer unique advantages such as surrogate models for design optimization and inverse problems. NeuroSPICE's flexibility enables the simulation of emerging devices, including highly nonlinear systems such as ferroelectric
memories.
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