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Physics Physics

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Sunday 24 May

Biological Physics

DNA end tethering through break-induced DNA–protein condensation

Rakesh Das, Tarun Mascarenhas, Nagaraja Chappidi et al. (+2 more)

Cells deploy robust mechanisms to repair DNA damage, safeguarding genomic stability and cellular health, but the physical principles underlying these processes remain incompletely understood. Experiments show in vitro that upon a DNA double-strand break, a DNA–protein condensate can tether the broken DNA ends before they disperse away, a critical step for subsequent repair biochemistry. However, it remains puzzling how such condensation reliably achieves spatiotemporal localization at the break site and captures both broken ends despite intrinsic stochasticity. Here, we propose that broken DNA ends can trigger a conversion of proteins from a soluble state to a condensate-competent state. Combining this idea with Brownian dynamics simulations and theory, we propose a physical mechanism for reliable DNA-end tethering. Simulations show that such break-induced conversion can drive local DNA–protein condensation with two possible outcomes: successful or failed tethering. To rationalize this, we construct an effective free energy landscape, identify the corresponding stationary states, and demonstrate that tethering is governed by a kinetic competition between polymer relaxation and condensation dynamics. Together, our study shows that DNA end-dependent conversion, coupled with DNA–protein condensation, can reliably tether broken DNA ends.
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All authors Rakesh Das, Tarun Mascarenhas, Nagaraja Chappidi, Simon Alberti, Frank Jülicher

Computational Physics · Cross-listed from cs.RO

Learning, locomotion, and navigation of soft synthetic snakes in three-dimensional, heterogeneous environments

Xiaotian Zhang, Ali Albazroun, Tixian Wang et al. (+3 more)

Limbless terrestrial animals exhibit exceptional locomotor versatility and control, currently unmatched by engineered counterparts. Here, we introduce a computational framework that enables soft synthetic snakes to navigate unstructured, heterogeneous 3D terrains. Our approach is grounded in bio-inspired actuation and sensing models that reduce the control complexity inherent to high-degree-of-freedom, continuum bodies. These models are integrated into a reinforcement learning architecture to derive environment-traversing policies. Training first occurs in simplified, homogeneous terrains to learn locomotion primitives. These are then composed into adaptive strategies for complex landscapes. We demonstrate robustness by deploying a snake in high-fidelity 3D environments reconstructed from real-world imaging, achieving reliable navigation. Overall, this work provides a physically-realistic simulation platform and practical insights for the control of continuum systems in natural terrains.
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All authors Xiaotian Zhang, Ali Albazroun, Tixian Wang, Songyuan Cui, Prashant G. Mehta, Mattia Gazzola

Computational Physics · Cross-listed from math.NA

A Guided Tour of Modern Domain Decomposition: From Schwarz Iterations to Robust Preconditioners and HPC Implementations

Victorita Dolean, Pierre Jolivet, Frédéric Nataf et al. (+1 more)

Domain decomposition methods (DDMs) provide a unifying framework for the scalable numerical solution of partial differential equations. Originating from Schwarz's alternating method, they have evolved into a rich family of algorithms that combine local robustness with global convergence acceleration and natural parallelism. Over the past decades, domain decomposition has played a central role in enabling large-scale simulations in numerous applications. This chapter presents an overview of modern DDMs, with a particular emphasis on scalable preconditioning techniques for challenging problems, including indefinite and high-frequency regimes. We revisit the fundamental concepts - overlapping decompositions, partition of unity, additive and restricted Schwarz formulations - and explain their algebraic interpretations. We then clarify their role as preconditioners in Krylov subspace solvers and discuss the necessity of coarse space corrections for scalability. Beyond a the survey aspect, the chapter distills key theoretical insights and practical design principles that have emerged over the past twenty years. Special attention is given to robust coarse spaces (GenEO, DtN-based approaches) and high-performance implementations. The goal is to provide both a coherent overview of the field and a concise, practice-oriented guide for readers seeking to understand and apply domain decomposition methods without navigating the entire literature.
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All authors Victorita Dolean, Pierre Jolivet, Frédéric Nataf, Pierre-Henri Tournier

History and Philosophy of Physics

Physical Coherence and Time's Emergence

Eugene Y. S. Chua

It is often said that time vanishes in quantum gravity. One general approach to quantum gravity accepts this fundamental timelessness but seeks to derive time's emergence at a non-fundamental level. To better assess such approaches, I develop the criterion of physical coherence and situate it in context by applying it to two programs for time's emergence, drawing from recent works by Chua and Callender (2021) and Chua (2025): semiclassical time and thermal time. Unlike some recent arguments for the metaphysical incoherence of time's emergence, which rule out all claims of time's emergence 'from on high' once we've fixed a definition of metaphysical emergence, my criterion of physical coherence leaves open the possibility that some programs in quantum gravity may succeed on their own terms in providing a physically coherent derivation of time from no-time. This sets a challenge for proponents of time's emergence to clarify the conceptual foundations of their program, while at the same time acting as a litmus test for a program's success.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG

RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges

Ruize Li, Zhibin Wen, Tao Han et al. (+5 more)

Accurate evaluation of weather forecasting models is critical for their reliable deployment in real-world applications. However, existing benchmarks predominantly rely on reanalysis products such as ERA5, which are generated through delayed data assimilation and do not reflect the constraints of real-time operational forecasting, thereby resulting in a systematic mismatch between benchmark performance and real-world forecasting. In this work, we introduce RealBench, a next-generation benchmark for AI weather forecasting that emphasizes realistic evaluation under operational conditions. RealBench features a strictly out-of-distribution test set spanning 2025 to eliminate data leakage and capture recent atmospheric regimes. It integrates multiple data sources, including low-latency operational analysis and a large-scale global in-situ observation dataset comprising over 10,000 stations, enabling direct evaluation against real atmospheric measurements. Beyond standard global metrics, RealBench provides a comprehensive evaluation framework for high-impact extreme events, including heatwaves, cold surges, and tropical cyclones, using event-specific metrics that better reflect real-world forecasting priorities. The evaluation results reveal substantial discrepancies between reanalysis-based metrics and real-world performance, particularly concerning extreme events. By highlighting the limitations of existing benchmarks, this work establishes a more faithful and operationally relevant evaluation paradigm, providing a rigorous foundation for advancing next-generation AI weather forecasting systems. The benchmark implementation is available at: https://github.com/lixruize-del/NWP-Benchmark.
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All authors Ruize Li, Zhibin Wen, Tao Han, Hao Chen, Fenghua Ling, Wei Zhang, Song Guo, Lei Bai

Fluid Dynamics

Geometry, elasticity, and activity in the transport of self-propelled filaments in turbulence

Kunal Kumar, Aliv Sahoo, Rahul Kumar Singh et al. (+1 more)

We investigate the transport of elastic active filaments in two-dimensional turbulence, focusing on how propulsion geometry and elasticity determine vortex trapping and transport. Using a bead-spring model with activity applied at the filament head, we compare propulsion that follows the instantaneous filament conformation with propulsion imposed along a fixed external direction. We find that activity does not generically enhance transport: when propulsion remains coupled to the filament backbone, vortex trapping remains dominant and motion stays effectively diffusive, whereas fixed-direction propulsion enables persistent excursions across flow structures and leads to superdiffusive transport. In both cases, activity shifts filament conformations toward more extended states, effectively opposing elastic relaxation without eliminating preferential sampling of coherent vortical regions. At low Weissenberg number, this conformational change is amplified: activity cooperates with elasticity to enhance preferential sampling of vortical regions and strengthen vortex trapping. Transport therefore emerges from a competition between activity, elasticity, and flow-induced deformation, with elasticity determining how effectively activity-induced extensions can persist against turbulent trapping. These results establish propulsion geometry as the key control parameter for transport, with elasticity and activity acting cooperatively rather than independently to shape filament dynamics in turbulent flows.
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All authors Kunal Kumar, Aliv Sahoo, Rahul Kumar Singh, Samriddhi Sankar Ray

Accelerator Physics

Electron beam evolution in a successive Compton backscattering

D.V. Gavrilenko, A.A. Savchenko, M.N. Strikhanov et al. (+1 more)

Inverse Compton scattering (ICS) is a unique source of highly monochromatic x-ray and gamma radiation. We investigate theoretically the cumulative effects of repeated head-on interactions between the electron beam and a train of powerful laser pulses inside a linear accelerating structure placed between mirrors of an optical resonator. We find that the longitudinal momentum spread converges exponentially to an equilibrium value due to the competition between quantum excitation (heating) and radiation friction (cooling). The predictions of the developed theory coincide very well with computer simulations. Our work establishes the necessity to account for cumulative transverse beam dynamics in the design and optimization of future stable, high-brightness ICS sources.
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All authors D.V. Gavrilenko, A.A. Savchenko, M.N. Strikhanov, A.A. Tishchenko

Atmospheric and Oceanic Physics · Cross-listed from cs.CE

Exascale Hybrid Numerical-AI Ensembles for Operational Flood-Season Forecasting in East Asia: 15-km Decadal Hindcasts and 1-km High-Resolution Capability

Mengxuan Chen, Yunpu Xu, Qiuyan Sun et al. (+19 more)

Seasonal forecasting of summer rainfall in East Asia remains a grand challenge, as predictability at 3 to 6 month lead times is constrained by the spring predictability barrier, weak large-scale signals, and localized nonlinear convective extremes. We address this challenge with CAPES, which integrates a kilometer-resolution coupled regional model with atmosphere, land, and ocean components and a data-driven AI seasonal forecasting system. At 15 km resolution, the fused workflow combines 174 numerical members from varying start times, physics schemes, and parameter perturbations with 1,600 AI members generated from initial and physical perturbations. Using the full LineShine system, CAPES completes ten annual 1,774-member hindcasts for 2016 to 2025 within 14.6 hours, improving the mean prediction score from ECMWF's 71.8 to 75.9 and delivering a major gain in operational forecasting capability. The 1-km configuration further enables fine-scale typhoon simulation and establishes the feasibility of kilometer-scale fused ensemble forecasting on a one-week timescale.
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All authors Mengxuan Chen, Yunpu Xu, Qiuyan Sun, Han Zhang, Jiayi Lai, Zheng Zhou, Juepeng Zheng, Hongsong Meng, Nan Wei, Jinxiao Zhang, Xiongchuan Tan, Haodong Bian, Yinan Cai, Ge Yang, Fang Wang, Yunyun Liu, Conghui He, Runmin Dong, Lanning Wang, Yutong Lu, Yongjiu Dai, Haohuan Fu

Chemical Physics

Unravelling Chemical Exchanges Through Steady State Free Precession NMR

Sundaresan Jayanthi, Adonis Lupulescu, Mark Shif et al. (+2 more)

NMR is uniquely endowed to analyze dynamics, with line shape and relaxation measurements covering timescales over several orders of magnitude. Further insight arises from pulse sequences like chemical exchange saturation transfer or relaxation dispersion, which facilitate, respectively, the detectability and shift characterization of even lowly populated states, and the pinpointing of the exact exchange rates. The present study demonstrates that Steady State Free Precession (SSFP) experiments involving a train of pulses with flip angle {\alpha} spaced by repetition times TR, combine valuable features from both these experiments. Indeed, in the presence of chemical exchanges, SSFP yields via its offset-dependent excitation and saturation profiles, detailed information about the number, the chemical shifts and the populations of the exchanging sites even when these involve multiple intermediates with dissimilar abundances. Simultaneously SSFP can provide, via its TR dependence, a controllable timescale yielding kinetic information over a variety of slow/intermediate/fast exchange rates. All this is theoretically demonstrated with the aid of a Liouville-space formalism examining the steady state in the presence of chemical exchange. This formalism leads in both the slow and fast exchange regimes to analytical predictions that match well brute-force numerical calculations, which lend themselves to rapid and accurate fittings of exchange rates, chemical shifts, and site populations. The basic features associated to this novel approach to examine chemical kinetics are experimentally verified on simple model compounds; potential extensions are briefly discussed.
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All authors Sundaresan Jayanthi, Adonis Lupulescu, Mark Shif, Zuzana Osifova, Lucio Frydman

Classical Physics · Cross-listed from astro-ph.HE

Pulse Modulation as a Signature of the Asteroid-Neutron Star Collision Model for High-Energy Transients

Partha Bagchi, Biswanath Layek, Dheeraj Saini et al. (+3 more)

Asteroid-neutron star collision models have been proposed as possible sources of high-energy transients, such as gamma-ray bursts (GRBs) and fast radio bursts (FRBs). The sequence of events following the impact of the asteroid and finally dissolving into the neutron star can have several other observable consequences. We propose that due to the development of the off-diagonal moment of inertia (MI) components, the merger's aftermath can lead to the wobbling of the pulsar (assuming the neutron star happens to be a pulsar). Using sample values of various parameters, viz., size, shape, the locations of the deposits, and the pre-existing pulsar deformation parameter ($\eta$), we calculate the detailed pulse profile modulation of the pulsar. We observe a distinct pattern of pulse profile modulation on a characteristic timescale enhanced by a factor of $1/\eta$ compared to the pulse timing. Importantly, even small changes in the MI components, of order $\epsilon$, can produce large pulse profile modulations of order $\epsilon/\eta$ (depending on the relative location of asteroid material deposition). Thus, if an asteroid-neutron star collision is responsible for a high-energy transient, the associated pulse profile modulation may serve as a falsifiable observational signature of such an event.
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All authors Partha Bagchi, Biswanath Layek, Dheeraj Saini, Anjishnu Sarkar, Ajit M. Srivastava, Deepthi Godaba Venkata

Computational Physics

Machine-learned atomistic simulations reveal the basis of hydrogen-induced crack-plane transition in alpha-Fe

Jiaqin Xu, Zhiqiang Zhao, Kazuma Ito et al. (+4 more)

Hydrogen-related fracture in body-centered cubic Fe and ferritic steels often appears as transgranular quasi-cleavage rather than purely intergranular failure, especially at low to moderate hydrogen contents. Fractography has suggested that hydrogen may change the dominant cleavage faceting from {100} toward {110}, but atomic-scale evidence for this possible crack-plane transition remains unclear. Here we construct an efficient neural-network potential for {\alpha}-Fe/H and combine large-scale, three-dimensional molecular dynamics with grand-canonical Monte Carlo (GCMC), allowing the near-tip crack-surface region and crack tip within a defined GCMC domain to exchange hydrogen with a reservoir at fixed chemical potential. A comparison of four crack systems identifies the controlling response: (100)[010], (100)[011], and (110)[001] remain cleavage-dominated, whereas the (110)[1-10] crack changes from dislocation emission in pure Fe to cleavage under hydrogen charging. The energetic origin is twofold. Hydrogen lowers the Griffith cleavage threshold of the {110} cleavage-plane family more strongly than that of {100}, and, for the controlling crack, a Rice-type energetic descriptor indicates that the surface-energy-controlled cleavage resistance decreases faster than the unstable-stacking-fault-controlled emission resistance, consistent with a weakened dislocation-emission shield. These results provide a thermodynamically consistent atomistic basis for a hydrogen-induced transgranular crack-plane transition in Fe.
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All authors Jiaqin Xu, Zhiqiang Zhao, Kazuma Ito, Shuhei Shinzato, Fanshun Meng, Shihao Zhang, Shigenobu Ogata

Computational Physics · Cross-listed from cs.LG

A comparative study of accuracy and rollout stability of temporal surrogate models

Rajarshi Biswas

Temporal surrogate models are effective for predicting chaotic dynamical systems where computational cost can be prohibitive. Several deep neural network architectures can be used for such purposes. In this work, a few commonly used architectures are compared using a common training protocol. The objective is to fairly assess the impact of model architectures for long-horizon prediction stability. Experiments are carried out for three problems, the double pendulum, the Kuramoto-Sivashinsky equations, and the Kolmogorov flow. The experiments are carried out with matching model capacity. Analysis is also carried out for a scenario where each model is individually optimized. It is observed that in both scenarios, the models exhibit categorical differences in long-horizon rollouts. For a concrete quantification, stepwise error injections and perturbation amplifications are analyzed using metrics such as local jacobian, relative one-step bias, and finite-time Lyapunov growth. Additionally, an attractor analysis is also conducted to assess how well the learned models replicate the underlying system geometry. An ablation study to isolate the impact of each component of a continuous-update architecture is also carried out. It is concluded that models that having integrator-like updates show lower bias and perturbation amplification yielding stable long-horizon rollout and more accurate predictions.
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Optics

Vacuum-Sealed Thermal Treatment Regulates Trap States and Red Persistent Luminescence in CaTiO3: Pr3+,Al3+ Phosphors

Ziyi Guo and Duanting Yan

Red persistent phosphors remain less mature than green and blue-green systems because their afterglow is often weak and decays rapidly. Here, CaTiO3:0.3%Pr3+,0.3%Al3+ phosphors were prepared by a high-temperature solid-state route under either air or vacuum-sealed quartz-tube (QT) conditions. The effects of processing atmosphere and sintering temperature on phase structure, microstructure, steady-state photoluminescence, afterglow, thermoluminescence, and excited-state decay were examined. X-ray diffraction and Raman spectra show that all samples retain the orthorhombic CaTiO3 perovskite phase, with no detectable secondary phase. SEM observations show particle coarsening at higher QT temperatures, while EDS mapping indicates a homogeneous distribution of Ca, Ti, O, Pr, and Al within the examined region. The QT-treated samples exhibit stronger Pr3+ red emission near 612 nm and markedly improved afterglow compared with the air-treated sample. The QT-1300 sample shows the best afterglow among the present samples, with a reported 3.6-fold higher intensity at 1200 s than Air-1200{\deg}C. Thermoluminescence results indicate that QT treatment increases the population of thermally active traps and enhances the deeper trap component. These results suggest that a low-oxygen sealed environment regulates defect-related traps, most likely involving oxygen-vacancy-associated centers, and improves carrier storage and release through the Pr3+ and Ti4+ intervalence charge-transfer pathway. This work provides a practical processing strategy for improving CaTiO3-based red persistent phosphors and offers insight into trap-state regulation under low-oxygen thermal treatment.
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Medical Physics

GRASP MRI: A Decade of Innovation from Bench to Bedside

Li Feng, Kai Tobias Block, Hersh Chandarana et al. (+1 more)

GRASP (Golden-angle RAdial Sparse Parallel) MRI has emerged as one of the most influential motion-robust dynamic MRI frameworks over the past decade. By combining continuous golden-angle radial sampling with compressed sensing and parallel imaging, GRASP enables free-breathing data acquisition with flexible retrospective image reconstruction. Since its original introduction, the framework has evolved substantially and has inspired a broad range of technical developments, including motion-resolved reconstruction, real-time imaging, quantitative MRI, deep learning-enabled reconstruction, and multidimensional cardiovascular imaging. These advances have further expanded the role of GRASP MRI in a range of clinical applications where conventional breath-hold imaging is challenging. This review summarizes the technical evolution and clinical translation of GRASP MRI over the past decade, with a particular focus on the conceptual advantages of continuous radial acquisition, flexible retrospective reconstruction, and motion-robust imaging. Emerging developments in deep learning reconstruction, real-time volumetric imaging, and quantitative free-breathing MRI are also discussed together with future directions of motion-robust MRI acquisition and reconstruction.
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All authors Li Feng, Kai Tobias Block, Hersh Chandarana, Daniel K Sodickson

Optics · Cross-listed from cond-mat.mtrl-sci

Photoluminescence Identification of Multiple Local Eu3+ Environments in BaTiO3 Ceramics

Yutong Cai, Duanting Yan and Hancheng Zhu

BaTiO3 is a model ferroelectric perovskite whose properties are highly sensitive to local structure, defect chemistry, and dopant distribution. However, conventional diffraction mainly probes the average lattice and can miss subtle changes in the local coordination environment. Here we use Eu3+ photoluminescence as a local optical probe for BaTiO3 ceramics prepared at 1250, 1300, and 1350 {\deg}C. X-ray diffraction and Raman spectra show that all samples retain the tetragonal BaTiO3 phase within the detection limits of these techniques. Electron microscopy reveals a porous ceramic microstructure with temperature-dependent grain growth, and elemental mapping confirms a spatially distributed Eu signal. The Eu3+ excitation and emission spectra show strong sensitivity to the processing temperature. The sample sintered at 1250 {\deg}C gives the highest emission intensity, while higher sintering temperatures change the relative intensity of the charge-transfer band and the 4f-4f transitions. Most importantly, the 5D0 to 7F0 emission contains two reproducible components near 579.5 nm and 582.2 nm. Their relative weights vary with sintering temperature, and double-exponential decay at 612 nm further supports the presence of multiple Eu-related local environments. These results show that Eu3+ luminescence provides a sensitive route to track local structural heterogeneity in BaTiO3 ceramics.
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Medical Physics

A Wireless Reconfigurable Metasurface for Enhanced Parallel Magnetic Resonance Imaging

Yuhan Liu, Xia Zhu, Ke Wu et al. (+4 more)

Modern magnetic resonance imaging (MRI) relies on application-specific multi-channel receive coils to achieve high performance, but these coils are typically costly, rigid, and difficult to generalize across anatomies. Recent wireless, low-cost metamaterials offer improved signal-to-noise ratio (SNR) but remain anatomy-dependent, are prone to destructive inter-element interference, and lack demonstrated compatibility with parallel imaging. Herein, a wireless, reconfigurable coaxial loop metasurface (CLM) is introduced as a platform for localized SNR enhancement that can operate either as a standalone element or as an insertable add-on alongside existing clinical receive systems. Through its coaxial architecture and shared current pathways, the CLM establishes a collective in-phase resonant mode that enforces phase-coherent current distributions across all loops, resulting in consistently constructive interference. Benchmarking on a 3.0 T MR system using an 8-loop CLM shows SNR enhancements of up to 14.8-fold and 14.02-fold in the sagittal and axial planes, relative to the birdcage coil (BC). As an add-on to a clinical posterior receive array, it further demonstrates up to 2.9-fold SNR enhancement and compatibility with parallel imaging across ex vivo and in vivo settings. The proposed CLM paves the way toward a new class of reconfigurable and insertable MRI hardware for flexible and system-compatible signal enhancement.
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All authors Yuhan Liu, Xia Zhu, Ke Wu, Artem Kaliaev, Christina A. LeBedis, Stephan W. Anderson, Xin Zhang

Saturday 23 May

Plasma Physics

Semi-analytical representation of the Gaunt-modified Landau-Lifshitz equation in a plane wave

S. A. Shekhanov and C. P. Ridgers

We analyze electron dynamics in a plane electromagnetic wave using the Landau-Lifshitz equation with a quantum radiation reaction correction modelled by a Gaunt factor. In this geometry, the quantum parameter $\chi$ depends solely on the lightfront momentum, allowing the modified equation of motion to retain the integrable structure of the classical problem. We derive a semi-analytical solution for the energy evolution and the four-velocity, which reduces to the known classical result in the appropriate limit. The results provide an analytical and deterministic description of semiclassical radiation reaction in plane-wave fields.
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Medical Physics

Towards Real-World Identification of Fatigued Muscle Groups via Musculoskeletal Simulation

Jenishkumar Chauhan, Samarth Brahmbhatt and Vineet Vashista

Contactless diagnosis of musculoskeletal disorders can potentially improve population health as well as robot behaviours in collaborative settings. However, current diagnosis methods require an in-person physical examination in which a trained physician senses, through contact, the force applied by various muscles. Simulation tools exist, but their use for diagnosis with real data is under-explored. In this paper, we propose an algorithm for identifying which upper-limb muscle group is fatigued. Our algorithm compares the realworld free-space motion of the subject with that of a simulated musculoskeletal model, and is therefore contactless: preventing the need for invasive sensing or in-person assessment. Our algorithm simulates various fatigue conditions using a physics-based musculoskeletal model and extracts diagnostic motion features from both real and simulated data, which are compared for diagnosis. Experimental results on real data demonstrate that the proposed method can reliably distinguish between multiple muscle-groups of fatigue. Additionally, through comprehensive performance comparisons, we show how recent advanced musculoskeletal simulators can be properly configured to address the sim-to-real gap in the context of the fatigue diagnosis task. Our approach can potentially spur further research in remote and automated diagnosis, significantly lowering the barrier to large-scale and early detection.
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Physics Education

A Simple Method of Demonstration of Characteristics of Rainbows Using a Glass of Water and a Few Laser Sources

Soumen Sarkar, Sanjoy Kumar Pal, Pradipta Panchadhyayee et al. (+2 more)

A rainbow is a captivating natural phenomenon resulting from the refraction, dispersion, and reflection of sunlight within water droplets. Traditional classroom demonstrations often focus on qualitative explanations of the formation of rainbows using prisms or water bowls. This study presents a simple experimental approach to analysing the process of rainbow formation through quantitative analysis using a cylindrical glass filled with water, graph paper, and three semiconductor laser sources emitting red, green, and blue light. By measuring the angles of minimum deviation for different wavelengths, we have found that the experimental values closely match the theoretical predictions. This method offers a hands-on, cost-effective approach to enhance students' understanding of the physics behind rainbows.
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All authors Soumen Sarkar, Sanjoy Kumar Pal, Pradipta Panchadhyayee, Shinjinee Das Gupta, Debapriyo Syam

Computational Physics · Cross-listed from cs.LG

Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs

Jinjin He, Zhiqi Li, Sinan Wang et al. (+1 more)

We propose Hermite-NGP, a gradient-augmented multi-resolution hash encoding designed to enable fast and accurate computation of spatial derivatives for neural PDE solvers. Unlike existing NGP-based approaches that rely on automatic differentiation or finite differences and suffer from instability or high cost, Hermite-NGP explicitly stores function values and mixed partial derivatives at hash grid vertices, allowing fully analytic evaluation of gradients, Jacobians, and Hessians via Hermite interpolation. This design preserves the efficiency and spatial adaptivity of NGP while supporting analytic differential operators up to second order. We further introduce a multi-resolution curriculum training strategy analogous to multigrid V-cycles to enable coarse-to-fine optimization. Across a range of 2D and 3D PDE benchmarks, Hermite-NGP achieves up to approximately 20 times lower error than prior neural PDE methods, and reduces wall-clock convergence time by 2 to 10 times compared to other solvers, with per-epoch training times as low as 3.5 ms for models with up to 17M parameters.
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All authors Jinjin He, Zhiqi Li, Sinan Wang, Bo Zhu

Fluid Dynamics · Cross-listed from cs.LG

High-fidelity Modeling of Full-scale Pressurized Water Reactor Flow Fields for Machine Learning Applications

Logan A. Burnett, Hyungjun Kim, Hsien-Cheng Chou et al. (+5 more)

This work presents a high-fidelity computational fluid dynamics (CFD) and data-driven modeling framework for assembly-level flow characterization in a four-loop pressurized water reactor (PWR). A full lower-plenum and core-inlet domain was constructed using publicly available geometry and operating conditions, enabling transient simulations with pump-induced swirl boundary conditions. The results show that cold-leg swirl and lower-plenum transport generate strongly heterogeneous assembly-wise inlet flow distributions, particularly near the lower core region, while axial resistance and mixing progressively homogenize the flow at higher elevations. These physics-informed datasets were subsequently used to evaluate machine learning (ML) applications for partial field reconstruction and short-term autoregressive prediction. A 3D convolutional-based inpainting model successfully recon-structed missing assembly-level mass flow rates from partial observations, with errors concentrated in the highly turbulent base (bottom) layer and diminishing significantly in upper layers. Comparative analysis across multiple ML models demon-strates that spatially aware architectures, particularly ConvLSTM, significantly outperform sequence-based (LSTM) and operator-learning (DeepONet) approaches by effectively capturing coupled spatio-temporal dynamics. The study also high-lights key challenges, including the sensitivity of inlet flow predictions to turbulence and mesh resolution, as well as the absence of full-scale experimental validation data. Despite these limitations, the results remain consistent with expected physical behavior. Overall, this work establishes high-fidelity CFD as a critical foundation for developing data-driven surrogates, sparse sensing strategies, and future multiphysics coupling frameworks.
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All authors Logan A. Burnett, Hyungjun Kim, Hsien-Cheng Chou, Arsha Witoelar, Robert A. Brewster, Benoit Forget, Emilio Baglietto, Majdi I. Radaideh

Chemical Physics

Transport-preserving neural ab initio scattering kernels for rarefied binary gas mixtures

Ehsan Roohi

Neural surrogates for molecular scattering provide a route to continuously evaluable and differentiable direct simulation Monte Carlo (DSMC) collision kernels, but a small pointwise deflection-angle error is not sufficient evidence that a learned map is kinetically reliable. Diffusion, viscosity, representative collision rates, angular redistribution, and mixture relaxation are nonlinear functionals of the same scattering measure. We therefore develop a multiscale validation framework for neural ab initio scattering kernels that combines angular regression, transport cross sections, Ohr-style representative quantities, cumulative angular measures, Fourier spectral content, impact-grid and angular-noise robustness, loss-ablation diagnostics, and three solver-level DSMC mixture tests. The framework is demonstrated on a refined argon–argon Jäger table and on helium–argon ab initio EPAPS data of Sharipov and Benites represented by a neural equal-area scattering surrogate. For He–Ar over $\Er/\kb\ge10~\mathrm{K}$, the surrogate preserves $\QD$, $\Qmu$, $\Qmu/\QD$, $\RCS$, and $\SigVSS$ within $0.75\%$, $1.37\%$, $0.84\%$, $1.21\%$, and $1.46\%$, respectively. The cumulative angular measure agrees within $1.43\%$, the median relative $L_2$ error of $\chi(q)$ is $3.4\times10^{-3}$, and the high-mode spectral-energy ratio is essentially unbiased. The same neural He–Ar kernel is then embedded in periodic DSMC mixture problems that separately probe mass diffusion, momentum diffusion, and two-dimensional field-level mixing. A sinusoidal composition mode is reproduced over three independent realizations with a mean normalized-history error of $1.28\pm0.22\%$ and $D_{\NN}/D_{\EPAPS}=1.015\pm0.013$. A transverse shear wave is reproduced with a $1.58\%$ history error and $\nu_{\NN}/\nu_{\EPAPS}=0.989$.
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Optics

Fundamental limits in photonics and electromagnetics: a tutorial

Owen D. Miller and Francesco Monticone

Theoretical limits and physical bounds across many areas of science, mathematics, and technology – including Shannon's information-capacity limits, Bennett and Landauer's thermodynamic limits on computation, and Gödel's incompleteness theorem in formal logic – serve as defining pillars of their fields. In photonics and electromagnetism, numerous physical bounds and constraints have likewise been uncovered over the past several decades. In this Tutorial, we first review the fundamental principles that constrain light-matter interactions, and then discuss limits at different hierarchical scales, from optical material responses to wave propagation, scattering, and related optical phenomena and functions, relevant to a wide range of applications. By providing a more unified treatment of these results and highlighting the many open questions that remain, our goal is to help readers rapidly get up to speed with the frontier of this research area and contribute to advancing the broader vision of a universal framework for fundamental limits of light interactions with matter.
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Instrumentation and Detectors

Towards 6D Tracking: A Study Of Using Fast-Timing For Measuring Track Position, Time, And Angles

Victor Turbiner, Elena Villhauer, Saveer Jain et al. (+7 more)

Next-generation particle trackers will incorporate precision timing with resolutions of tens of picoseconds. Using two-dimensional TCAD simulations of Low-Gain Avalanche Diodes (LGADs) with a $25~\mathrm{\mu m}$ pitch and $75~\mathrm{\mu m}$ thickness, we show that tilted tracks traversing multiple pixels produce systematic inter-pixel timing differences of hundreds of picoseconds. These differences must be corrected for in cluster hit time reconstruction, but they also encode the track angle. We derive an analytic linear model relating inter-pixel timing differences to the track angle, and determine the sign of the angle, which the cluster shape cannot provide, using an amplitude-weighted method. For tracks crossing at least three pixels, this enables single-layer angle reconstruction with a resolution of $2^\circ-3^\circ$ and, after a simple numerical inversion, a bias below $1^\circ$. The dominant limitation arises from large Landau fluctuations: non-uniform charge deposition along the track induces inter-pixel crosstalk that distorts the timing signals. Affected tracks can be identified and rejected using the total cluster charge. Neural networks that additionally exploit nonlinear correlations and pixel charge improve the resolution to approximately $1.7^\circ$, indicating that the computationally inexpensive linear model captures most of the available angular information. These results provide a path toward 6D tracking, in which each detector layer measures track position, time, and angles.
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All authors Victor Turbiner, Elena Villhauer, Saveer Jain, Abhiraj Gupta, Michael Cardiff, Julie Segal, Christopher J. Kenney, Mark Horowitz, Ariel Schwartzman, Angelo Dragone

Optics · Cross-listed from cond-mat.mes-hall

Quantum Printing: Laguerre-Gaussian Beam Induced Topological Magnetic Textures

Yuefei Liu, Tien-Tien Yeh and Alexander V. Balatsky

Structured light has become a practical tool for controlling matter by applying tailored, space- and time-dependent electromagnetic fields. We show that Laguerre-Gaussian pulses imprint non-collinear magnetic textures via the spatial structure of optical magnetic field. Our route offers a direct spatial selectivity determined by the optical features without relying on material anisotropic interactions. The proposed printing approach does not require interfacial anisotropy or bulk chirality, current-driven torques, or thermal quenching. We use micromagnetic simulations to demonstrate the potential to create topological charge density emerging during the pulse and reveal control through the optical topological properties and polarization. These results suggest structured-light quantum printing as a viable approach for magnonics and motivate studies toward reconfigurable topological textures enabled by ultrafast THz optics and non-thermal control.
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Classical Physics

Simple Pendulums in Simple Harmonic motion

Adel H. Alameh

The motion of a simple pendulum in a uniform gravitational field can be described by the solution of a second-order differential equation, nonlinear differential equation. In practice we solve this equation using the small angle approximation relying on students familiarity with simple harmonic motion. This paper presents a straightforward method of finding the time equation of motion of a simple pendulum for small angular amplitudes, without having any recourse to solving the differential equation that governs its oscillations. This method relies on finding the indefinite integral of a certain relation derived from the conservation of mechanical energy of the system (Pendulum-Earth). And shows no need to the mathematical complexities in which differential equations are involved.
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Fluid Dynamics

A contaminant-concentration-dependent surface tension does not explain the absence of solutal Marangoni flow in evaporating droplets

Javier Martínez-Puig, Théophile Gaichies and Javier Rodríguez-Rodríguez

Theoretical models of evaporating droplets predict Marangoni flows orders of magnitude faster than those observed experimentally. While this discrepancy is often attributed to surface contamination, the underlying mechanism by which contaminants weaken Marangoni stresses remains unclear. In this study, we compare particle image velocimetry (PIV) experiments with a coupled hydrodynamic and solute transport model to investigate the internal flow of evaporating aqueous droplets containing salt, glycerol, or ethanol. By analyzing both sessile and pendant droplets, we demonstrate that the flow is driven entirely by natural convection, in contrast to theoretical predictions that use surface-tension gradients. Remarkably, in some cases, the experimental surface velocity is found to be directed against the predicted surface-tension gradient. We further prove that commonly used contamination models—whether based on surfactants lowering the surface tension or on surface rheology—cannot account for this flow reversal, as they would require the surfactant to be transported against the flow when the surface velocity is opposed to the surface-tension gradient. Our results show that a reconsideration of these models is required to explain the absence of solutal Marangoni in evaporating droplets.
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Applied Physics

Universal square-root-log scaling for slender-body end effects

Gunnar Peng and Ory Schnitzer

The charge on a conducting cylinder becomes uniformly distributed at large aspect ratios, albeit very slowly and with nonuniformity persisting near the ends. We show that the charge density and field magnitude are enhanced near the ends by a factor scaling as the square-root of the logarithm of the aspect ratio. This scaling is obtained by locally resumming a perturbation-series solution to the integral equation of slender-body theory. The same scaling applies to a broad class of "truncated" slender bodies – including cylinders and shapes tapered near the ends on the cross-sectional scale – as well as other physical setups. We validate this scaling through boundary-element simulations for cylinders with flat and hemispherical caps, and demonstrate its applicability to diffusion, plasmonics and Stokes flow.
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Physics and Society

Quantifying concurrency in event-based temporal network and hypergraph data

Jiyoung Kang, Hang-Hyun Jo and Naoki Masuda

Many social, biological, and technological systems are recorded as sequences of time-stamped interactions. In such systems, concurrency, i.e., the tendency for an individual to participate in multiple interactions approximately at the same time, can strongly affect processes such as epidemic or information spreading. However, concurrency measures for event-based temporal network data are not established. We introduce edge-event correlation (EEC), a simple and interpretable measure that quantifies how similarly two connections are active over time. We apply EEC to empirical temporal networks and temporal hypergraphs, the latter allowing single events to involve more than two nodes. Across most datasets, pairs of edges or hyperedges that share a node show higher concurrency than pairs that do not. We further find that this elevated concurrency is mainly driven by pairs embedded in closed local structures, such as triangles in the aggregated network. EEC provides a practical tool for quantifying concurrency in event-based temporal data and may help identify network structures that facilitate rapid spreading or collective dynamics.
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Chemical Physics · Cross-listed from quant-ph

Transformer refined quantum sampling for strongly correlated electronic structure

Xiongzhi Zeng, Ming Gong, Bowen Kan et al. (+18 more)

Although quantum computing offers a promising solution for strongly correlated system simulation, existing algorithms face significant bottlenecks on current noisy intermediate-scale quantum (NISQ) devices. Here, we introduce QiankunNet-QSCI, a hybrid quantum-classical framework that addresses this challenge by combining efficient quantum-sampling with a transformer neural network. An efficient unitary selected configuration Interaction (USCI) ansatz especially designed for quantum sampling is proposed to identify the most chemically significant electronic configurations on the Zuchongzhi 3.1 quantum processor. Subsequently, the transformer model QiankunNet learns from these sparse yet critical quantum data to infer and reconstruct the complete electronic wavefunction with high fidelity. Simulation of the challenging 40-qubit [2Fe-2S] ferredoxin active center achieves chemical accuracy. Simulation of the nitrogenase P-cluster in a 114-electron 73-orbital active space also reaches 12 milli-Hartree-level agreement with the best density matrix renormalization group (DMRG) result. QiankunNet-QSCI thus offers a practical route to accurate quantum-assisted electronic structure calculations on current devices.
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All authors Xiongzhi Zeng, Ming Gong, Bowen Kan, Yi Fan, Huan Ma, Jianbin Cai, Yancheng Liu, Naibin Zhou, Tao Jiang, Shaojun Guo, Zhijie Fan, Zongkang Zhang, Yuan Li, Sirui Cao, Kai Yan, Xiaobo Zhu, Yi Luo, Honghui Shang, Zhenyu Li, Jian-Wei Pan, Jinlong Yang