Atomic Physics
Role of Metastable Dicationic Intermediates in the Breakup of CH$_4^{2+}$
Samiksha Dehru, Evan Munaro-Langloÿs, Aditya Yadav et al. (+8 more)
We investigate the fragmentation dynamics of methane dication (CH$_4^{2+}$) produced in collisions with 50-MeV C$^{6+}$ ions using the COLTRIMS technique. The method provides complete three-dimensional momentum vectors of the charged fragments, enabling full kinematic reconstruction of the fragmentation process. The dynamics are analyzed using Dalitz plots, Newton diagrams, and the native-frame method to distinguish between concerted and sequential dissociation mechanisms. The data indicate the presence of sequential fragmentation pathways for the CH$_4^{2+}$ $\rightarrow$ CH$_2^+$ + H$^+$ + H, CH$_4^{2+}$ $\rightarrow$ CH$^+$ + H$^+$ + 2H, and CH$_4^{2+}$ $\rightarrow$ C$^+$ + H$^+$ + 3H channels, consistent with dissociation via short-lived dicationic intermediates CH$_3^{2+}$, CH$_2^{2+}$, and CH$^{2+}$, respectively. From the Newton-diagram momentum distributions, we further estimate the half-rotational periods of the intermediate states, providing insight into their rotational dynamics and finite lifetimes prior to fragmentation. The experimental observations are further supported by comparisons with calculated potential-energy curves.
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All authors Samiksha Dehru, Evan Munaro-Langloÿs, Aditya Yadav, Siddhanta Barnowal, Manojit Das, Harpreet Singh, Jibak Mukherjee, Rajarshi Sinha-Roy, Victor Despré, Deepankar Misra, Arnab Khan
Fluid Dynamics
An Architecture-Agnostic High-Order Discontinuous Galerkin Framework for Compressible Flows
Spencer Starr, Yannik Feldner, Patrick Kopper et al. (+6 more)
With the recent proliferation of heterogeneous, GPU-accelerated supercomputers, high-order computational fluid dynamics (CFD) simulations of complex, turbulent flows are more accessible than ever. To leverage the computing power of these machines, CFD software must adapt. However, complicating the situation is the emerging need to support hardware from multiple GPU vendors. Addressing this need is the GPU-accelerated, discontinuous Galerkin spectral element method (DGSEM) framework GALÆXI, a high-order, open source, architecture-agnostic toolchain for the study of complex, compressible, turbulent flows on unstructured, hexahedral grids. GPU-accelerated computations with GALÆXI are possible on GPU hardware by interfacing Fortran source code to the vendor models CUDA C++ for NVIDIA and HIP C++ for AMD. The DGSEM implementation in GALÆXI was verified using the method of manufactured solutions to rigorously confirm the expected order of convergence. Simulations of a compressible Taylor-Green-
Vortex also demonstrated excellent agreement with reference solutions across all supported architectures. GALÆXI achieved near ideal strong and weak scaling on GPU hardware from both NVIDIA and AMD. In the largest case, GALÆXI performed a simulation with 67.1 billion degrees of freedom on 65,536 AMD MI250X graphics compute devices with a parallel efficiency of 82.6%. Comparing node-to-node performance, GPU simulations offered speedups between 7.75x and 8.08x over CPU computations in time-to-solution while consuming less than half the energy. To demonstrate GALÆXI's effectiveness for production-scale simulations, wall-resolved large eddy simulations of the transonic flow past a NACA 64A-110 airfoil and an ONERA OAT15A airfoil under shock buffet conditions were computed.
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All authors Spencer Starr, Yannik Feldner, Patrick Kopper, Marcel Blind, Daniel Kempf, Jannik Schrempp, Felix Rodach, Andrea Beck, Anna Schwarz
Computational Physics · Cross-listed from cond-mat.stat-mech
AI estimation of partition functions with the PULSE method for the thermodynamic properties of disordered compounds
Baptiste Bernard, Luca Messina, Eiji Kawasaki et al. (+1 more)
Predicting the thermodynamic properties of chemically disordered materials is constrained by the combinatorial growth of possible atomic configurations, which makes conventional sampling approaches computationally costly. In this work, we extend the PULSE (Partition function Unsupervised Learning Sampling and Evaluation) approach that enables the estimation of observable-dependent partition functions, thereby extending its applicability from local atomic quantities to general thermodynamic observables. This is based on a generative machine-learning approach in which a single model both generates statistically representative atomic configurations and provides explicit partition function estimates. Our primary goal is to assess it on the two-dimensional Ising model, an exactly solvable
benchmark system sharing the same statistical-mechanical formulation as chemically disordered binary materials, and compare its performance against exact brute-force calculations as well as Wolff and Wang-Landau Monte Carlo
algorithms. PULSE reproduces the relevant partition functions accurately using a limited number of configurations, at a sampling cost that does not grow with system size. These key results demonstrate the relevance of our method to enable the study of disordered materials at scales that are difficult to achieve using conventional approaches, and with limited computational effort.
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All authors Baptiste Bernard, Luca Messina, Eiji Kawasaki, Emeric Bourasseau
Computational Physics
Surface Contact Approximation for Magneto-Thermal Finite Element Analysis of No-Insulation HTS Coils
Erik Schnaubelt, Louis Denis, Mariusz Wozniak et al. (+2 more)
High-temperature superconducting (HTS) coated conductors (CCs) can be wound into no-insulation (NI) coils, in which electrical current can partially bypass local normal zones via turn-to-turn contact layers (T2TCLs). Accurate magneto-thermal simulation of such coils, therefore, requires an efficient representation of the electrical and thermal behavior of the T2TCLs. This paper introduces a magneto-thermal surface contact approximation (SCA) for finite element analysis of NI HTS coils. The formulation is derived as a special case of the more general thin shell approximation (TSA) by introducing suitable approximations such as negligible tangential surface currents and eddy-current effects inside the T2TCL. The resulting SCA formulation replaces the thin volumetric contact layer with a dedicated surface weak formulation based on the electric contact resistance and thermal contact conductance. In contrast, the TSA formulation requires the definition of electric resistivities and thermal conductivities as well as the thickness of the T2TCL. The SCA is implemented in the Pancake3D module of the free and open-source Finite Element Quench Simulator. It is verified through transient magneto-thermal simulations of a model NI pancake coil. Numerical results are compared against the established TSA formulation. The results show that the SCA accurately reproduces the relevant electromagnetic and thermal behavior. For the TSA, there is a trade-off between choosing large (potentially unphysical) thicknesses with low resistivities leading to inaccurate results, or small thicknesses with large resistivities making the linear system harder to solve, increasing the computational effort. In contrast, the SCA, thanks to using contact resistances and conductances directly without the necessity to define a thickness, is easy to use and robust.
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All authors Erik Schnaubelt, Louis Denis, Mariusz Wozniak, Julien Dular, Arjan Verweij
Optics · Cross-listed from eess.SP
Unified Analytical Framework for SPAD Array Receivers with Dead-Time-Induced Blocking Loss and Inter-Symbol Interference in PAM-OWC Systems
Chen Wang, Zhiyong Xu, Jingyuan Wang et al. (+3 more)
Optical wireless communication (OWC) leveraging single-
photon avalanche diode (SPAD) arrays offers exceptional sensitivity for
photon-starving links. However, the inherent dead time of SPADs critically limits achievable data rates by introducing non-linear
photon-counting distortions: blocking loss within a symbol duration and inter-symbol interference (ISI) across durations. This paper proposes a unified analytical framework capturing both distortions across all operational speed regimes for pulse-amplitude modulation (PAM), by establishing comprehensive statistical models for SPAD array receivers. For low and medium-speed systems (symbol duration longer than dead time), we derive exact closed-form expressions for the
photon counts probability distribution using renewal theory, explicitly incorporating blocking loss and ISI. For high-speed systems (symbol duration shorter than dead time), we develop a Markov chain model characterizing the steady-state operational states and integrate it with trigger probability to obtain the exact binomial
photon counts distribution. Furthermore, we propose low-complexity, near-optimal threshold detection schemes based on these models. This work provides essential theoretical tools for designing and optimizing high-performance SPAD-based OWC systems employing PAM.
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All authors Chen Wang, Zhiyong Xu, Jingyuan Wang, Jianhua Li, Weifeng Mou, Huatao Zhu
Instrumentation and Detectors
Development and Characterization of a Time Projection Chamber Prototype for Neutron Oscillation Searches at the European Spallation Source
Blahoslav Rataj, Valentina Santoro, Anders Oskarsson et al. (+3 more)
A compact time projection chamber (TPC) prototype was studied for charged-pion tracking in the annihilation detector proposed for the HIBEAM experiment at the European Spallation Source. HIBEAM aims to search for
neutron-antineutron oscillations, where a produced antineutron would annihilate on a carbon target and produce a pionic final state. A tracking
algorithm was developed and validated using
cosmic-particle measurements expected to be dominated by atmospheric
cosmic muons,
proton elastic-scattering data from the Cyclotron Centre Bronowice, and simulated TPC event data.
Cosmic measurements provided a minimum-ionising reference for pion-like tracks, while
proton-scattering data tested reconstruction in a more highly ionising environment. Simulated crossing-track events were used as a stress test of complex
topologies. The
algorithm performed reliably for well-separated tracks, while crossing or overlapping tracks and dense
proton-scattering events reduced performance. In experimental data, reconstructed tracks showed sub-millimetre residual widths, robust charge sharing supporting the zigzag-shaped readout, and uniform measured dE/dx across the drift volume. The truncated-mean track-level dE/dx distribution in
cosmic data showed an approximately Gaussian peak with a relative width of about 16%, demonstrating how energy-loss information can be used for particle identification. Tilted
proton tracks showed broader residuals in yz, because the pad row signal was extended in time. A sub-centroid refit technique was proposed, using the internal ADC time profile within a pad row instead of a single charge-weighted time position. With four equal-y sub-centroids per pad row, the yz residual width was reduced from 1.30 mm to 0.55 mm. These results validate the initial tracking capabilities of the
algorithm and prototype, and provide feedback for the next-generation prototype.
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All authors Blahoslav Rataj, Valentina Santoro, Anders Oskarsson, Matthias Holl, Verena Hehl, David Silvermyr
Fluid Dynamics
Parametric Subharmonic Instability in the Ocean Bottom Boundary Layer
Logan Knudsen, Jacob Wenegrat, James Hilditch et al. (+1 more)
Internal waves with frequency larger than twice the local minimum allowable wave frequency can be susceptible to parametric subharmonic instability (PSI). This instability draws energy from the wave and provides a mechanism for generating small-scale
turbulence and mixing. In the ocean, strongly baroclinic flows at the submesoscale adjust the minimum frequency of internal waves such that it is possible for PSI to occur for locally near-inertial waves. One setting where this may occur is in baroclinic bottom boundary layers along sloping topography, where near-bottom interior flows in the sense of Kelvin-wave propagation lead to a reduction of bottom boundary layer Ertel potential vorticity, and consequently lower the minimum frequency sufficiently to allow PSI. Linear stability analysis, and nonlinear simulations, show that PSI grows at a rate determined by the vertical stratification of the bottom boundary layer, and the slope Burger number. Wave shear production is the primary energy source for the instability, with additional contributions from buoyancy production that depend on the slope parameters. A partially compensating loss of energy to geostrophic shear production becomes increasingly important as the flow approaches the marginally stable state. These results suggest PSI as a potential mechanism for generating near-bottom mixing in the ocean.
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All authors Logan Knudsen, Jacob Wenegrat, James Hilditch, Leif Thomas
Accelerator Physics
A Method for Passive Streaker LPS Reconstruction
Sergey Tomin and Igor Zagorodnov
Understanding the electron beam distribution in the longitudinal phase space (LPS) is crucial for free electron
laser (FEL) facilities. Conventionally, LPS diagnostics utilize
radio frequency (RF) deflecting structures to streak the electron beam transversely, mapping the longitudinal bunch distribution onto a transverse plane for observation. However, RF structures are complex and costly, especially for high-energy machines like the European XFEL. Wakefield structures have emerged as a promising alternative, offering simplicity in construction and minimal maintenance costs. However, they suffer from nonlinear streaking, requiring image reconstruction for LPS distribution. Several iterative
algorithms have been developed for LPS reconstruction using passive wakefield streakers in recent years. This paper proposes a simple, computationally efficient method tailored for cases with known beam current profiles.
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Computational Physics · Cross-listed from cs.CE
Unified sparse framework for large-scale simulations using the material point method
Yidong Zhao, Lars Blatny, Xiang Feng et al. (+3 more)
The material point method (MPM) is a hybrid particle-grid method widely used for large deformation problems with history-dependent behavior, including geophysical mass flows. Standard MPM often relies on a dense background grid, which can be highly inefficient when material occupies a small fraction of the computational domain. Such sparsity is common in many large-scale geophysical mass flow problems. Here, we introduce a unified sparse background-grid framework for large-scale MPM simulation. The framework treats sparse grid construction as a general active-node indexing problem. We develop two architecture-specific implementations to realize the same sparse framework: a scan-based strategy for CPUs and a hash-based strategy for GPUs. Through
benchmark problems and a large-scale landslide simulation, we show that the framework provides identical results as standard dense MPM while reducing computational time and
memory usage by one to two orders of magnitude in strongly sparse cases.
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All authors Yidong Zhao, Lars Blatny, Xiang Feng, Mikkel M. Juel, Chenfanfu Jiang, Johan Gaume
Atomic Physics
Optical cycling on thorium monoxide (ThO) for an improved test of fundamental symmetries
Alexander Frenett, Dorothy Gan, Nicholas Emtage et al. (+3 more)
Optical cycling refers to repeated excitation and spontaneous emission on an electronic transition in an atom or molecule. Optical cycling in molecules can enable a wide range of
quantum control and readout techniques, but unfortunately it has only been demonstrated on a small class of alkali-like or alkaline-earth-like molecules. Thorium monoxide (ThO), a molecule used in one of the most precise permanent electron electric dipole moment (eEDM) searches (ACME [1]), does not fall into this category. In this work, we demonstrate the first optical cycling on this non-conventional class over a range of experimental parameter space, including
laser intensity, polarization switching rate, and interaction time. We show that both the $J = 1, 2$ rotational levels of ThO molecule are capable of cycling $11(2)$
photons on average with a single
laser, at $1.9(6) \times 10^{6}~\mathrm{s}^{-1}$ and $2.3(7)\times 10^6~\mathrm{s}^{-1}$ scattering rate, respectively, before population is lost to other vibronic levels. We outline a scheme to apply this demonstrated optical cycling in an ACME-style eEDM measurement, improving the detection efficiency by over fourfold compared to non-cycling fluorescence detection. This would lead to over a twofold enhancement in the statistical sensitivity of the eEDM search. This optical cycling scheme can be further extended to scatter about 100
photons, which would enable a wider range of
quantum control and sensing using ThO molecules. [1] V. Andreev, D. G. Ang, D. DeMille, J. M. Doyle, G. Gabrielse, J. Haefner, N. R. Hutzler, Z. Lasner, C. Meisenhelder, B. R. O`Leary, C. D. Panda, A. D. West, E. P. West, and X. Wu, Nature 562, 355 (2018).
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All authors Alexander Frenett, Dorothy Gan, Nicholas Emtage, Monika Fouad, Sebastian Miki-Silva, Xing Wu
Optics
Toward Micro-Endoscopy: Distal-Free, Configuration-Agnostic Focusing Through Multimode Fiber
Dvir Marsh, Lior Fridman, Stav Lotan et al. (+3 more)
Multimode fibers (MMFs) can transmit multiple guided modes simultaneously, making them a promising platform for high-resolution biomedical imaging, endoscopy and high-bandwidth optical communication. However, their complex modal behavior, influenced by environmental perturbations and mode coupling, presents a major challenge for accurate wavefront control. Conventional approaches for shaping the light at their output typically rely on the transmitted field as a source for iterative feedback, making it impractical for in-situ applications where direct access to the transmission is impossible. Here, we introduce a deep learning-based framework for predicting transmission through MMF by observing only the reflected signal. Harnessing the reflected signals that encode the fiber's internal configuration, our approach not only generalizes across varying fiber conditions but also enables focusing through the fiber without requiring transmission feedback. By training the system experimentally using a
dataset of 4 million images across 1200 distinct fiber configurations, we demonstrate robust and precise wavefront reconstruction even under significant perturbations. Our results underscore the potential of learning-based techniques for real-time MMF-based imaging and optical communications, paving the way for efficient non-invasive focusing in practical applications.
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All authors Dvir Marsh, Lior Fridman, Stav Lotan, Amit Kam, Shie Mannor, Guy Bartal
Computational Physics · Cross-listed from math.NA
Wigner-Eckart Factorization of the Spectral Boltzmann Collision Operator
René R. Hiemstra, Torsten Keßler and Michael R.A. Abdelmalik
We reduce the eight-dimensional weak form of the bilinear Boltzmann collision operator to a five-dimensional kinematic core by rigidly rotating the laboratory frame to align with the colliding pair and integrating over the $\mathrm{SO}(3)$ rotation group. This reduction yields an exact Wigner–Eckart factorization within a spectral Galerkin framework of associated Laguerre
polynomials and spherical harmonics. The decomposition decouples the angular geometry from the scattering physics. The former, represented by Clebsch–Gordan coefficients, is evaluated exactly, while the latter is evaluated to machine precision by a spectrally convergent singular quadrature strategy. By explicitly zeroing specific entries, the macroscopic collision invariants are embedded without approximation. Cache-optimized contractions deliver up to a 37-fold single-core speedup and a 1000-fold
memory reduction over standard dense Cartesian formulations. The approach is validated against analytical solutions for Maxwell molecules and infinite-order Chapman–Enskog viscosity coefficients for hard spheres.
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Optics · Cross-listed from cond-mat.mes-hall
Substrate-driven topological engineering in plasmonic Su-Schrieffer-Heeger chains
Florian Herz, Alireza Naeimi and Svend-Age Biehs
We demonstrate the possibility of engineering the topological band structure of a plasmonic Su-Schrieffer-Heeger (SSH) chain through the interaction with its electromagnetic environment. We find that the long-range interaction of the in-plane modes of the SSH chain with the surface plasmon polaritons of a planar substrate introduces a band hybridization connected to a change of the Zak phase. On the other hand, the short-range interaction with the substrate introduces a band touching, again with a change in the Zak phase. Surprisingly, this second mechanism enables the emergence of topologically protected edge modes for parameters which correspond to the topologically trivial phase for an isolated plasmonic SSH chain. We study these mechanisms by changing the chain-substrate distance and the dimerization parameter. Finally, we discuss the robustness against disorder and, as one example, the impact of the observed effects on the near-field radiative heat transfer and the local density of states along the chain. Our findings pave the way to the engineering of edge modes in plasmonic topological configurations via the coupling to a plasmonic environment.
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Optics
Simultaneous Measurement of Circular Dichroism and Circular Differential Scattering
Qiang Hao, Pathum Wathudura, Huy Pham et al. (+7 more)
Chiroptical spectroscopy provides a non-invasive, label-free approach for resolving microscopic structural details via interactions with circularly polarized light. Despite the widespread application and complementary information provided for chiroptical materials characterization, the simultaneous acquisition of circular dichroism (CD) and circular differential scattering (CDS) spectra has remained challenging. In this work, we develop a dual-channel spectrometer that enables the acquisition of CD and CDS spectra from the same solution. To address the challenge of CDS baseline correction, we introduce a scattering spectral matching method. The performance of the instrument is validated using two representative model systems: a mixture of ammonium d-10 camphor sulfonate and polystyrene nanoparticles (PSNPs), and plasmonic gold helicoid nanoparticles, which exhibit both
chiral absorption and scattering. For the former case, the CDS spectra show opposite signs to the CD spectra because the PSNPs are achiral scattering particles and the CDS spectra are affected by the
chiral absorption. For the latter case, both CD and CDS spectra exhibit matched resonance wavelengths and stronger responses to the right-handed circularly polarized light, indicating that the
chiral absorption and scattering arise from the same plasmonic resonance modes. To the best of our knowledge, this work represents the first experimental demonstration of the concurrent acquisition of ensemble-averaged CD and CDS spectra. The presented technique enables a direct and accurate comparison of CD and CDS spectra acquired under identical conditions.
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All authors Qiang Hao, Pathum Wathudura, Huy Pham, In Han Ha, Abrahan Martinez, Justin Lovett, Nicholas C. Fitzkee, Ki Tae Nam, Shengli Zou, Dongmao Zhang
Physics Education · Cross-listed from quant-ph
Learning shape resonances from the stabilization method
Daniel Kromm, Hans-Werner Hammer and Artem Volosniev
Resonances in
quantum mechanics are commonly introduced as quasi-bound states embedded in the continuum, a perspective that can be conceptually challenging due to the abstract nature of continuum states. In this work, we discuss an alternative approach that avoids an explicit treatment of the continuum by formulating the problem in terms of discrete
quantum states. Our discussion is based on the stabilization method, in which the system is confined to a finite region such that the continuum is replaced by a discrete energy spectrum. Resonances then appear as characteristic features in the energy levels under variation of the confining box size, providing an intuitive interpretation in terms of a two-level system while remaining closely connected to standard
quantum mechanics curriculum. We review the method, derive selected results, and discuss practical strategies for extracting resonance parameters from stabilization diagrams. In addition to established fitting procedures, we introduce a novel approach based on the analysis of spatial localization of resonant states, which enables a robust identification of resonance properties. The approach is illustrated using both attractive and repulsive delta-shell potentials, which serve as simple and instructive model systems amenable to analytical treatment.
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Instrumentation and Detectors
Performance evaluation of GYGAG crystals for neutrinoless double beta decay search
Hibiki Hayasaki, Keishi Hosokawa, Koichi Ichimura et al. (+6 more)
Neutrinoless double beta decay (0$\nu\beta\beta$) is a crucial for confirming
neutrinos' Majorana characteristics. Previous searches for 0$\nu\beta\beta$ decay of $^{160}$Gd using GSO
crystals was conducted, but the sensitivity was limited by background $\alpha$-rays from radioactive
impurities. To distinguish the backgrounds, PSD (Pulse Shape Discrimination) and energy resolution are essential. GAGG (Gd$_{3}$(Al, Ga)$_5$O$_{12}$) is a $^{160}$Gd-containing
crystal that exhibits a higher light yield than GSO and excellent PSD capabilities. GYGAG (Gd$_{3-x}$Y$_x$(Al, Ga)$_5$O$_{12}$) is a variant
crystal where a portion of Gd is substituted with Yttrium and can have enhanced light yield, motivating its investigation for 0$\nu\beta\beta$ decay searches. In this study, GYGAG
crystals with different Yttrium concentrations were fabricated and their energy resolution, pulse shape discrimination capability between $\alpha$ and $\gamma$ rays, and scintillation timing characteristics were evaluated for applications in 0$\nu\beta\beta$ decay searches. Y substitution enhanced the light yield, and the best energy resolution was achieved for Gd$_{2.5}$Y$_{0.5}$Al$_2$Ga$_3$O$_{12}$. GYGAG exhibited high pulse shape discrimination performance across various yttrium concentrations.
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All authors Hibiki Hayasaki, Keishi Hosokawa, Koichi Ichimura, Shunsuke Kurosawa, Yuta Masaki, Yusuke Mizuno, Yasuhiro Nakajima, Hiroyuki Sekiya, Akihiro Yamaji
Space Physics
Forward Modeling of Spectral-Line Polarization for Weak Magnetic-Field Imaging
Chuanpeng Hou, Huirong Yan and Siqi Zhao
Measurements of interplanetary
magnetic fields rely mainly on spacecraft observations that provide in-situ sampling and cannot directly reveal global
magnetic structures. In addition, the Zeeman effect is generally too weak to image weak interplanetary
magnetic fields. Here, we investigate the suitability of spectral-line polarization for spatially resolved imaging of weak
magnetic fields, focusing on the Na I D lines in Mercury's magnetosphere. We calculate the spectral-line polarization produced by anisotropic
solar radiation and modified by the
magnetic-field orientation. Using a three-dimensional forward-imaging model of Mercury's magnetosphere, we generate synthetic maps of Na I D-line intensity and linear polarization. The resulting polarization maps trace the large-scale magnetospheric
magnetic-field geometry, demonstrating the potential of Na I D-line polarimetric imaging to constrain the spatial structure of Mercury's magnetosphere. We further show that, with a 1.8-m
telescope, Na I D-line linear-polarization imaging of Mercury's magnetosphere at a spatial resolution of 2" is feasible with an exposure time of approximately ten minutes.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Can MACE Potentials Accurately Describe Magnetism and Phase Stability in Fe-Ni Alloys? A Systematic Benchmark
Kushal Ramakrishna, Mani Lokamani and Attila Cangi
We present a systematic
benchmark of MACE potentials for iron-nickel
alloys, focusing on structural, elastic,
magnetic, and finite-temperature properties relevant to phase stability. The reference
dataset comprises
spin-polarized PBE density functional theory (DFT) calculations for chemically disordered special quasirandom structures (SQS), spanning compositions, bcc and fcc
crystal structures, and volumetric and shear deformations. A system-specific MACE-sqs model trained on this
dataset achieves validation errors of 2.0 meV/atom for energies and 24.3 meV/Angstrom for forces. Compared with several MACE foundation models, including models trained with Hubbard U corrections, MACE-sqs gives the most consistent agreement with DFT and experiment for equations of state,
equilibrium volumes, elastic constants, and thermal expansion trends in bcc and fcc Fe-Ni
alloys. For the bcc-to-hcp transition, MACE-sqs predicts a pure-Fe transition pressure closer to experiment than the tested foundation models, but all models predict an incorrect increase of transition pressure with Ni content. This failure indicates that high-pressure
magnetic collapse and composition-dependent magnetoelastic effects are not yet fully captured. Overall, targeted SQS-based training substantially improves the accuracy of MACE potentials for Fe-Ni
alloys, while phase stability under
magnetic collapse remains a key limitation for future model development.
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Classical Physics
A nonlinear beam model for photoresponsive thermoelastic solids driven by localised heating
William T. Simpkins, Matteo Taffetani and Matthew G. Hennessy
Asymptotic methods are used to derive a geometrically nonlinear beam model for thermoelastic solids with a spatially localised heat source. The asymptotic reduction is based on collapsing the heated region to a point. Away from the point of heating, the governing equations reduce to a pair of beam equations with nonlinear von Kármán strains. The effects of the localised heat source are captured through asymptotically consistent jump conditions that hold at the point of heating. The model accounts for changes in beam length due to longitudinal thermal expansion and bending moments produced by transverse thermal gradients. The model is used to study light-induced actuation of photoresponsive hydrogel beams with localised heating arising from
laser irradiation. Two loading scenarios are considered. In the first, the ends of the beam are assumed to be free, resulting in a V-shaped deformation upon heating. An analytical expression for the fold angle of the V is provided. In the second, the beam is assumed to be in a pre-buckled configuration due to clamped end conditions. The critical conditions leading to light-driven snap-through are calculated. Offsetting the
laser from the mid-point of the beam is found to inhibit the onset of snap through.
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Plasma Physics
Analytical theory of coherent radiation and radiation friction in laser-plasma collisions
E. G. Gelfer, A. M. Fedotov, M. P. Malakhov et al. (+4 more)
We develop an analytical theory of coherent (scaled quadratically with the number of particles) radiation and coherent radiation friction in a head-on collision of a dense charged particle bunch with an intense
laser pulse. We demonstrate that the low-frequency coherent radiation in the forward and backward directions dominates the energy-momentum losses of a mildly relativistic bunch and can result in a substantial enhancement of the overall radiation friction as compared to the incoherent case. We derive the scaling laws for the average momentum losses of the bunch over the collision with respect to
laser intensity, pulse duration, and particle bunch parameters, and show their robustness with respect to
laser polarization and the shape of the particle distribution in the bunch.
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All authors E. G. Gelfer, A. M. Fedotov, M. P. Malakhov, Th. Benahmed, J. Custodio, O. Klimo, S. Weber
Applied Physics · Cross-listed from cs.LG
LEIA: Learned Environment for Interactive Architected Materials
Haiqian Yang, Yuan Cao and Markus J. Buehler
World models have enabled interactive exploration of game environments and robotic manipulation, but physical engineering remains beyond their reach: real materials exhibit nonlinear constitutive laws, carry history-dependent internal state, undergo inertial dynamics, and may possess hierarchical structures spanning multiple length scales. We present LEIA (Learned Environment for Interactive Architected materials), a world model that lets engineers apply boundary conditions step by step and observe the resulting deformation and stress fields in real time. LEIA handles large three-dimensional unstructured meshes and generates autoregressive responses to user-specified loading. We introduce MicroPlate, a
benchmark of architected plates spanning two regimes of microstructure modeling: architected
lattices that resolve microstructure explicitly through three-dimensional geometry, and a homogeneous plate where microstructural change is modeled implicitly through internal degrees of freedom. MicroPlate is used to assess LEIA alongside four baseline methods across both regimes. Finally, we demonstrate that LEIA enables efficient candidate generation and ranking for fast surrogate-guided search for de novo designs of architected materials, with stress-accurate candidate ranking validated by finite element ground truth.
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Fluid Dynamics
Bow-shock instability in entry, descent, and landing vehicles under high-enthalpy conditions
Adrián Antón-Álvarez and Adrián Lozano-Durán
Laminar–turbulent transition remains a major uncertainty in the aerothermal design of entry, descent, and landing (EDL) vehicles. We show that, under high-enthalpy Mars-entry conditions, the detached bow shock and shock-generated shear–
entropy layer can become unstable under freestream disturbances, leading to nonlinear breakdown and enhanced wall heating. The analysis spans freestream Mach numbers ($M_\infty$) up to 30 for both Earth and Mars at high altitude, with Mars being more susceptible. The receptivity analysis shows that disturbance amplification occurs through a three-step mechanism: (i) transmission and amplification of acoustic and entropic freestream components across the bow shock; (ii) further convective amplification within the post-shock shear–
entropy layer; and (iii) bow-shock corrugation driven by the downstream pressure field, which reinforces the instability. The dominant response is localized in the shock layer, with no classical boundary-layer mode required. The total optimal energy gain scales as $\overline{G}_T^{\rm opt}\sim \gamma_2^*M_\infty^2 \exp[(\rho_2/\rho_1)/C-B/\sqrt{Re_\infty}]$, where $\gamma_2^*$ is an effective specific-heat ratio, $\rho_1$ and $\rho_2$ the pre- and post-shock densities, $Re_\infty$ the freestream Reynolds number, and $B$, $C$ geometry-dependent constants. For a representative EDL vehicle during Mars entry, amplification factors reach order $10^6$. Flight measurements from the Mars Science Laboratory (MSL) and Mars 2020/Perseverance capsules are consistent with these results, as are wall-modeled large-eddy simulations of MSL under representative Mars-entry conditions. These results suggest that bow-shock instabilities may constitute a transition mechanism for blunt hypersonic entry vehicles, either alone or combined with others.
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Fluid Dynamics
Peristaltic pumping in short annular geometries: An experimental approach for studying Glymphatic flow
Shahaf Ella Salach and Ron Shnapp
Peristaltic pumping is hypothesized to drive fluid transport in several physiological systems, including cerebrospinal fluid flow through cerebral perivascular spaces (PVSs). Cerebral PVSs are unique in the context of peristaltic pumping because they have annular geometry and are orders of magnitude shorter than the peristaltic wavelength. Due to these features, questions were raised as to whether peristaltic pumping is possible under such conditions, and experimental tests for this concept are lacking. This work presents a novel experimental setup that enables direct, detailed measurements of peristaltic flow in short annular channels formed between a compliant inner tube and a rigid outer tube. A propagating pulse wave along the inner tube generates back and forth fluid motion in the annular gap, which we measure using particle tracking velocimetry in a refractive-index matched setup. Despite the instantaneous back and forth motion, net axial fluid transport in the direction of wave propagation is observed, and the resulting net velocity profiles collapse across a range of wall deformation amplitudes. These results provide experimental evidence for net transport induced by long wave length peristaltic deformations in a physiologically relevant flow regime.
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Optics
Polarimetric Backscattering Setup for Quantitative Scattering Parameters Retrieval
Bhanu P. Singh, Vladislav Stefanov, Nadine A. Coorens et al. (+1 more)
We present two backscattering polarimetric scanning setups based on point-illumination schemes, that are designed to probe the optical properties of subsurface media. We describe their advantages and limitations, characterize their performance in Mueller
matrix determination, and demonstrate their ability to retrieve unknown sample parameters (such as the scattering coefficient and anisotropy factor) using a maximum likelihood approach. As an experimental validation, a polystyrene suspension is investigated as a representative case. By applying Fisher information formalism on the theoretical model, we estimate boundaries of the retrieved parameters.
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All authors Bhanu P. Singh, Vladislav Stefanov, Nadine A. Coorens, Andre Stefanov
Computational Physics · Cross-listed from cs.LG
Hybrid Neural World Models
Pranav Lakshmanan and Paras Chopra
Neural surrogates promise large speedups over classical solvers for physical dynamics but fail silently at sharp dynamical events such as shocks, fronts, and contact. We present hybrid neural world models for physical dynamics: a recipe for training and deploying multi-horizon surrogates in physical state space, where a single network with continuous horizon conditioning is trained with direct supervision against textbook reference solvers to predict any future state at horizon T in one forward pass. Although no part of the training data, loss function, or architecture supervises discontinuity location, the trained surrogate encodes it implicitly, recoverable from its forward passes alone as a per-trajectory error map that concentrates on shocks, fronts, and contacts, and stays small elsewhere. The map is competitive with or better than standard label-free baselines including deep ensembles, learned error heads, gradient-magnitude indicators, and locally-adaptive conformal prediction, while using only a single trained network and requiring no calibration set or governing-equation knowledge. The recipe supports two operating points. Mode 1 runs the surrogate alone for maximum throughput, with same-hardware CPU speedups of 26x to 72x against textbook solvers on the PDE environments. Mode 2 uses the error map to gate a reference-solver fallback, deferring uncertain trajectories and roughly halving the surrogate's residual error at the default operating point. The recipe applies without modification across reaction-
diffusion, compressible Euler, and rigid-body collision dynamics.
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Instrumentation and Detectors · Cross-listed from cs.LG
Machine Learning methods for event classification and vertex reconstruction of the 12C + 12C reaction with the MATE-TPC
Minghui Zhang, Xiaobin Li, Jie Chen et al. (+11 more)
In modern
nuclear physics experiments, identifying events of interest is challenging for
nuclear reaction studies with the active target Time Projection Chamber (TPC). In this work, machine learning techniques are employed to analyze the complex data of the 12C + 12C fusion reaction from a TPC named MATE (multi-purpose active-target time projection chamber for
nuclear experiments). Specifically, we successfully applied Residual Neural Network (ResNet-50, ResNet-34 and ResNet-18) and Visual Geometry Group (VGG-19) to classify elastic scattering and fusion reaction events from the 12C + 12C reaction. The classification results of the four models are nearly identical, with accuracies of approximately 97% for the simulated data and 90% for the experimental data. Moreover, these approaches successfully identify some events that are misclassified by traditional methods. These models are also applied to classify events from different fusion reaction channels, with classification accuracies of approximately 95% on simulated data. In addition, a Convolutional Neural Network (CNN) model is developed to reconstruct the reaction vertex, providing an alternative strategy for vertex reconstruction. These results indicate that machine learning techniques can effectively classify reaction events from different channels and reconstruct the reaction vertex, thereby paving the way for future analyses of complex
nuclear reaction data.
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All authors Minghui Zhang, Xiaobin Li, Jie Chen, Ningtao Zhang, Fenhua Lu, Junrui Ma, Jiazhen Yan, Wanqin Tu, Xiaodong Tang, Bingshui Gao, Chengui Lu, Zhichao Zhang, Jinlong Zhang, Weiping Liu
Physics and Society
Contact, conflict, or opportunity? Out-group exposure creates tie opportunity, not tolerance
Mauritz N. Cartier van Dissel, Tomáš Lintner, Samuel Martin-Gutierrez et al. (+1 more)
Three theories offer competing predictions about how people respond to growing diversity in their social environment. Contact theory suggests more exposure to out-groups reduces prejudice; conflict theory predicts a stronger in-group preference; structural opportunity theory argues that shifts in behaviour only reflect changes in the opportunity structure rather than in underlying preference. We test these predictions using friendship and rejection nominations from nearly 5,000 students in 228 classrooms, across gender, ethnicity, and socio-economic status. We estimate individual preference using a multilevel model based on the Wallenius hypergeometric distribution, which accounts for the finite, asymmetric pool of potential ties. Results show that for ethnicity and socio-economic status, preferences are largely unaffected by classroom composition. For gender, however, same-gender preference strengthens as the out-group increases, supporting conflict theory. This means greater diversity does not necessarily change the intrinsic preference of students toward out-group peers, but creates more opportunities for cross-group interactions.
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All authors Mauritz N. Cartier van Dissel, Tomáš Lintner, Samuel Martin-Gutierrez, Fariba Karimi
Optics
Universal zero-crosstalk photonic integration via slab-engineered mode hybridization
Kyungtae Kim, Yoseph Shin, Seungyong Lee et al. (+8 more)
Photonic integrated
circuits have emerged as a scalable platform for optical computing, communication, and
quantum technologies, where high-fidelity optical processing is essential. However, as photonic systems scale in complexity, inter-channel crosstalk accumulates across cascaded components, fundamentally degrading signal fidelity, limiting system-level performance, and constraining integration density. Existing crosstalk-suppression strategies rely on specialized nanostructures or platform-specific designs, hindering their adoption in standard foundry processes and across diverse material systems. Here we establish a universal and foundry-compatible route to eliminating crosstalk based on slab-engineered mode hybridization in standard rib waveguides. By tailoring the slab thickness, mode hybridization induces anisotropic modal perturbations that enable complete cancellation of coupling between adjacent waveguides. We experimentally demonstrate zero-crosstalk across diverse material platforms, including silicon-on-
insulator, silicon nitride, thin-film lithium niobate, and germanium-on-
insulator, spanning wavelengths from the visible to the mid-infrared. Our approach provides a manufacturable route toward scalable, high-fidelity, and high-density photonic integration, overcoming the long-standing trade-off between signal fidelity and integration density in large-scale photonic systems.
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All authors Kyungtae Kim, Yoseph Shin, Seungyong Lee, Inki Kim, Hyeyoon Jeon, Jibaek Song, Minseop Lee, Sanghyeon Kim, Hyounghan Kwon, Hojoong Jung, Sangsik Kim
Fluid Dynamics
Data-efficient semi-supervised learning for flow estimation using unlabelled probe data
Junwei Chen, Marco Raiola and Stefano Discetti
Estimating time-resolved velocity and pressure fields from Particle Image Velocimetry (PIV) remains challenging due to its limited temporal resolution in many applications. Data-driven approaches that combine snapshot PIV with high-frequency probe data have shown great promise in reconstructing the flow dynamics for advection-dominated flows; however, they typically exploit only the probe measurements directly synchronized with the PIV frames, leaving a large volume of probe-only data acquired between snapshots unused. In this work, we propose a framework that enriches the original PIV training
dataset by time-marching a simple advection model and then exploits unlabelled probe data through a semi-supervised learning strategy. Two neural networks are trained to predict the temporal coefficients of Proper Orthogonal Decomposition (POD) modes of the flow fields, and their temporal derivatives, respectively. Unlabelled probe samples are leveraged to enforce temporal consistency and expand the coverage of flow scenarios beyond those captured by snapshot PIV, which is crucial for obtaining physically consistent temporal gradients required for pressure field reconstruction. A least-squares regularization step is further employed to reconcile the predictions and enforce consistency between temporal coefficients and their derivatives. The proposed approach is validated on both synthetic turbulent channel flow data and experimental PIV measurements of an airfoil wake. Results demonstrate that incorporating unlabelled probe data significantly improves the accuracy and temporal smoothness of velocity reconstruction, leading to more reliable pressure estimation via the Navier-Stokes equations, without increasing the experimental cost.
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Chemical Physics
Approximate label symmetries improve data efficiency
Scott Y. H. Kim, Mathis Lechaume-Robert and O. Anatole von Lilienfeld
Enforcing feature
symmetries in machine learning (ML) models is a common strategy to mitigate data scarcity. Confirming expectations from statistical learning theory, we show that exact, as well as approximate, label
symmetries can also improve data efficiency. We illustrate the idea for the s, p, d orbital densities of the electron in the hydrogen atom, for the three vibrational normal modes of the water molecule, and for its full 3D potential energy hypersurface. Resulting ML models of electron density and potential energies exhibit superior learning curves, demonstrating improved generalization efficiency. We observe that learning curves similarly improve even when label
symmetries are not exact - up to the convergence floors set by the degree to which the
symmetry is approximate. Further improvements are obtained for approximate label
symmetries in the molecular potential energy surface, using a Hessian-based correction that suppresses the leading order term in the error.
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