Applied Physics · Cross-listed from cond-mat.mtrl-sci
Non-linear diffusion and inhomogeneity of the magnetic field in single-turn coils: Insights from 3D multiphysics modeling
Hideaki Kobayashi, Yugaku Goyo, Yuto Ishii et al. (+3 more)
The single-turn coil method is a destructive pulsed magnet for generating over 100 T with a few $\mu$-second pulse duration, and it inevitably causes the coil to explode. The temporal and spatial distributions of the electric current and
magnetic field are highly inhomogeneous, arising from the skin effect, rapid temperature rise, and coil deformation. To grasp the dynamic phenomena in the single-turn coil, we conducted a finite element analysis using multiphysics simulation. We employed finite element method calculations using a fully 3D model of the single-turn coil with broken cylindrical
symmetry. The calculated result revealed highly nonlinear
diffusion of electric current, temperature, and
magnetic fields, which are the sources of the inhomogeneous
magnetic fields inside the single-turn coil in time and space.
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All authors Hideaki Kobayashi, Yugaku Goyo, Yuto Ishii, Yasuhiro H. Matsuda, Kunio Takekoshi, Akihiko Ikeda
Instrumentation and Detectors
A Heavy Ion Monitor on a Chip Based on a Non-Volatile Memory Architecture – Part II: Device Characterization & Modeling
Dale Julson, Mike Youngs, Hannah Lowrey et al. (+3 more)
Building on the demonstrated sensitivity of the Heavy Ion Monitor on a Chip (HIMoC) presented in Part I of this work, we performed additional irradiation exposures using 24.8 MeV/u beams of $^{14}$N, $^{22}$Ne, and $^{40}$Ar at the Texas A&M University Cyclotron Institute. A novel simulation workflow was developed that couples the particle-transport toolkit Geant4 with the open-source TCAD simulator DEVSIM to model the heavy-ion-induced signal in HIMoC devices. The model represents energy deposition by primary heavy ions and secondary electrons as Gaussian charge-loss profiles that produce measurable threshold-voltage shifts in the device. Good agreement between simulated and experimental $\Delta V_{\mathrm{th}}$ distributions was obtained. HIMoC was also shown to generate a signal that scales approximately linearly with a dose-like quantity proportional to ion fluence, LET, and active detector area. These results support HIMoC as a passive heavy-ion dosimeter and provide a framework for modeling the effects of radiation-induced charge loss in charge-trapping non-volatile
memory devices.
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All authors Dale Julson, Mike Youngs, Hannah Lowrey, David Keltner, Tim Hossain, Clayton Fullwood
Optics · Cross-listed from quant-ph
Optimization of circular cavities via guided-mode expansion method based inverse design
Abhishek Das, Neelesh Kumar Vij and Demitry Farfurnik
Spin-
photon interfaces, realized by coupling optically active
spin systems to photonic cavities, are essential for
quantum networking and
quantum information processing. Implementing such an interface for polarization-encoded
photons requires a cavity that supports arbitrary polarization, provides efficient optical access through its far-field mode, and maintains sufficiently high quality factors to enable high cooperativity with the system's optical transitions. However, inherent trade-offs between the Q-factor and far-field emission mode make the simultaneous optimization of these parameters toward the realization of
spin-
photon interfaces challenging. In this work, we implement a gradient-based inverse-design framework using guided-mode expansion with automatic differentiation to obtain the geometrical features of a circular ring cavity that supports arbitrary polarization while simultaneously optimizing the cavity quality factor and far-field mode profile. The resulting optimized non-periodic cavity achieves a quality factor of approximately $9,000$, about an order-of-magnitude higher than that of a periodic ("bullseye") cavity while preserving a Gaussian-like far-field emission pattern. Furthermore, by varying the cavity geometry within a $\pm 6$ nm fabrication tolerance, we demonstrate the robustness of the design against fabrication errors and identify the innermost ring width and central disk radius as the parameters with the greatest impact on the quality factor and far-field mode. These results establish guided mode expansion-based inverse design as a powerful and computationally efficient approach for developing high-cooperativity
spin-
photon interfaces for
quantum photonic applications.
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Atmospheric and Oceanic Physics · Cross-listed from cond-mat.stat-mech
Data-driven analysis of metastability in a stochastic bistable system
Ankan Banerjee, Manuel Santos Gutierrez, John Moroney et al. (+1 more)
We present a methodology to analyze metastable properties of a simple prototypical
stochastic bistable system by identifying slow inter-well and fast saddle escape processes using the formalism of the Koopman operator. Instead of studying noise-induced transitions by following the trajectories of the system, we track them by studying the time
evolution and the decay rate of the subdominant mode of the Koopman operator, thus in a geometry-agnostic framework. The obtained escape time statistics together with the decay rate are in good agreement with the predictions - both the exponential and subexponential ones - of large deviation theory in the weak-noise limit, both in
equilibrium and nonequilibrium conditions. The subdominant Koopman mode also allows for an accurate reconstruction of the competing basins of attraction. Furthermore, going deeper in the Koopman spectrum, we are able to recognise modes that are associated with intra-well variability as well as with the escape of trajectories from the saddle towards the attractor, both in the
equilibrium and nonequilibrium case. Our methodology, being grounded in purely data-driven techniques, could provide a comprehensive, multi-scale framework for studying high-dimensional metastable systems.
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All authors Ankan Banerjee, Manuel Santos Gutierrez, John Moroney, Valerio Lucarini
Fluid Dynamics · Cross-listed from cs.LG
Wavelet Flow Matching for Multi-Scale Physics Emulation
Gabriele Accarino, Juan Nathaniel, Carla Roesch et al. (+4 more)
Accurate emulation of multi-scale physical systems governed by PDEs demands models that remain stable over long autoregressive rollouts while preserving fine-scale structures. Deterministic emulators produce overly-smoothed predictions, while generative approaches better capture details but are costly. Latent-space generative models have emerged as a compromise but with the additional cost of separately pre-trained autoencoders. We propose Wavelet Flow Matching (WFM), a novel generative emulator that overcomes current trade-offs between cost and skill by performing optimal-transport directly in the multi-scale wavelet space. Rather than learning a latent compression, WFM leverages the hierarchical structure of a U-Net to jointly predict transport velocities of a prescribed wavelet representation. On three challenging systems of chaotic fluid dynamics, WFM achieves superior long-horizon stability, accuracy and spectral coherence compared to state-of-the-art models. Our results clearly position the wavelet space as an effective training-free representation for generative emulation of complex physical dynamics.
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All authors Gabriele Accarino, Juan Nathaniel, Carla Roesch, Pierre Gentine, Sara Shamekh, Duncan Watson-Parris, Viviana Acquaviva
Applied Physics · Cross-listed from quant-ph
Measurement and Control of the Complex Berry Phase in a Quantum System
Pratik J. Barge, Qian Cao, Niklas Hörnedal et al. (+2 more)
The Berry phase is a
geometric phase acquired during adiabatic
evolution over a closed loop in parameter space. It plays an essential role in
geometric quantum gates and other phase-based protocols. In non-Hermitian systems, the Berry phase is complex, introducing fundamentally new
geometric effects, including state amplification. In this work, we report experimental measurement of both the real and imaginary components of a Berry phase in a fully
quantum system using a superconducting transmon
circuit with engineered dissipation. We also demonstrate the path-dependent effects of the imaginary part on the dissipation and its utility in the implementation of non-
unitary quantum control. These findings establish a clear
geometric distinction between the real and imaginary components of the Berry phase and experimentally confirm the unique adiabatic behavior of non-Hermitian
quantum systems.
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All authors Pratik J. Barge, Qian Cao, Niklas Hörnedal, Aurélia Chenu, Kater W. Murch
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Ultrasonic determination of crystallographic texture by transmitted field fitting regardless of medium dispersivity
Diego A. Cowes, Juan I. Mieza and Martín P. Gómez
The determination of crystallographic texture through elastic wave propagation offers a cost-effective, nondestructive means of obtaining through-thickness information with minimal sample preparation. Existing ultrasonic approaches rely on either bulk-wave or guided-wave velocity measurements for texture inversion. These strategies impose
geometric constraints: bulk-wave methods become impractical for thin specimens, whereas guided-wave techniques are limited to relatively small thicknesses. Furthermore, many formulations assume orthotropic
symmetry of the aggregate, thereby restricting their applicability to materials with higher anisotropy. In this work, a full-field wave fitting strategy is developed in which the transmitted ultrasonic field is simulated and directly compared to experimental measurements. Because the approach does not rely on bulk-wave or plate-wave approximations, it remains applicable across a broad range of specimen thicknesses. Furthermore, no macroscopic
symmetry assumptions are imposed on the aggregate, enabling the characterization of generally anisotropic materials. The effective elastic response is computed using a Hashin-Shtrikman homogenization framework, which provides tighter bounds than classical Voigt-Reuss-Hill averages and constrains the admissible search space during optimization, thereby improving convergence. The nonlinear inverse problem is solved using a GPU-accelerated optimization scheme. The methodology is validated on materials with hexagonal and cubic
crystal symmetry over a range of specimen thicknesses. The inferred texture coefficients show consistent agreement with independent diffraction measurements. Additionally, textures with weak elastic anisotropy are successfully recovered, demonstrating the robustness and versatility of the proposed method. Complete measurement and inversion are achieved within approximately 10 minutes.
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Data Analysis and Statistics · Cross-listed from cs.SD
vega-mir: An information-theoretic Python toolkit for symbolic music, with applications to harmonic graphs and rubato spectra
Fred Jalbert-Desforges
We present vega-mir, an open-source Python library that bundles nine information-theoretic and statistical metrics for the analysis of symbolic music corpora behind a small, tested, citable API, and demonstrates two of them at corpus scale in case studies not addressed by the upstream Cygnus paper. Of the nine metrics, three (Shannon
entropy, Kullback-Leibler divergence, Zipfian fits) were deployed in the companion Cygnus arXiv preprint; two (network analysis on chord-transition graphs and spectral analysis of rubato curves) are deployed in full case studies here; the four remaining (multi-dimensional Gini, chi-squared stationarity, Higuchi fractal dimension, interval distribution) are validated against analytic anchors and exercised as sanity checks on a bundled 8-composer
dataset. The two case studies yield two main observations. First, on the fourteen MAESTRO composers with N >= 10 pieces, the PageRank value of the
gravity-centre node correlates with the marginal Kullback-Leibler distance at rho = 0.61 (Spearman, composer-level jackknife N = 14); the categorical
gravity-centre identity takes five distinct values across the corpus but is not itself correlated with marginal KL (rho = 0.13, p = 0.21). Second, on the 247-piece Bach multi-master corpus (Schiff, Gould, Richter), Gould holds the highest periodicity ratio of the three performers, not the lowest, inverting the cliché that low scalar rubato reads as "metronomic": Gould's rubato is small in amplitude but structured in time, with a median dominant period of 66 beats against Schiff's 102 and Richter's 104.
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Instrumentation and Detectors
Cosmogenic activation in detector materials at shallow depths
Sagar S. Poudel, Lekhraj Pandey, Robert Calkins et al. (+6 more)
The radioactive decay from long-lived radioactive isotopes produced by cosmogenic activation can be an important background in direct-detection dark matter and
neutrino experiments. In general, activation of materials located above ground is dominated by
nuclear spallation due to energetic
neutrons produced as secondary particles from primary
cosmic ray interactions in the atmosphere. As experiments become larger and strive for greater sensitivity to rare events, it is increasingly important to store, assemble, and even fabricate the detector materials underground to mitigate cosmogenic activation. There has been no study of cosmogenic activation in detector materials at shallow depths (< 100 meter-water-equivalent). Unlike at aboveground or at deep depths, where
neutrons are the major contributors to activation in materials, there are multiple competing physical processes that contribute to the activation in materials at shallow depths. We present a detailed calculation of the production of tritium in Ge and Si, as well as the production of 60Co in Cu, at shallow depths. We also obtain cosmogenic activation suppression factors and tritium production at several shallow-depth sites including the Stanford Underground Facility (SUF), where the SuperCDMS collaboration stored Ge, Si, and Cu detector materials for a substantial period of time.
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All authors Sagar S. Poudel, Lekhraj Pandey, Robert Calkins, Manish K. Jha, Ben Loer, John L. Orrell, Alan Robinson, Joel Sander, Richard W. Schnee
Computational Physics · Cross-listed from hep-ph
Freeze-in Warm Dark Matter via Dimension-6 Operators in 3-3-1 Models
Fuwei Liu and Fujun Liu
We propose a natural resolution to the fine-tuning problem inherent in the freeze-in dark matter paradigm by
embedding a sterile singlet within a 3-3-1 electroweak extension. By imposing an exact $Z_{13}$ discrete gauge
symmetry, we formally suppress all low-dimensional portals to ensure that the dark sector communicates with the Standard Model (SM) exclusively through a dimension-six operator. This theoretical structure allows the extraordinarily small coupling required for dark matter production to emerge naturally from the profound hierarchy between the electroweak scale and the ultra-high Peccei-Quinn
symmetry breaking scale. Detailed numerical integration of the Boltzmann equations demonstrates that the sterile singlet can be produced via the infrared freeze-in mechanism to match the observed relic abundance of $\Omega_S h^2 = 0.12$. The resulting keV-scale warm dark matter candidate remains consistent with stringent Lyman-alpha forest constraints while offering a viable solution to
galactic-scale discrepancies such as the cusp-core and missing satellites problems. Ultimately, this framework provides a self-consistent unification of dark matter genesis and the strong CP solution that is completely independent of ad hoc parameter adjustments.
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Plasma Physics
Stern–Gerlach Spin Sorting and Dynamical Feedback in Relativistic Pair-Plasma Reconnection
K. Nykyri
We derive a Stern–Gerlach control parameter, $\Xi$, comparing
spin-driven cross-sheet displacement with the relativistic Larmor radius. It places heliospheric
plasmas and most astrophysical jets in the negligible regime, some
stellar-mass black-hole coronae in a transitional regime, and magnetar sheets in a strong, near-QED regime. Relativistic pair-
plasma simulations at fixed $\gamma_{\rm tr}=2$ show that increasing $\Xi$ produces, within the coupled SG+$\mathbf J_M$ model,
magnetic-moment sorting and magnetization-current feedback that enhance the normalized flux-growth rate through an additional
spin-kinetic pathway beyond classical pressure- and geometry-controlled pair-
plasma reconnection.
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Optics · Cross-listed from cond-mat.mes-hall
Acoustic spin resonance in polariton condensates
D. A. Saltykova, A. Kudlis, A. V. Yulin et al. (+1 more)
We theoretically investigate acoustic
spin resonance in a spatially homogeneous spinor polariton condensate. A longitudinal acoustic wave generates a time-periodic strain-induced effective
magnetic field acting on the condensate pseudospin. When this field is transverse to the static in-plane linear-polarization splitting, it resonantly drives polarization oscillations. We show that
spin-dependent interactions shift the resonance and produce nonlinear line shapes, while gain, reservoir dynamics, and
spin relaxation make the response dissipative and history-dependent, producing amplitude hysteresis. In the presence of lifetime anisotropy, the condensate can develop a bifurcated stationary state with finite circular polarization, and a resonant acoustic drive can switch between the corresponding out-of-plane branches. A Zeeman splitting provides an additional conservative knob for tuning the resonance frequency. Our results identify coherent acoustic driving as a route to resonant, nonlinear, and switchable control of polariton pseudospin dynamics.
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All authors D. A. Saltykova, A. Kudlis, A. V. Yulin, I. A. Shelykh
Plasma Physics
Kinetic Simulations of Laser-Driven Compression and Heating of Magnetised Cryogenic Hydrogen Targets using PIConGPU
Filip Optołowicz, Klaus Steiniger, David Blaschke et al. (+2 more)
We present fully kinetic two-dimensional, three-velocity-component (2D3V) PIConGPU simulations of a three-beam direct-drive interaction with a 15 $\mu$m solid-density cryogenic hydrogen cylinder, establishing a predictive numerical baseline for the operational DRACO ($\tau=30$ fs) and upcoming PENELOPE ($\tau=150$ fs)
laser facilities at HZDR. The simulations resolve charge-separation fields on the order of 3 TV/m and reveal a robust kinematic bifurcation of the accelerated population into a fast (1-5 MeV) ion beam and a slower bulk (1-100 keV) flow. We demonstrate analytically and numerically that the charge-separation front ($v_{hb}$) is an intrinsically non-quasi-neutral electrostatic double layer that lies outside the closure assumptions of radiation-hydrodynamic models. A simple $2v_{hb}$ reflection scaling derived directly from the front trajectory tracks the centroid of the constant-energy fast-ion band under the impulsive 30 fs driver and the time-varying upper edge of the swept fast-ion band under the sustained 150 fs driver, across both intensities ($a_{0}=12.7$ and 22.0), establishing this non-thermal mechanism as the dominant acceleration pathway. We then scan an external axial
magnetic field from 0 T to 10 kT. Laboratory-achievable 20 T fields leave all macroscopic observables unchanged; fields at the kT scale progressively magnetise the MeV hot-electron population, quench the
laser-driven charge-separation mechanism, suppress the fast-ion band, and more than double the net-inward compression time of the short-pulse driver-while extending the outer target envelope. A
geometric equivalence argument maps these kT-scale results onto larger-diameter cryogenic hydrogen jets.
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All authors Filip Optołowicz, Klaus Steiniger, David Blaschke, Michael Bussmann, Brian Marre
Computational Physics · Cross-listed from cs.CL
Optimized Three-Dimensional Photovoltaic Structures with LLM guided Tree Search
Michael P. Brenner, Lizzie Dorfman and John C. Platt
We present a case study for how AI coding systems can be used to generate novel scientific hypotheses. We combine a generic coding
agent (Google's AntiGravity) with an LLM-driven tree search
algorithm (Empirical Research Assistance / ERA) to autonomously generate high-efficiency three-dimensional photovoltaic (3DPV) structures that overcome losses limiting flat
solar panels at mid-latitudes. These structures operate by presenting favorable angles to the sun throughout the day, and for illustrative purposes we focus on optimizing performance for a single
solar day. Our workflow begins by using AntiGravity to reproduce calculations \cite{bernardi2012
solar} showing that 3DPV can have energy densities much higher than stationary flat PV panels. We use these initial designs as the starting point for large scale tree search, where we seek improved solutions and score them for their diurnal yield. The initial tree search leads to nominally more efficient solutions, yet they are caused by algorithmic reward hacking, arising from non-physical design features such as structurally levitating disconnected tiers and exploitations of the discretizations in the optics solver. To counteract this, we develop a workflow where the coding
agent iteratively patches the physics engine with constraints to eliminate reward hacking. With reward-hacking eliminated, ERA discovers a series of designs with various constraints and improved performance, including optimal designs with different fixed collector areas, optimizing zenith tracking and avoiding self shadowing. Combining coding
agents with tree search (ERA) provides a powerful platform for scientific discovery, for problems whose solutions can be empirically evaluated with a score function.
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Chemical Physics · Cross-listed from quant-ph
Quantum Solvers for Nonlinear Matrix Equations in Quantum Chemistry
Pablo Rodenas-Ruiz, Andrew Zhao and Joonho Lee
We present a
quantum algorithm for solving algebraic Riccati equations, with applications to
quantum-chemical random-phase approximation (RPA) and higher-order RPA theories. Our method block-encodes stabilizing Riccati solutions via Riesz projectors onto invariant subspaces of an associated non-normal
matrix, implemented using contour-integral resolvents and
quantum singular value transformations. Applied to $m$-particle, $m$-hole RPA, our
algorithm yields a block-encoding of the amplitude solution and estimates the electronic correlation-energy density with it. Under localized-orbital sparsity assumptions, the end-to-end cost scales linearly with system size and polynomially with excitation rank $m$, suggesting an exponential advantage in $m$ over plausible classical local-correlation heuristics. More broadly, this work provides a framework for
quantum algorithms for nonlinear
matrix equations in
quantum chemistry and opens a possible route toward developing
quantum algorithms for coupled-cluster theory.
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Atmospheric and Oceanic Physics
Probabilistic Seasonal Streamflow Forecasting Across California's Sierra Nevada Watersheds with Agentic AI
Ignacio Lopez-Gomez, Michael P. Brenner and Tapio Schneider
Accurate seasonal runoff forecasts are critical for managing California's reservoirs and water supply for millions of its residents. Winter snow accumulation provides a strong source of predictability of snowmelt-based runoff in the spring and summer months, but progressive hydroclimatic changes in the Sierra Nevada are altering its timing and volume. These changes reduce the skill of statistical forecasts trained on historical data, highlighting the need for improved
forecasting systems that can capture the changing dynamics of snowmelt. Here we demonstrate that a collaborative workflow between an agentic AI assistant and an automated code-mutation system, both powered by large
language models, can accelerate the development of competitive seasonal runoff
forecasting systems. In our framework, the AI
agent discovers relevant
datasets, synthesizes domain knowledge from prior
forecasting competitions and the scientific literature, and explores the space of model architectures, while the code-mutation system refines each of the solutions explored by the
agent through Monte Carlo Tree Search over the code space. The resulting system forecasts monthly Full Natural Flow (FNF) at 1- to 6-month lead times across 23 Sierra Nevada watersheds using an adaptive ensemble of three XGBoost
quantile regression sub-models with physics-informed feature engineering. Evaluated against California's operational Bulletin 120 forecasts over 2021-2025, the
agent-evolved model achieves superior skill for early-season cumulative April-July runoff predictions, reducing watershed-averaged
quantile forecast error by up to 29%, and offering a new paradigm for AI-driven scientific model development in the geosciences.
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Chemical Physics · Cross-listed from cs.LO
LeanBET: Formally-verified surface area calculations in Lean
Ejike D. Ugwuanyi, Colin T. Jones, John Velkey et al. (+1 more)
The Brunauer–Emmett–Teller (BET) method is a standard tool for estimating surface areas from adsorption isotherms, yet practical implementations involve multiple algorithmic steps whose correctness is rarely made explicit. In this work, we present a fully executable and formally verified BET analysis pipeline implemented in the Lean~4
theorem prover. Our formalization covers the complete BET Surface Identification (BETSI)-style workflow, including window enumeration, monotonicity checks, knee selection, and linear regression. We carry out computations in floating-point arithmetic and develop the corresponding correctness proofs over the real numbers, using a shared polymorphic implementation that supports both. On the proof side, we show that the regression coefficients returned by the
algorithm agree with their specification-level definitions and minimize the least-squares error under the stated assumptions. We also formalize the algebraic derivation of the BET linearized expression and connect that result directly to the executable analysis pipeline. We further prove that the window enumeration is sound and complete, and that the admissibility checks and knee-based selection satisfy their formal specifications. We evaluate the implementation against the BETSI reference method on
benchmark adsorption isotherms. Compared to BETSI, LeanBET agrees to machine precision for 18 of the 19 isotherms, with only a 0.03% deviation for the UiO-66
dataset. This demonstrates that a scientific computing workflow can be built in Lean, yielding both formal verification guarantees and numerical agreement with an established Python reference implementation.
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All authors Ejike D. Ugwuanyi, Colin T. Jones, John Velkey, Tyler R. Josephson
Atmospheric and Oceanic Physics
SwAIther-Precip: Lead-Time-Aware Bias Correction Enables Kilometer-Scale Downscaling of Global AI Precipitation Forecasts over Switzerland
Dan Assouline, Erwan Koch, Federico Amato et al. (+5 more)
Skillful medium-range precipitation
forecasting at kilometer scale remains challenging over complex terrain because precipitation arises from multiscale nonlinear processes that global models cannot explicitly resolve at affordable cost. Global AI weather models can produce skillful medium-range forecasts, but their native 0.25 degrees resolution limits direct use for local hazard applications. Statistical downscaling can help bridge this gap, yet existing approaches often struggle with state-dependent, and especially lead-time-dependent, biases in global forecasts. We introduce SwAIther-Precip, a lead-time-aware downscaling framework that converts coarse-resolution AIFS forecasts into probabilistic km-scale precipitation fields over Switzerland. First, a U-Net conditioned on lead time via feature-wise linear modulation deterministically corrects systematic biases at coarse resolution. This targeted correction enables a cheaper super-resolution stage conditioned only on corrected precipitation, allowing direct training on observations rather than on the full atmospheric state. A
diffusion-based model then generates fine-scale spatial variability independently of lead time. Using AIFS forecasts and CombiPrecip radar-gauge observations, SwAIther-Precip reduces CRPS by 48% relative to raw AIFS. The generated fields reproduce observed spatial variability with spectral fidelity above 0.85 at large scales and 0.88 at small scales, corresponding to an effective resolution of approximately 4 km on a 1 km grid for lead times up to 5 days. Training across lead times further improves long-range performance, yielding a 13% CRPS reduction at 6 days relative to lead-time-specific models. These results show that explicitly correcting lead-time-dependent biases before generative super-resolution is key to efficient km-scale probabilistic downscaling of global AI precipitation forecasts.
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All authors Dan Assouline, Erwan Koch, Federico Amato, Filippo Quarenghi, Daniele Nerini, Thibaut Loiseau, Kyle van de Langemheen, Tom Beucler
Plasma Physics
Beyond Maxwell-Boltzmann: Transport in Quasiequilibrium Plasmas
Kamel Ourabah
Space
plasmas are generally characterized by non-Maxwellian distributions with suprathermal populations, as routinely revealed by in situ observations. Such departures from standard Maxwellian distributions can be understood as signatures of quasiequilibrium states, in which the distribution of the medium can be expressed as a continuous superposition of Maxwellian distributions, namely through superstatistics. Here, we construct macroscopic relations linking fluxes to their associated driving forces in such
plasmas, where superstatistical effects enter the picture through the transport coefficients. After comparing the resulting superstatistical distributions with observed electron distributions in the
solar wind, we turn to the kinetic response of quasiequilibrium
plasmas and derive the corresponding transport coefficients, including the electric and thermal conductivities, the mobility, and the
diffusion coefficient. We further extend the analysis to viscous
plasmas and compute the shear and bulk viscosity coefficients. Overall, quasiequilibrium effects are found to systematically enhance the transport coefficients relative to their Maxwellian values. We quantify this enhancement for the three main universality classes of superstatistics, which are the most commonly encountered in experimental and observational situations, and interpret it as a consequence of the increased population of energetic particles in the non-Maxwellian tails.
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Optics · Cross-listed from quant-ph
Sub-picosecond inter-core skew characterization in multicore fibers via Hong–Ou–Mandel interference
L. Lira Tacca, L. Marques Fagundes, M. Morales Lillo et al. (+9 more)
Inter-core skew (ICS), the differential group delay between cores of a multicore fiber (MCF), is a critical parameter for both classical space-division multiplexed communications and
quantum photonic networks. We present a high-precision measurement of ICS in a commercially available four-core fiber using two-
photon Hong–Ou–Mandel (HOM) interference in a fiber-integrated $4\times4$ multiport beam splitter. By extracting the center position of HOM interference dips and peaks across all twelve core-pair combinations, we obtain individual ICS values with a demonstrated precision of $\pm0.11\,$ps, limited by the delay-stage positioning uncertainty. The root-mean-square ICS grows as $\sigma_\tau(L) = \kappa\sqrt{L}+c$ with $\kappa = 48.7 \pm 2.5\,\mathrm{ps}/\!\sqrt{\mathrm{km}}$ and $c = 9.76 \pm 1.2\,$ps, over fiber lengths from $7.7\,$m to $1300\,$m. This first direct validation of the
stochastic random-walk scaling across a length range spanning laboratory to field-deployed scales was made possible by HOM's immunity to first-order path fluctuations, which renders classical interferometric methods impractical for long installed fibers. The demonstrated $\pm0.11\,$ps precision represents a $\sim\!180$-fold improvement over correlation optical time-domain reflectometry (C-OTDR), the standard method for long-fiber ICS characterization. Fisher information analysis establishes a fundamental Cramér–Rao precision limit in the femtosecond range, indicating further improvement is achievable with better delay control. These results establish a practical platform for characterising timing uniformity in MCF-based networks for both
quantum and classical space-division multiplexed applications.
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All authors L. Lira Tacca, L. Marques Fagundes, M. Morales Lillo, M. Navarro, I. Machuca, S. Gómez, G. H. dos Santos, J. Cariñe, G. Saavedra, E. S. Gómez, G. Lima, S. P. Walborn
Fluid Dynamics · Cross-listed from cond-mat.stat-mech
Staggering domino-like blast front motion in a one-dimensional cold gas
Taras Holovatch, Yuri Kozitsky, Krzysztof Pilorz et al. (+1 more)
One-dimensional alternating particle systems are widely used to study interconnections between the hydrodynamics of blast waves in a gas-like medium and the Newtonian dynamics of its corpuscular constituents. We study the model in which point particles with masses $m,\mu, m,\mu,\dots, (m\geq\mu)$ are distributed on the positive half-line $\mathbb{R}_{+}$. Their dynamics are initiated by giving a positive velocity to the leftmost particle; in its course, the particles undergo elastic collisions. For this model with $m/\mu=2$, it has previously been established that the dynamics that start from random initial positions are consistent with predictions based on Euler's hydrodynamic equation. In particular, they have the following properties: (i) the position of the rightmost particle (shock front) evolves as $t^\delta$ with $\delta<1$; (ii) recoiled particles behind the front enter the negative half-axis; (iii) particles with locations $x\leq0$ move ballistically and eventually take over the total energy of the system. In this paper, we present numerical and analytical results for the dynamics of this model with nonrandom (typically equidistant) initial positions and various values of $m/\mu$. For $m/\mu=2$ and equidistant initial positions, our results qualitatively agree with those just mentioned. At the same time, we found an infinite family of numbers $\{\mathcal{M}_k\}$ such that, for $m/\mu=\mathcal{M}_k$, the hydrodynamic behavior mentioned changes drastically to the following. At each moment, only a single triplet $m,\mu, m$ is in motion, whereas all other particles are at rest. As a result, the shock front moves ballistically with an average velocity equal to the initial one. Such a `staggering domino-like' picture is obtained as an exact solution, which yields, in particular, explicit formulas for $\mathcal{M}_k$ and the particle velocities and positions.
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All authors Taras Holovatch, Yuri Kozitsky, Krzysztof Pilorz, Yurij Holovatch
History and Philosophy of Physics · Cross-listed from quant-ph
Quantum Measurement without Ontology
Richard Healey
Measurement is an important scientific activity. In most of science, including classical physics, is may be understood as a way of finding out about the physical world and representing the results numerically. No-go
theorems show that measurement of
quantum observables is not like that: the recorded outcome is typically created rather than revealed in a
quantum measurement, in which case there is no objective fact about the observable's prior value. Other no-go
theorems show that
unitary quantum theory can generally neither explain nor even represent a unique recorded outcome, thereby threatening that outcome's objectivity. Methodological norms inherent in
quantum physical practice nevertheless institute the objectivity, not only of unique recorded outcomes of
quantum measurements, but also of non-
quantum features of the world that physicists and other scientists take their models to represent.
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Atomic Physics
Multipole blackbody radiation shift in Rydberg atoms
R. M. Potvliege
We study the role of retardation in the energy shift of Rydberg states induced by thermal radiation, focusing on the case of temperatures higher than those for which the electric-dipole approximation is expected to apply. As anticipated by Farley and Wing [Phys. Rev. A 23, 2397 (1981)], retardation needs to be taken into account in calculations of this energy shift at and above the temperature $\alpha\, mc^2/(3k_{\rm B}\,n^2)$, where $n$ is the principal
quantum number of the state considered, $m$ is the mass of the electron and $k_{\rm B}$ is Boltzmann constant.The corresponding non-dipole shift dominates the electric-dipole shift at about 2.5 times that characteristic temperature. We also show that the electric-quadrupole thermal shift is of the same order of magnitude as the diamagnetic thermal shift and would thus need to be taken into account in the circumstances where the latter is relevant.
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Atmospheric and Oceanic Physics · Cross-listed from cs.DC
An efficient multi-GPU implementation for the Discontinuous Galerkin ocean model SLIM
Miguel De Le Court, Vincent Legat, Ange P. Ishimwe et al. (+3 more)
Unstructured-mesh ocean models are increasingly used for coastal applications due to their ability to represent complex geometries and apply local grid refinement where needed. However, their broader use has been hindered by their high computational cost, particularly for models based on the Discontinuous Galerkin finite element (DG-FE) method, which involves significantly more degrees of freedom than traditional finite volume or continuous finite element approaches. The rapid emergence of GPU-based high-performance computing architectures now offers a pathway to address this limitation, as DG-FE formulations are inherently well suited to massively parallel, element-wise computations. Here, we present a full 3D DG-FE ocean model implementation optimized for both single- and multi-GPU systems, with support for both NVIDIA and AMD architectures. We detail the computational strategies employed to achieve high performance, including
memory layout optimization, kernel-level parallelization, and
matrix-free solvers for key vertical processes.
Benchmark results demonstrate that a single HPC-grade GPU (e.g. NVIDIA A100) delivers performance equivalent to approximately 1500 CPU cores, while replacing a 128-core CPU node with a 4xA100 GPU node yields a speedup of around 50x. Weak-scaling efficiency is maintained up to 1024 GPUs. We further demonstrate the model's capabilities on a real-world application in the Great Barrier Reef, achieving a spatial resolution five times finer than the most accurate existing model while maintaining a physical-to-numerical time ratio of 100. These results highlight how GPU-accelerated DG-FE methods can dramatically advance the capabilities of unstructured-mesh ocean modeling, enabling ultra-high-resolution coastal simulations that were previously infeasible.
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All authors Miguel De Le Court, Vincent Legat, Ange P. Ishimwe, Colin Scherpereel, Emmanuel Hanert, Jonathan Lambrechts
Biological Physics · Cross-listed from cond-mat.soft
Biophysical Considerations for Rational Antibody and ADC Design
Alberto Ocana and Jorge R. Espinosa
Antibody-based therapeutics-including antibody-drug conjugates (ADCs), bispecific antibodies, and novel formats-are reshaping oncology, yet key determinants of efficacy, safety, and manufacturability frequently emerge after conjugation and formulation. We argue that computational biophysics provides an underexploited framework to address this gap by connecting molecular interactions to biological outcomes. We highlight how molecular dynamics, coarse-grained simulations, and free energy calculations reveal how conjugation site, linker chemistry, and drug-antibody ratio reshape conformational landscapes. We emphasize structural coupling between antibody, linker, and payload, with implications for antigen binding, internalization, and developability. We propose that integrating physics-based modeling into development pipelines-alongside experimental validation-can reduce empirical iteration and de-risk translation. As force fields, and hybrid physics-machine-learning methods improve, this field is poised to become a central driver of next-generation ADC design.
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Applied Physics · Cross-listed from cond-mat.mes-hall
Prabhu Prasad Swain, Nahid Hosseini, Eveline. S Mayner et al. (+3 more)
Correlative nanoscale surface characterization benefits from simultaneously measuring electronic and structural properties in the same environment, a capability that is essential for modern-day materials science and
semiconductor failure analysis. In-situ AFM-SEM measurements facilitated by self-sensing cantilevers offer great potential here; however, they are limited due to their inherent capacitive crosstalk. Here, we demonstrate for the first time the in-situ implementation of single-pass heterodyne Kelvin probe force microscopy inside a scanning electron microscope, using piezo-resistive cantilevers. We overcome the capacitive crosstalk prevalent in piezo-resistive cantilevers by demodulating excitation and detection to simultaneously map surface topography and contact potential difference for correlation with compositional analysis. We systematically compare different operational modes of this heterodyne technique, elucidating their spatial resolution, signal sensitivity, and signal-to-noise ratio. The integrated approach yields exceptional signal quality and reveals how electron beam scan parameters can directly influence surface potential contrast. We demonstrate this correlative analysis workflow on two-dimensional
heterostructures and
semiconductor circuits. This work establishes a robust and versatile correlative imaging mode for in-situ Kelvin force and topography imaging inside a scanning electron microscope for next-generation
semiconductor device analysis and materials science.
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All authors Prabhu Prasad Swain, Nahid Hosseini, Eveline. S Mayner, Aleksandra Radenovic, Marcos Penedo, Georg E. Fantner
Computational Physics · Cross-listed from quant-ph
Quantum Feature Amplification Network (QFAN) as An Autoregressive Quantum Generative Model
Jamal Slim, Saverio Monaco, Florian Rehm et al. (+2 more)
Gate-based
quantum generative models have been limited to small images, because their
quantum resources grow with the size of the data. The
Quantum Feature Amplification Network (QFAN) removes this limit. It reuses a single few-
qubit circuit to generate the data block by block, each block conditioned on a compact summary of those before it, with the
circuit's measurement outcomes as the source of randomness. The number of
qubits is set by the block rather than by the data, and the number of
circuits per training step does not grow with the data either. In simulations with only four
qubits, QFAN generates full-resolution calorimeter showers from the CaloChallenge
Dataset~1
benchmark, 368 voxels each, and learns their correlations and shower-to-shower fluctuations. A three-
qubit version generates 12- and 25-pixel images on IBM
quantum hardware. This brings high-dimensional scientific data within reach of near-term
quantum generative models.
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All authors Jamal Slim, Saverio Monaco, Florian Rehm, Dirk Kruecker, Kerstin Borras
Applied Physics · Cross-listed from cond-mat.mtrl-sci
A practical Laser-Heated Diamond Anvil Cell synthesis technique and recovery workflow for metastable MnSb2 and YbZn2 phases
S. Huyan, R. F. S. Penacchio, D. Zhang et al. (+5 more)
The creation and exploration of new materials under extreme pressure-temperature conditions has become increasingly reliant on
laser-heated diamond anvil
cell (LHDAC) techniques, which provide direct access to previously unexplored regions of multinary phase diagrams. Whereas numerous high-pressure phases have been identified in situ, systematic recovery and post-synthesis physical property characterization of these materials remain significant challenges. In this work, we present the development of an integrated LHDAC synthesis and demonstrate a practical LHDAC-based synthesis workflow that enables stabilization and recovery of metastable intermetallic phases for subsequent structural and transport studies. Using this approach, we successfully achieved LHDAC synthesis of high-pressure MnSb2 and YbZn2 phases under moderate pressures. Synchrotron X-ray diffraction and spatial mapping confirm dominant formation of the targeted phases, whereas laboratory-based refinement quantifies phase fractions despite intrinsic microstrain and minor secondary phases. High-pressure transport measurements on recovered samples reveal tunable by pressure electronic instabilities in both systems. In MnSb2, pressure suppresses two high-temperature
magnetic ordering anomalies, observed in transport, by 5 GPa and for higher pressures induces a new low-temperature feature that increases with further pressure increase. In hexagonal high-pressure YbZn2, an electronic reconstruction emerges at ~11 GPa, characterized by semiconducting-like behavior from ~ 30 K to 300 K and a broad low-temperature coherence crossover near 30 K. Our results establish LHDAC synthesis not only as a structural discovery tool, but also as an experimental platform for investigating correlated
quantum states stabilized far from
equilibrium thermodynamic conditions.
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All authors S. Huyan, R. F. S. Penacchio, D. Zhang, Z. Li, S. L. Morelhão, Raquel Ribeiro, P. C. Canfield, S. L. Bud'ko
Applied Physics
Physics-Aware Machine-Learning-Driven Inverse Design of Broadband Ultra-Open Acoustic Metamaterials
Zhiwei Yang, Mengyu Li, Xiaohang Xie et al. (+3 more)
Ventilated acoustic silencers combing sound attenuation with high ventilation are pivotal for advanced noise control. However, balancing attenuation, bandwidth, openness, and thickness remains a high-dimensional challenge. Here, we report a physics-aware machine-learning-driven inverse design framework for ultra-open acoustic silencers (UAS). By leveraging Green's function-based parameterization, we physically decouple the design space into spectral and radial parameters, ensuring physical interpretability while reducing complexity. We introduce a two-stage forward prediction architecture that captures broadband envelopes and sharp resonant features via a coarse-to-fine strategy. Coupled with a population-based, hybrid-objective parallel (PHP) inverse strategy, our framework enables rapid exploration of non-convex landscapes, identifying hundreds of optimized candidates within seconds. Crucially, this framework uncovers hidden linear design rules that govern high-performance monolithic designs, acting as
geometric proxies for optimal impedance-matching. We experimentally validate a family of prototypes: UAS-2 demonstrates the monolithic limit with high ventilation ratio, while UAS-3 demonstrates versatility in multi-mode interactions. To circumvent the trade-off ceiling of single-unit resonators, a parallel-composite architecture (UAS-4) is introduced to enhance performance through spatial interference distribution. Results confirm a broadband bandwidth exceeding 830 Hz achieved with an ultra-thin profile (0.1-0.2{\lambda}) and 80% ventilation. This work establishes a data-driven paradigm for discovering design principles in functional metamaterials.
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All authors Zhiwei Yang, Mengyu Li, Xiaohang Xie, Ao Chen, Thomas G. Bifano, Xin Zhang
Plasma Physics
Advances in laser-assisted nuclear decay and nuclear excitation
Q. Xiao, J. H. Cheng, Y. Y. Xu et al. (+4 more)
From the synthesis and
evolution of the elements to the celestial
nuclear processes of
stellar explosions and
neutron star mergers,
nuclear physics is the foundation of our understanding of the universe. After more than a century of progress, the field of
nuclear physics remains vibrant. The rapid advancement of
laser technology has opened unprecedented avenues in
nuclear physics, driven by the interdisciplinary convergence of
laser physics,
nuclear structure,
plasma science, and
quantum dynamics. This emerging field enables studies on
laser-induced
nuclear excitation,
laser assisted
nuclear decay, and precision manipulation of
nuclear isomers for optical clocks. This review comprehensively examines the research achievements over the past decade regarding the influence of
lasers on radioactive charged particle emissions and
nuclear excitation. Regarding theoretical developments, the review details various methods used to evaluate the interactions between
lasers and
nuclei, including the time-dependent Schrödinger equation for $\alpha$ decay,
proton radioactivity, and two-
proton radioactivity and
Fermi's golden rule for
nuclear excitation as well as the application and advancement of various theoretical models and approximation methods. In experimental research, the review synthesizes significant breakthroughs in
laser induced
nuclear excitation experiments, particularly emphasizing the excitation of the $^{229}$Th, $^{83}$Kr, and $^{45}$Sc. These achievements provide essential groundwork for future breakthroughs in both fundamental
nuclear science and its broader technological applications.
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All authors Q. Xiao, J. H. Cheng, Y. Y. Xu, Y. T. Zou, Z. Z. Ren, A. Ya. Dzyublik, T. P. Yu