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Physics Physics

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Friday 5 June

Optics

FLASH: Ultrafast beam quality characterization via spatial-to-temporal mapping

J. Qiu, Y. Xiong, X. Hua et al. (+2 more)

Accurate and real-time monitoring of spatial beam quality has emerged as the absolute prerequisite for intelligent optical field regulation and advanced laser applications. However, modern high-power and multimode optical systems exhibit highly complex, nonlinear, and transient behaviors. In these systems, the spatial beam profile undergoes dramatic reorganizations within extremely short timeframes. Phenomena such as spatio-temporal mode-locking, transient beam self-cleaning, and plasma-induced aberrations demand nanosecond-level dynamic characterization. Yet, capturing these ultrafast dynamics is fundamentally bottlenecked by the kilohertz frame rates of conventional two-dimensional image sensors. To break this dimensional and temporal barrier, we propose an ultrafast non-imaging beam quality monitoring technique, termed Fiber-based Laser Assessment via Spatial-to-temporal High-speed-mapping (FLASH). By utilizing a multimode fiber to encode spatial beam variations into high-dimensional speckle fingerprints and a multicore fiber delay line array to serialize these features, we transform two-dimensional spatial information into high-speed one-dimensional temporal pulse sequences. Empowered by a deep learning model to decipher the serialized signals, the FLASH system achieves an unprecedented 100 MHz measurement rate with a minimal mean relative error of 0.32%. Realizing a five-order-of-magnitude speed improvement over standard camera-based methods, this spatial-to-temporal mapping paradigm provides a transformative spatial oscilloscope. It unlocks new possibilities for real-time intelligent adaptive control and the exploration of complex multimode nonlinear physics.
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All authors J. Qiu, Y. Xiong, X. Hua, H. Wu, M. Tang

Chemical Physics

Distilling first-principles accuracy into compact machine learning potentials for condensed-phase chemistry

Sijia Chen, Niamh O'Neill, Benjamin X. Shi et al. (+1 more)

Accurate machine learning interatomic potentials (MLIPs) have made first-principles-quality potential energy surfaces increasingly accessible for condensed-phase chemistry, but their inference cost can still limit the sampling needed to compute experimentally relevant observables. In this work, we combine transfer learning and knowledge distillation to construct compact "student" models that retain the accuracy of much larger "teacher" models obtained by applying transfer learning to foundation models. The resulting students reduce production simulation cost by roughly an order of magnitude, making high-accuracy sampling practical for challenging condensed-phase problems. We demonstrate this across three problems of increasing sampling complexity: finite-temperature NPT simulations of ice Ih, classical and path-integral simulations of liquid water over 240-370 K, and path-integral umbrella-sampling simulations of water dissociation at the anatase TiO2(101)/water interface. In all cases, the distilled students reproduce the target observables of their teachers more reliably than models of the same size trained directly on the limited reference data. The liquid-water student, distilled from a {\Delta}-learned CCSD(T)-quality teacher, reproduces thermodynamic, structural, transport, and nuclear quantum properties over the full temperature range studied. At the TiO2/water interface, distillation makes PIMD umbrella sampling practical and shows that nuclear quantum effects lower the dissociation barrier by roughly 2 kcal/mol and shift the molecular-dissociated free energy difference into quantitative agreement with recent solid-state 17O NMR measurements. Our work demonstrates how knowledge distillation can make accurate MLIPs practical for the sampling methods needed to connect condensed-phase reaction thermodynamics with experiment, notably for interfacial chemistry and catalysis.
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All authors Sijia Chen, Niamh O'Neill, Benjamin X. Shi, Venkat Kapil

Atmospheric and Oceanic Physics · Cross-listed from nlin.CD

Loop Current Extension as an Effective Delayed Dynamical System

Francisco J. Beron-Vera, María J. Olascoaga and Philippe Miron

The Loop Current is the dominant circulation feature of the Gulf of Mexico and exhibits pronounced variability associated with northward extension, retraction, and eddy shedding. Despite decades of study, the extent to which this variability admits a reduced dynamical description remains unclear. We investigate this question using delayed-coordinate representations constructed from satellite-altimetry observations of Loop Current extension. Ridge regression, multilayer perceptron forecasting, and Sparse Identification of Nonlinear Dynamics (SINDy) are applied to learn delayed evolution maps from the extension time series. Forecast skill consistently exceeds persistence at lead times of 30–90 days while requiring only a small number of delayed coordinates. Ridge regression reveals saturation with delayed-state dimension, indicating that much of the predictive information is contained within a compact representation. Neural-network forecasts provide modest additional improvements, while delayed SINDy identifies sparse evolution maps involving intraseasonal memory scales, from approximately two weeks to a few months, that remain stable under recursive iteration. Physical diagnostics associated with Yucatan Channel inflow, Florida Straits outflow, gateway geometry, and northern Caribbean vorticity contain predictive information but do not provide additional independent state information once the delayed Loop Current state is included. These results support the interpretation of Loop Current extension as an observable evolving on an effective low-dimensional delayed dynamical system. A substantial fraction of the predictable variability can be reconstructed from a small number of delayed observations and represented through compact delayed evolution maps.
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Optics

High-Speed Multi-Dimensional Optical Field Measurement via MMF-MCF Spatial-Temporal Mapping Architecture

Yuxuan Xiong, Jingze Liu, Junjie Qiu et al. (+4 more)

Wavelength and state of polarization constitute fundamental dimensions of optical fields. While simultaneous quantification of these parameters is critical, existing methodologies often lack the speed required for real-time analysis. Here, we present a compact high-dimensional optical field analyzer employing a discrete spatiotemporal sampling architecture based on multimode and multicore fibers. An optical delay line array maps spatial speckle patterns into serial pulse sequences and facilitates efficient single-pixel detection. Leveraging a residual multilayer perceptron network, the system attains a wavelength mean absolute error of 0.25 pm and a polarization resolution of 0.2015 (in normalized Stokes space). Analysis of the spatial sampling density reveals that 5-6 sampling points are required to balance measurement rate and accuracy. Notably, the system exhibits isotropic fault tolerance against single-core failures. This confirms that optical field information is redundantly encoded across the entire fiber cross-section rather than localized in specific channels. This framework provides a solution for multiparameter decoupling under severe spatial downsampling and useful insights for the design of next generation high-speed and robust all-fiber analysis systems.
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All authors Yuxuan Xiong, Jingze Liu, Junjie Qiu, Zhuyixiao Liu, Zheng Gao, Hao Wu, Ming Tang

Optics

Ultralow shot noise limited giant passive resonant gyroscope for Earth rotation measurement

Yuhong Zhong, Yangsheng Cai, Zhanhao Liu et al. (+9 more)

Optical gyroscopes directly measure the Earth's rotation and are promising instruments for real-time geophysical observations and Earth orientation parameter (EOP) determination requiring both high precision and high temporal resolution. Large-scale ring laser gyroscopes (RLGs) currently reach rotational resolutions around $10^{-11}\,\mathrm{(rad/s)/\sqrt{Hz}}$, but their quantum noise limits make it challenging to meet the requirements of future high-temporal-resolution EOP measurements. Passive resonant gyroscopes (PRGs), on the other hand, offer a potentially lower photon shot noise limit and more flexible power scaling, even if their demonstrated rotational resolutions are still about two orders of magnitude below those of leading RLGs. Here we demonstrate a $64\,\mathrm{m^{2}}$ giant passive resonant gyroscope HUST-2, and develop with an extremely low shot noise level. We experimentally obtain a shot noise limited of $5.7(1)\times10^{-13}\,\mathrm{(rad/s)/\sqrt{Hz}}$ at $1\,\mathrm{mW}$ incident optical power, following the characteristic $1/\sqrt{P}$ scaling. Through systematic suppression of dominant technical noise sources, HUST-2 further achieves a measured rotational resolution of $3\times10^{-11}\,\mathrm{(rad/s)/\sqrt{Hz}}$, bringing PRGs into the performance regime of leading large-scale RLGs for the first time. The gap between the present demonstrated rotational resolution and the shot noise limit indicates nearly two orders of magnitude further improvement potential. Reaching this limit would enable high-precision length-of-day (LOD) measurements with $10$-$100\,\mathrm{s}$ temporal resolution and lays the foundation for future large-scale gyroscope networks dedicated to real-time EOP determination.
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All authors Yuhong Zhong, Yangsheng Cai, Zhanhao Liu, Lei Zheng, Yunhe Wang, Xiaojun Huang, Zhiyuan Wang, Kui Liu, Liangcheng Tu, Jun Luo, Zehuang Lu, Jie Zhang

Optics · Cross-listed from quant-ph

Cyclic ladder operators and hidden Weyl-Heisenberg structure in a Floquet system

Tianao Wu and Li Ge

Ladder operators, found in the quantum harmonic oscillator and other quantized systems, provide an elegant approach to solving or understanding otherwise intricate physics problems. In this Letter, we discuss cyclic ladder operators in both Hermitian and non-Hermitian systems with a finite Hilbert space, with the highest (lowest) level directly descending (ascending) to the lowest (highest) level via a single raising (lowering) operation. We show that an equally spaced energy ladder emerges when these systems have an underlying Weyl-Heisenberg commutation relation, with the cyclic ladder operators and the temporal evolution operator behaving as the generators of the Weyl-Heisenberg group. We further illustrate such a system using a one-dimensional Floquet lattice, where the cyclic ladder operators become diagonal and the temporal evolution simplifies to a permutation matrix after a Floquet period. Our findings reveal a hidden relation between non-trivial dynamics and algebraic principles in Floquet systems, which may exist for other quantum numbers as well besides the energy levels.
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Computational Physics · Cross-listed from math.NA

Multiscale Nudging: From Macroscopic Observations to Microscopic Dynamics

Liyao Lyu, Xinyue Yu and Hayden Schaeffer

We introduce a measure-based nudging framework for assimilating macroscopic observations into microscopic mean-field particle dynamics. The central difficulty is a representation mismatch: the forecast is a labeled particle system, while the observations specify only a smoothed, permutation-invariant density. To address this mismatch, we define the forecast-observation discrepancy as a quadratic functional on probability measures after applying the same smoothing operator used by the observation process. The Wasserstein gradient of this functional induces a transport velocity on state space, which yields a particle-level correction without constructing particle-to-particle matching, linearizing the dynamics, or estimating ensemble covariances. For a fixed observation scale, we prove well-posedness of the assimilated McKean-Vlasov dynamics and propagation of chaos for the interacting particle approximation. Under exact smoothed observations and an observability condition at the kernel scale, we establish an $L^2$-stability estimate showing exponential decay up to a bias floor controlled by model misspecification. Numerical experiments on linear, bimodal, chaotic, kinetic, and collective-motion systems demonstrate that the method can recover macroscopic structure from incomplete density-level observations.
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Accelerator Physics

Particle swarm optimization fitting of long-range wake potentials for trapped-mode parameter characterization in the HALF storage ring

Haiyan Yao, Tianlong He, Xiaoyu Liu et al. (+2 more)

Accurate extraction of trapped-mode impedance parameters of complex storage ring components is essential for assessing their impact on coupled-bunch instabilities. This paper proposes a parameter extraction method based on particle swarm optimization. By constructing a multi-resonator fitting model, trapped-mode parameters are extracted from partially decayed long-range wake potentials. Benchmark validation using a cylindrical pillbox cavity demonstrates that the proposed method yields results consistent with those obtained from the CST eigenmode solver and the existing differential evolution method for both longitudinal and transverse cases, while significantly reducing the computational cost. The method is further applied to three critical components of the Hefei Advanced Light Facility storage ring, demonstrating its applicability to complex structures.
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All authors Haiyan Yao, Tianlong He, Xiaoyu Liu, Weiwei Li, Zhenghe Bai

Medical Physics

The First Human-Based In Vitro Flow Loop and Quantification for Fetal Aortic Hemodynamics

Kamlesh Kumar, Biao Si, Pritom Saha et al. (+2 more)

Coarctation of the aorta (CoA) is a common congenital defect that remains difficult to diagnose prenatally due to subtle and evolving anatomical features. In the fetus, the ductus arteriosus creates a dual-inflow configuration that generates complex three-dimensional flow patterns not captured by standard imaging. Improved characterization of fetal hemodynamics may enhance diagnostic accuracy beyond anatomy-based assessment. This study presents the first human-based in vitro flow loop of the fetal aorta, constructed from anatomies reconstructed using medical imaging data. Models representing normal and coarctation conditions were fabricated and integrated into a physiological flow loop. Velocity fields were measured using planar and stereoscopic particle image velocimetry (PIV) to resolve near-wall and three-dimensional flow structures, enabling quantitative assessment of velocity gradients and wall shear stress (WSS) under normal and coarctation configurations. The in vitro flow loop closely reproduced target fetal flow segmentation, with segmental flow-rate errors generally below 6%. High-resolution planar and stereoscopic PIV revealed dual jets from the ascending aorta and the ductus arteriosus and predominantly planar flow in the normal aorta, but strong jet acceleration, separation, and reattachment in the coarcted geometry. Coarctation produced markedly elevated and spatially heterogeneous WSS, and 2-component PIV underestimated WSS by up to ~29% compared with 3-component measurements, especially in high-shear regions. These findings show that accurate three-component velocity measurements are critical for reliable WSS estimation and suggest that detailed hemodynamic metrics, such as WSS, may serve as potential biomarkers to enhance fetal CoA diagnosis beyond anatomy alone.
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All authors Kamlesh Kumar, Biao Si, Pritom Saha, Shuping Ge, Zhenglun Alan Wei

Optics

Passive all-optical synchronization for polarization-maintaining ultrafast fiber lasers

Kun Huang, Jing Zeng, Jiwei Gan et al. (+3 more)

We have proposed and implemented for the first time to our best knowledge a passive and all-optical pulse synchronization for polarization-maintaining ultrafast fiber lasers. Specifically, the synchronization system was comprised of two independent Yb-doped and Er-doped mode-locked fiber lasers in a master-slave configuration. Master pulses were injected into the slave laser cavity consisting of a nonlinear amplifying loop mirror, which provided an effective fast intensity modulator due to the periodic introduction of nonreciprocal phase difference. As a result, robust and tight timing synchronization was achieved with a cavity mismatch tolerance of 800 $\mu$m and a relative timing jitter of 26 fs within 1-MHz bandwidth. In combination with all-polarization-maintaining structure of fiber lasers, long-term stable operation was demonstrated over 12 hours without the need of temperature stabilization and vibration isolation. The implemented synchronous laser system could find immediate applications such as pump-probe microscopy, two-color spectroscopy and nonlinear frequency mixing.
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All authors Kun Huang, Jing Zeng, Jiwei Gan, Qiang Hao, Ming Yan, Heping Zeng

Atomic Physics · Cross-listed from quant-ph

Machine-Learning Optimization and Characterization of a High-Optical-Depth Two-Color Nanofiber Trap

W. Crump, M. Sadeghi and M.D. Hoogerland

Optical nanofibers provide a way of coupling quantum information in cold atoms across large distances, however, this coupling requires atoms to reside close to the nanofiber surface. Atoms can be trapped close to the surface using a two-color dipole trap. Here we present our experimental realization of a two-color dipole trap. We optimize the number of trapped atoms using a machine learning algorithm and measure the optical density via the transmission. We estimate the number of atoms in the trap to be approximately 1400 and the lifetime of the atoms in the trap to be 28 ms. Machine-learning optimization improved the on-resonance optical depth from 0.5 in the initial optimization stage to optical depths exceeding 15.
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Plasma Physics

Flow-Regulated Suprathermal Particle Acceleration in Weakly Collisional Astrophysical Plasmas

Ji-Hoon Ha and Elena S. Volnova

We investigate the formation of suprathermal particle populations in weakly collisional plasmas using a one-dimensional Fokker-Planck framework. A key element of this work is the introduction of a systematic velocity-space drift term that represents net energization relative to a background streaming flow. This term provides a minimal phenomenological description of competing relaxation and acceleration processes, enabling the incorporation of large-scale plasma dynamics into kinetic particle evolution. The model further includes spatial advection, velocity-space diffusion associated with wave-particle interactions, and collisional relaxation. To explore the role of time-dependent large-scale plasma dynamics, we consider three representative temporal profiles of the streaming velocity: accelerating, decelerating, and steady flows. We find that velocity-space diffusion primarily governs the formation of suprathermal tails, while the streaming-induced drift regulates their efficiency and spectral properties. In particular, the overall fraction of suprathermal particles depends only weakly on the detailed temporal evolution of the flow and is largely controlled by the time-averaged streaming velocity. These results suggest that large-scale streaming motions can be incorporated as an effective systematic energization mechanism in weakly collisional plasmas, providing a minimal and flexible framework applicable to a broad range of space and astrophysical environments.
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Thursday 4 June

Computational Physics · Cross-listed from cs.AI

PhononBench-MP40: a spectrum-resolved benchmark dataset for phonon stability

Wen-Kao Li, Ze-Feng Gao and Zhong-Yi Lu

Imaginary phonon modes remain a practical bottleneck in computational materials screening because otherwise plausible structures can be locally dynamically unstable under a chosen workflow. Here we present PhononBench-MP40, a spectrum-resolved benchmark dataset of Materials Project-derived crystals for workflow-defined phonon stability. The dataset starts from 47,969 MP40 workflow tasks and provides 46,899 completed records with paired stability labels and local phonopy YAML spectra, including 16,683 Stable records and 30,216 completed-phonon unstable records. A further 1,067 relaxation failures are reported separately rather than merged into the completed phonon denominator. The release centers on the local YAML spectrum: the stability label, the lowest sampled frequency and any threshold-dependent relabeling are derived from that spectrum. The dataset is openly available through Science Data Bank at https://doi.org/10.57760/sciencedb.38735. A companion GitHub repository provides the calculation code and lightweight access utilities. PhononBench-MP40 provides an auditable reference for workflow-defined stability classification, minimum-frequency analysis, threshold studies and failure-aware triage, while keeping the reference workflow, data schema and interpretation boundaries explicit.
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Computational Physics

Tensor network compression using fluid dynamics as a testbed: Analytical foundations in one dimension

Matthew D. Horner, Callum W. Duncan, Oliver T. Brown et al. (+2 more)

High performance computers produce extreme-scale data sets that require sampling or compression if they are to be used to their full potential. Existing data compression techniques typically exploit features such as sparsity in the data, homogeneity in the data, or a priori knowledge of what subsets of data are of most interest. Fluid dynamics data in general do not exhibit these features and so are attractive test beds for generic compression techniques that are objective, robust, and tuneable with respect to information lost due to compression. Presented here is a method based on tensor networks, specifically matrix product states or tensor trains, that meets these requirements. The method is demonstrated for compression in one-dimension and is extensible to higher dimensionality. Lossless compression is demonstrated for random Fourier series for sufficiently high bond dimension of the tensor network, with the memory required to store the tensor network scaling directly proportional to the bond dimension. The lossy compression exhibited at lower bond dimension can be well within the relative error of many fluid simulations. The compression algorithm is tested for the time evolution of Burger's equation with excellent results. We additionally demonstrate the capability to perform computations in the compressed form through a tensor network periodic convolution that can be orders of magnitude faster than using fast Fourier transforms and the convolution theorem. In addition to being an attractive method for working with data sets generated by existing computers, the tensor network methods utilised are directly translatable to the emerging paradigm of quantum computing.
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All authors Matthew D. Horner, Callum W. Duncan, Oliver T. Brown, Stephen M. de Bruyn Kops, Muralikrishnan Gopalakrishnan Meena

Physics and Society

The Competitiveness of Renewables: An Analysis of Magnitude, Geography, and Drivers

Pascal Fröhlich, Maximilian Bernecker and Felix Müsgens

While renewable energy sources are the fastest-growing electricity generation technology globally, their competitiveness is still the subject of controversy. This paper presents an electricity system model for investment and dispatch to determine the cost-optimal shares of renewable energy sources. We compute and analyse renewable generation shares in market equilibrium for Germany and Texas, using annual data for 2015 to 2024, and in five-year intervals for 2030 to 2050. Furthermore, we identify the key drivers of the renewable competitiveness and quantify their contribution through parameter variations. Our results show that renewable generation achieves considerable market shares even without subsidies. In Germany, the increase in renewable generation is primarily driven by CO2 pricing, complemented by declining investment costs for renewable technologies. In Texas, solar PV is part of the cost-optimal system, even in the absence of CO2 pricing and despite low natural gas prices.
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History and Philosophy of Physics

Erdal İnönü at 100: From the Sphere to the Plane

Ilmar Gahramanov

On the centennial of Erdal İnönü's birth, this article reflects on his scientific legacy and his role in shaping modern theoretical physics in Türkiye. We briefly discuss his life, scientific vision, and contributions to academic institutions, and then turn to his most celebrated scientific achievement: the İnönü-Wigner contraction. Through the simple geometric example of a sphere becoming a plane, we present an accessible introduction to this important idea and its significance for modern physics.
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Optics · Cross-listed from eess.IV

The Need for Neural ISP in the Small-Pixel Era: How Shrinking Pixels Push Optics to the Limit and Neural Restoration Pushes Back

Jingxi Li, Neerja Aggarwal, Laurent Gudemann et al. (+4 more)

Smartphone telephoto cameras are approaching a "telephoto physics wall": as pixel pitches shrink toward sub-0.5 micron, the optics remain limited by geometric aberrations, leading to diminishing returns on resolution. Traditional Image Signal Processors (ISPs) cannot eliminate these aberrations, because they operate through local, stage-wise processing with no explicit model of the underlying point spread function (PSF). We demonstrate how a learning-based Neural ISP for image restoration, trained on the underlying degradations, inverts what stage-wise pipelines cannot, turning small-pixel designs into a net advantage. We investigate this through a controlled simulation of a representative telephoto module, evaluating five configurations (0.35–0.75 micron pixel pitch). The aperture is scaled proportionally to keep per-pixel SNR and diffraction spot size fixed, thereby isolating geometric aberration and spatial sampling. While the traditional ISP improves only modestly with smaller pixels, the Neural ISP scales substantially: at 0.35 micron} it reaches 745 cycles/mm MTF50 (vertical), a 2.5–3x resolution improvement over the traditional ISP, and LPIPS improves significantly from 0.244 to 0.151 while traditional results stay comparatively flat. In a low-SNR extension (15 dB per-frame bursts at 0.35 micron), a multi-frame Neural ISP recovers performance close to the bright-light single-frame baseline, whereas a multi-frame traditional ISP shows no meaningful improvement – indicating that traditional pipelines at small pixels are bottlenecked by uncorrected PSF blur rather than by noise. These results point to a design philosophy in which Neural ISPs enable high-resolution telephoto modules by correcting residual optical aberrations rather than requiring increasingly complex optics.
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All authors Jingxi Li, Neerja Aggarwal, Laurent Gudemann, Shivansh Rao, Vishal Vinod, Tom E. Bishop, Ziv Attar

Data Analysis and Statistics

Design Principles for AI-Ready QCD Data with a Barrel Imaging Calorimeter Application

Zhiwan Xu, Sylvester Joosten, Minho Kim et al. (+2 more)

Data from large physics collider experiments in Quantum Chromodynamics (QCD) research differ fundamentally from the modalities used in modern foundation models. The heterogeneity of detector readouts and their technology dependence require principled curation for cross experiment AI applications. We present a design framework for AI-ready QCD data to define a unified data structure that accommodates heterogeneous detector technologies within a single schema. We apply the design principle to the simulated data of the Barrel Imaging Calorimeter (BIC) in the ePIC detector at the Electron–Ion Collider. The BIC simulation data combines AstroPix silicon pixel imaging layers with Pb/ScFi calorimeter layers across different readout types. We describe the schema specialization, data preparation pipeline, and visualization of the curated AI-ready dataset.
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All authors Zhiwan Xu, Sylvester Joosten, Minho Kim, Chun Yuen Tsang, Maria Zurek

Accelerator Physics

Manufacturability studies for the FCC-ee positron source target: determination of the minimum bending radius and ovalization in tantalum cooling tube elbows

Ramiro Mena-Andrade, Mickaell Crouvizier, Jean-Philippe Rigaud et al. (+2 more)

Beam intercepting devices rely on cooling systems to effectively dissipate the thermal energy generated during the impact of a high-energy beam. Regardless of the device's size, integrating the cooling system is a complex task, particularly when the resulting device is only a few centimetres in size, as is the case with the positron source target for the Future Circular Collider at CERN, where the current design consists of a tungsten core with two embedded tantalum cooling tubes. Due to the reduced dimensions of the chosen tantalum tubes (OD6.35xID4.35 mm), the selected manufacturing method is compression bending. The present study develops and evaluates a numerical model to manufacture the required elbow. The methodology is divided in four steps: i) minium allowable bending radius calculation, ii) material constitutive law validation, iii) prediction of the resulting distortion due to ovalization and iv) experimental validation via (non) destructive methods. The results indicate that a minimum bending radius of 10 mm is suitable for manufacturing the elbow. The distortion caused by ovalization is within +-0.5 mm, resulting in an important deviation respect to the nominal geometry. The numerical model was successfully validated experimentally. The micrographies performed in the cross-section of the tantalum tube before and after plastic bending confirm the integrity of the elbow. Additionally, an empirical expression is proposed to estimate the yield stress of pure tantalum based on Vickers hardness measurements. The proposed numerical model is capable to predict the ovalization along the resulting elbow, offering a viable alternative to define the cooling tube geometry. This study provides a methodology to determine the minimum bending radius for thick walled tubes to be used with compression bending and can be applied for the cooling system design of other high-performance devices
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All authors Ramiro Mena-Andrade, Mickaell Crouvizier, Jean-Philippe Rigaud, Thibaut Coiffet, Antonio Perillo-Marcone

Fluid Dynamics

Vortex gust interactions with a freely-flying rigid airfoil

Bingfei Yan and Jennifer A. Franck

This study numerically investigates the interaction between an isolated vortex gust and a freely-flying airfoil, introducing a theoretical framework for interpreting the coupled lift and heave response. This complex and coupled dynamics is important for modern light-weight aircraft where gusts may easily perturb the wing, generating transient changes in trajectory and attitude. Here, the freely-flying airfoil is modeled with a single degree-of-freedom in heave, and is impacted by an isolated vortex gust generated upstream. Computational results demonstrate that the freely-flying airfoil reaches a maximum heave displacement after vortex impingement and subsequently rebounds with a comparable magnitude. The lift coefficient is then modeled by augmenting the lift from a corresponding stationary airfoil interaction with motion induced contributions associated with the induced angle of attack and added-mass. A comparison of the modeled lift with the simulation data confirms that the dynamics of the airfoil before impingement is dominated by these two terms, however the rebound after impingement is only partially explained by the model since it is also influenced by the gust-induced vortex shedding. Comparisons across various parameters show that the pre-impingement motion depends primarily on vortex rotation direction, whereas the post-impingement and induced shedding patterns vary with respect to angle of attack and vortex transverse position. With the lift coefficient of the corresponding stationary airfoil interaction as an input, the model can successfully predict the heave trajectory, thus providing a mechanism to assess the dynamic motion of an airfoil from experimental/computational data of gusts interacting with fixed airfoils.
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Instrumentation and Detectors

Lightfall: An API-first, LLM-addressable control platform for synchrotron beamlines

Ronald J. Pandolfi, Damian Guenzing, Marcus M. Noack et al. (+2 more)

Synchrotron beamlines differ in hardware, technique, and workflow, making customized control interfaces necessary; bespoke per-beamline graphical user interfaces (GUIs) do not scale well, one-size-fits-all facility software forces compromises that leave most of the interface unused, and even recent component-library approaches keep per-scientist tweaks on a developer's queue. We present Lightfall, a control platform designed for facility-wide use, whose API-first architecture exposes every panel, device, and scan plan through a single uniform addressable interface. An embedded language-model agent drives experiments through that interface, from a single move-and-read to a Gaussian-process-driven autonomous scan, while beamline staff extend the interface during operation via skills: plugin modules the agent invokes to compose and modify panels in the running application. The result is a closed development loop: a beamline scientist authors a panel change in natural language, the agent emits and applies it, and the commit lands in the beamline's plugin repository as a side effect. The per-iteration cost of a scientist-driven change is then fixed in the scientist's own time rather than in developer hours the facility must supply. Lightfall is in testing at the COSMIC-Scattering beamline at the Advanced Light Source.
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All authors Ronald J. Pandolfi, Damian Guenzing, Marcus M. Noack, Sophie A. Morley, Damon English

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

Plasticity of Neutron Star Crusts

Matthew E Caplan, Nevin T Smith, Ashley J Bransgrove et al. (+1 more)

We use first-principles molecular dynamics simulations to study the deformation and breaking of neutron star crusts. When simulating with strain rates several orders of magnitude slower than prior work, we find a new regime of steady plastic flow beyond the breaking point that is independent of the initial crystal structure. Polycrystals exhibit a robust transition from linear elasticity to perfect plastic flow at shear strains of $\epsilon = 0.05$, while monocrystals break at $\epsilon = 0.11$ and then flow plastically. The universal post-break plasticity may arise because the crystal self-consistently assumes a defect density to accommodate the imposed strain rate. If broken crusts can re-anneal to large crystal sizes, crust breaking may repeat with implications for magnetar bursts and flares.
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All authors Matthew E Caplan, Nevin T Smith, Ashley J Bransgrove, Charles J Horowitz

Fluid Dynamics

Fluctuation-induced and quantum effects in nanofluidic transport

Adrien Sutter, Peter Gispert, Baptiste Coquinot et al. (+2 more)

The hydrodynamic wall has traditionally been considered a featureless object, whose only role is to provide a boundary for fluid flow. Yet, there is now ample evidence that at nanometer scales, liquid flows are sensitive to the wall's internal – in particular, electronic – degrees of freedom. Here, after reviewing the experimental evidence for nanoscale liquid-electron couplings, we present the theoretical advances that have allowed for their quantitative understanding. We discuss how a quantum description of the liquid-solid interface reveals the influence of electron dynamics on classical fluid transport, in the form of the fluctuation-induced quantum friction effect. Quantum friction is at the root of liquid-electron coupled transport phenomena, that may be combined into a hydro-electronic transport matrix. We present analytical formulas for the hydro-electronic transport coefficients, that allow for their quantitative estimation in practical cases; we further outline the potential consequences of coupled liquid-electron transport for the water-energy nexus. Fluctuation-induced and quantum effects at liquid-solid interfaces represent an emerging interface between fluid dynamics and condensed-matter physics, and a largely uncharted territory for both theory and experiment.
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All authors Adrien Sutter, Peter Gispert, Baptiste Coquinot, Lydéric Bocquet, Nikita Kavokine

Computational Physics · Cross-listed from cs.LG

Capturing non-Markovian dynamics in non-equilibrium stochastic systems using flow matching

Bhargav Sriram Siddani, John B. Bell, Alejandro L. Garcia et al. (+1 more)

Hydrodynamic models of stochastic particle systems represented by coarse-grained stochastic partial differential equations (SPDE), such as the regularized Dean-Kawasaki (DK) equation, do not accurately capture the short-time system dynamics that is dominated by non-Markovian effects, and low particle density regimes where the distributions are highly non-Gaussian. We develop a generative flow matching method that directly models the probability distribution of fluxes from particle simulations that explicitly incorporates non-Markovian and non-Gaussian effects. As a demonstration, we use this method to simulate the Kramers first passage time problem for a system of non-interacting Brownian particles. We show the model accurately captures the short-time behavior and provides better predictions of the statistical moments of the number density when compared against the solution of the Markovian baseline, regularized DK equation.
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All authors Bhargav Sriram Siddani, John B. Bell, Alejandro L. Garcia, Ishan Srivastava

Optics

Reconfigurable Single-Ring Photonic Molecule on Lithium Niobate

Tianyi Zhang, André Garcia Primo, Jiawen Liu et al. (+2 more)

Resonant photonic structures enable optical enhancement and spectral filtering and are essential for lasers, quantum emitters, transducers, or modulators. Photonic molecules, formed by mode hybridisation in two coupled resonators, break the equidistant frequency spacing of zero-dispersion resonators and provide control over their spectrum. Reconfigurability over these devices is a key asset, allowing to align photonic resonances to target frequencies on-demand. While electro-optic materials such as thin-film lithium niobate (TFLN) have enabled frequency tuning beyond traditional thermo-optic effects, they require continuous bias, posing challenges to scalability. Here we demonstrate an optically programmable, erasable, and rewritable photonic molecule realized within a single TFLN racetrack resonator. A long-lasting photorefractive grating induced through interference of co-propagating dark and bright transverse modes promotes their hybridisation, forming a single-ring photonic molecule. We observe GHz-scale hybrid-mode splitting over a 700 GHz-wide optical bandwidth and hour-long lifetimes, and show that their coupling strength can be programmed by the optical pump used to write the grating. By selectively pumping orthogonal hybridised modes, we further demonstrate multiple reversible all-optical write-erase-rewrite cycles of these gratings. Finally, we use this technique to realize single-sideband mmWave transduction around 107 GHz with a 5 GHz tuning bandwidth. These results establish photorefraction as a reliable mechanism for reconfigurable resonances in TFLN, and suggest a route towards tunable microwave-optical functionalities within a reduced footprint.
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All authors Tianyi Zhang, André Garcia Primo, Jiawen Liu, Aleksei Gaier, Ileana-Cristina Benea-Chelmus

Accelerator Physics

Low Level RF and Timing System Design for the Cool Copper Collider

Chao Liu, Ankur Dhar, Martin Breidenbach et al. (+1 more)

The Cool Copper Collider (C3) is a linear accelerator (LINAC) concept based on compact, high gradient, and normal conducting accelerator technology to support Higgs boson studies at 250 GeV and 550 GeV center of mass. The C3 accelerator is ten kilometers in scale and consist of 2,200 RF stations for 550 GeV center of mass. To maintain the stringent beam quality required by the collider across the LINACs, each of the cavities has a dedicated low-level RF (LLRF) system to stabilize the phase and amplitude of the field in the cavities from pulse to pulse and to compensate the fluctuation of the RF field within each pulse introduced by the beam loading process. To meet the design goals of being compact and affordable for future accelerators, we have designed the next generation LLRF (NG-LLRF) with a higher integration level based on radio frequency system-on-chip (RFSoC) technology. The NG-LLRF system samples RF signals directly and performs RF mixing digitally. The NG-LLRF has been characterized in loopback mode to evaluate the performance of the system and has also been tested with a standing-wave accelerating structure, a prototype structure for the C3 with peak RF power level up to 16.45 MW. This paper will focus on introducing the LLRF system design and timing system for C3 and the current NG-LLRF design. The high-power test results at different stages of the test setup with several pulse modulation schemes, including square pulse, pulse with phase reversals, and pulse trains, will be summarized, analyzed, and discussed.
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All authors Chao Liu, Ankur Dhar, Martin Breidenbach, Emilio Nanni

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Matching Terahertz and Hall Mobilities as a Hallmark of Intrinsic Charge Transport in Metal-Halide Perovskites

Dmitry R. Maslennikov, Ben P. Carwithen, Vladimir V. Bruevich et al. (+9 more)

Charge-carrier transport in soft-lattice materials, including metal-halide perovskites, is often perceived to be highly heterogeneous across different length scales, and influenced by both the intrinsic (dynamic) thermal electronic disorder and extrinsic (static) disorder due to crystal defects, impurities, grain boundaries, and surface states. As a consequence, the reported carrier mobilities obtained by different electrical and optical measurement techniques frequently disagree, raising a critical question: can a truly intrinsic charge transport regime (that is, a regime not dominated by static disorder) extend across macroscopic single crystals of these materials? Here, we demonstrate such a regime in an exemplary metal-halide perovskite system, epitaxial CsPbBr$_{3}$ single crystals, where the local mobility obtained via optical pump-terahertz probe (OPTP) spectroscopy quantitatively agrees with the macroscopic transport mobility across a broad range of experimental conditions. Using a dedicated device platform that enables concurrent Hall-effect and OPTP measurements on the same single-crystalline sample, we obtain consistent room-temperature mobilities of ~ 30 cm$^{2}$V$^{-1}$s$^{-1}$, among the highest reliably reported for CsPbBr$_{3}$. Both techniques reveal band-like temperature dependence of the hole mobility with similar power exponents, confirming that the same intrinsic transport mechanism governs the ultrafast/local and steady-state/macroscopic responses. These results show that defect-free charge transport is achievable in soft-lattice perovskites on millimetre length scales and establish a robust methodology for benchmarking intrinsic mobility in emerging semiconductors.
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All authors Dmitry R. Maslennikov, Ben P. Carwithen, Vladimir V. Bruevich, Yichao Cai, Davide Nodari, Navendu Mondal, Xijia Zheng, Beier Hu, Nicola Gasparini, Jarvist M. Frost, Vitaly Podzorov, Artem A. Bakulin

Chemical Physics

Prolate spheroidal wave functions enable fast and exponent-aware long-range machine learning interatomic potentials

Jiuyang Liang, Libin Lu, Yajie Ji et al. (+1 more)

Long-range interactions such as electrostatics and dispersion remain a central bottleneck for machine learning interatomic potentials (MLIPs), especially in ionic, polar and interfacial systems. Ewald-based reciprocal-space mechanisms provide a physically grounded route for capturing these nonlocal effects, but often require dense Fourier grids and can become memory-limited at scale. This problem is particularly pronounced in molecular dynamics, where high efficiency requirements make accurate long-range modelling particularly costly. Here we introduce PSWF-LR, an exponent-aware long-range framework based on prolate spheroidal wave functions (PSWFs) that can be easily incorporated into existing model architectures. Its core components are PSWF-based mollification and atom-grid spreading, which enable compact and efficient representation of arbitrary inverse-power channels $1/r^p$ while treating the decay exponent as a physical prior. Across diverse long-range benchmarks, PSWF-LR reduces Fourier-mode requirements, improves energy and force accuracy, accelerates production-level simulations by about threefold, and extends long-range MLIP simulations beyond the memory limits of conventional MLIPs.
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All authors Jiuyang Liang, Libin Lu, Yajie Ji, Shidong Jiang

Data Analysis and Statistics · Cross-listed from hep-ph

Reweighting Adversarial Networks for Unbinned Unfolding

Umar Sohail Qureshi, Krish Desai, Jesse Thaler et al. (+1 more)

Differential cross sections are the currency of scientific exchange in particle and nuclear physics. Recently, machine learning methods have enabled unbinned and high-dimensional cross section measurements through new approaches to unfolding. A key challenge with unfolding is that it is a bi-level optimization problem where constraints are available at the detector level while the target is at the particle level, linked by a stochastic detector response. Further complications arise when the particle-level and detector-level distributions have non-overlapping or only partially overlapping support, which can destabilize training and degrade unfolding performance. In this paper, we introduce a new unbinned unfolding technique called the Reweighting Adversarial Network (RAN), which can be viewed as a generalization of the Moment Unfolding protocol to accommodate full phase-space unfolding. RANs address the bi-level optimization problem through a particle-level reweighting function steered by a Wasserstein critic at the detector level. RANs do not require overlapping support at the detector level, nor multiple iterations of training. We evaluate the performance of RANs with Gaussian data and jet substructure studies, including cases specifically designed to stress test the method under vanishing support overlap. We demonstrate that RANs outperform state-of-the-art methods in accuracy and have a lower computational overhead.
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All authors Umar Sohail Qureshi, Krish Desai, Jesse Thaler, Benjamin Nachman

Space Physics · Cross-listed from astro-ph.SR

Nonthermal line broadening at solar flare footpoints is primarily field-aligned

Andy S. H. To and Alexander J. B. Russell

Magnetic reconnection powers solar and stellar flares, but a full understanding of how the released energy is transported and converted within the solar atmosphere remains elusive. One clue lies at solar-flare footpoints, where spectral lines are far broader than the electron temperature alone can explain. Unresolved flows, waves, turbulence and ion heating have all been proposed, but observations have not yet conclusively distinguished between these mechanisms. Here we perform an unprecedented geometric test for flare footpoints, using 4,593 Hinode/EIS spectra from 407 C- to M-class flares. Line widths decrease systematically from disk centre to limb in all coronal emission lines, showing that the dominant broadening component is magnetic field aligned rather than isotropic or transverse. Cooler lines retain substantial broadening into the early decay phase, consistent with persistent unresolved field-aligned flows or line-of-sight velocity gradients. Hotter lines show an impulsive component that decays rapidly after the soft X-ray peak, consistent with preferential ion heating and ion temperature anisotropy. These findings resolve the long-standing question of the nature of line broadening at flare footpoints, place direct limits on flare energetics, and motivate a new direction in flare physics incorporating distinct field-aligned and perpendicular ion temperatures that exceed the electron temperature.
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