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Physics Physics

physics Watch Physics

Thursday 26 February

Atomic Physics · Cross-listed from quant-ph

Polarization-selective quantum cooperative response in dual-species atom arrays

Huan Wang, Shangguo Zhu, Yun Long et al. (+4 more)

Atom arrays have emerged as a powerful platform for quantum light-matter interfaces, yet single-species arrays are constrained by in-plane symmetry, restricting polarization control. Here we investigate the cooperative optical response of dual-species subwavelength atom arrays, in which intrinsic polarizability difference breaks in-plane symmetry. By engineering the lattice constants and detunings, the arrays exhibit polarization-dependent subradiant modes, enabling complete reflection of a specific polarization component. Leveraging this mechanism, we assemble array units as functional pixels and demonstrate a scalable polarization-selective quantum light modulator. Our work establishes a dynamically reconfigurable atomic-photonic platform for versatile subwavelength quantum optical elements.
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All authors Huan Wang, Shangguo Zhu, Yun Long, Fei Zhang, Yinghui Guo, Mingbo Pu, Xiangang Luo

Computational Physics

Ceci n'est pas un committor, yet it samples like one: efficient sampling via approximated committor functions

Enrico Trizio, Giorgia Rossi and Michele Parrinello

Atomistic simulations are widely used to investigate reactive processes but are often limited by the rare event problem due to kinetic bottlenecks. We recently introduced an enhanced sampling approach based on the committor function, machine-learned following a variational principle. This method combines a transition-state-oriented bias potential, expressed as a functional of the committor, with a metadynamics-like bias along a committor-based collective variable, enabling uniform exploration of reaction pathways. In its original formulation, the committor is represented by a neural network that takes physical descriptors as input and is trained by minimizing a functional involving gradients with respect to atomic coordinates, which can be computationally demanding in some cases. Here, we propose a simplified learning criterion formulated entirely in the descriptor space, which bypasses the need for explicit and costly coordinate gradients and provides a relaxed upper bound to the original variational principle. Although this approach does not formally target the exact committor, we show that it retains robust sampling performance while significantly reducing computational costs, thus enabling the study of processes that would be practically unfeasible using the original formulation.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci

Efficient training of generative models from multireference simulations and its application to the design of Dy complexes with large magnetic anisotropy

Zahra Khatibi, Lorenzo A. Mariano, Lion Frangoulis et al. (+1 more)

Generative machine learning models can potentially provide direct access to novel and relevant portions of the full chemical space, overcoming the cost of systematic sampling. However, the training of these models generally requires a large amount of data, often precluding the use of expensive high-level ab initio simulations for this task. The generation of coordination compounds of Dy with large magnetic anisotropy represents a topical example, where multireference simulations of large molecules are necessary to perform reliable predictions. Here, we show that a semi-supervised chemically-inspired training-by-proxy of generative variational autoencoders can reduce the cost associated with building a training set from multireference simulations by two orders of magnitude. We illustrate the power of this approach by generating 100s of new organic ligands for Dy(III) pentagonal bipyramidal complexes exhibiting record values of magnetic anisotropy, while starting from datasets as small as 1k multireference calculations. This work thus paves the way to the computational generation of molecules as complex coordination compounds with target electronic and magnetic properties.
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All authors Zahra Khatibi, Lorenzo A. Mariano, Lion Frangoulis, Alessandro Lunghi

Chemical Physics

Evidence of orbital mixing upon ionization via Cooper minimum photoelectron dynamics in epichlorohydrin. Experiment and Theory

L. Schio, M. Alagia, T. Moitra et al. (+18 more)

A peculiar electron correlation effect, leading to orbital rotation upon ionization, theoretically predicted long ago, was never experimentally characterized. The effect is expected to appear prominently in the photoionization of chiral molecules, due to the lack of symmetry constraints to wave-functions mixing. This is observed to have a profound effect on the photoelectron dynamics, as here demonstrated by investigating e̱ta} asymmetry parameters and partial cross-section observables in the Cl 3p Cooper minimum region of epichlorohydrin, a chiral prototype system. Angle-resolved photoelectron spectroscopy with tunable synchrotron radiation allowed measuring Cooper minimum $\beta$ oscillations, which were observed for solely two valence photoionization channels. The nature and number of channels exhibiting such dynamical behavior, along with the extent of the observed oscillation amplitudes, could not be accounted for by predictions based on Hartree-Fock (HF) and Density Functional Theory (DFT). These features could only be explained by incorporating correlation effects, which mix single-hole configurations of identical symmetry, in the characterization of the four lowest-lying molecular cation states, via equation-of-motion coupled cluster singles and doubles Dyson orbitals.
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All authors L. Schio, M. Alagia, T. Moitra, D. Toffoli, A. Ponzi, M. Stener, S. Coriani, P. Decleva, O. Rebrov, V. Zhaunerchyk, M. Larsson, S. Falcinelli, A. A. Dias, D. Catone, S. Turchini, N. Zema, F. Salvador, D. Benedetti, D. Vivoda, B. Botta, S. Stranges

Optics · Cross-listed from quant-ph

Connecting Quantum Contextuality and Nonlocality

Jianqi Sheng, Dongkai Zhang and Lixiang Chen

Quantum theory departs from classical physics in its treatment of correlations, most prominently through the phenomena of contextuality and nonlocality. Once regarded primarily as foundational curiosities, these effects are now understood as key operational resources for quantum computation, communication, and simulation. Although traditionally investigated in distinct settings, recent theoretical and experimental advances have revealed deep conceptual, mathematical, and operational connections between them. This review presents a unified perspective on these developments based on sheaf-theoretic and graph-theoretic frameworks, which provide theory-independent characterizations of statistical correlations. These approaches clarify the structural relationship between contextuality and nonlocality, facilitate the formulation of experimentally testable inequalities, and guide implementations in realistic physical platforms, with particular emphasis on photonic systems. By bridging abstract theoretical structures and concrete experimental realizations, this review sheds light on the nonclassical foundations of quantum correlations and their emerging role in quantum technologies.
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Accelerator Physics

RF Basics I & II

Frank Gerigk

This lecture starts with a brief historical introduction and an explanation how to get from Maxwell's Equations to a simple cavity. After simplifying and adapting the equations for their application to Radio Frequency problems, the most important formulae and characteristics for cavities and wave-guides are derived. The most common figures of merit are explained and some of the different cavity types are introduced. The alternative description of cavities as a lumped circuit model is then introduced, which is often used to characterise the cavity-coupler-generator interplay.
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Chemical Physics

Learning Thermal Response Forces: A Method for Extending the Thermodynamic Transferability of Coarse-Grained Models via Machine-Learning

Patrick G. Sahrmann, Benjamin T. Nebgen, Kipton Barros et al. (+1 more)

Machine-learned (ML) coarse-grained (CG) models are a promising tool for significantly enhancing the efficiency of molecular simulations by systematically removing degrees of freedom while retaining fidelity to the underlying fine-grained model. The CG potential of mean force (PMF) is inherently dependent on thermodynamic conditions and, hence, a CG force-field (FF) which is trained at one thermodynamic state point is not necessarily accurate at another. We propose, in this work, a novel and data-efficient means of learning temperature dependence into ML CG force-fields via training on the thermal response forces of the PMF. We demonstrate how incorporating these terms into ML CG FFs confers significantly improved transferability for CG water models and demonstrate how this transferability enables accurate and predictive CG dynamics.
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All authors Patrick G. Sahrmann, Benjamin T. Nebgen, Kipton Barros, Brenden W. Hamilton

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

Spectral Universality of Turbulent Fluctuations in Relativistic Flows

Alexander G. Tevzadze

We develop a Lorentz-covariant framework for projecting spacetime spectra into temporal spectra of stationary turbulent fluctuations in relativistic flows. For self-similar spacetime spectra, we derive a universal scaling relation, $\alpha = \beta - D$, where $\alpha$ is the temporal spectral index, $\beta$ the spacetime homogeneity exponent, and $D$ the effective dimensionality of spectral support. We further demonstrate that this universality breaks down when spacetime homogeneity is violated. Temporal spectra in relativistic flows are thus intrinsically nonlocal observables, requiring a covariant projection framework that establishes a general principle for spectral inference in relativistic plasma turbulence and high-energy plasma flows.
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Fluid Dynamics · Cross-listed from cs.LG

Efficient Adaptation of ROMs for Unsteady Flows Using Data Assimilation

Ismaël Zighed, Andrea Nóvoa, Luca Magri et al. (+1 more)

We propose an efficient retraining strategy for a parameterized Reduced Order Model (ROM) that attains accuracy comparable to full retraining while requiring only a fraction of the computational time and relying solely on sparse observations of the full system. The architecture employs an encode-process-decode structure: a Variational Autoencoder (VAE) to perform dimensionality reduction, and a transformer network to evolve the latent states and model the dynamics. The ROM is parameterized by an external control variable, the Reynolds number in the Navier-Stokes setting, with the transformer exploiting attention mechanisms to capture both temporal dependencies and parameter effects. The probabilistic VAE enables stochastic sampling of trajectory ensembles, providing predictive means and uncertainty quantification through the first two moments. After initial training on a limited set of dynamical regimes, the model is adapted to out-of-sample parameter regions using only sparse data. Its probabilistic formulation naturally supports ensemble generation, which we employ within an ensemble Kalman filtering framework to assimilate data and reconstruct full-state trajectories from minimal observations. We further show that, for the dynamical system considered, the dominant source of error in out-of-sample forecasts stems from distortions of the latent manifold rather than changes in the latent dynamics. Consequently, retraining can be limited to the autoencoder, allowing for a lightweight, computationally efficient adaptation procedure with very sparse fine-tuning data.
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All authors Ismaël Zighed, Andrea Nóvoa, Luca Magri, Taraneh Sayadi

Accelerator Physics

The transient behavior of superconducting multi-cell accelerating cavities

Volker Ziemann

We employ an equivalent-circuit model of a multi-cell cavity to explore its time-dependent behavior in order to understand differences between the multi-cell model and the commonly-used model of a single-cell resonator. Furthermore, we address tolerances that arise from manufacturing imperfections.
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Fluid Dynamics

An abundance of periodic orbits in two-dimensional turbulence revealed by a diffusion-based generative model

Jeremy P Parker and Tobias M Schneider

Unstable periodic orbits offer a route to reconstructing the statistical properties of chaotic systems, including turbulence. Short periodic orbits are particularly important in periodic-orbit expansions, yet their abundance and diversity remain largely unexplored even in the extensively studied two-dimensional Kolmogorov flow. We search for short relative periodic orbits in this flow at $Re=40$, considering all distinct classes of recurrence symmetry. We train a generative diffusion model on nonperiodic vorticity sequences from a direct numerical simulation of turbulence, producing time series that resemble physically plausible trajectories. The model incorporates symmetry properties of the system but is otherwise trained solely on these data, without enforcing the governing equations. After training, we modify its architecture to generate synthetic trajectories that are periodic up to spatial symmetry transformations, without retraining its weights. These synthetic trajectories are then refined into exact solutions using an iterative solver, yielding 111 new relative periodic orbits with periods $T < 3$, including 40 with $T<2$. Rather than revealing a hierarchy dominated by a small number of short cycles, this abundance suggests that quantitatively converged periodic-orbit descriptions of spatiotemporal chaos may require substantially larger orbit libraries than anticipated.
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Optics

Versatile CMOS modulation-free self-isolating stabilized precision lasers on a chip

David A. S. Heim, Kaikai Liu, Rahul Chawlani et al. (+2 more)

Ultra-low-noise stabilized lasers are a fundamental tool for precision quantum technologies, optical clocks, microwave and millimeter-wave generation, and fiber sensing. Existing systems rely on table-top bulk-optic components – discrete lasers, reference cavities, isolators, modulators and frequency shifters – limiting portability, scalability, and manufacturability. While these systems offer flexibility in laser design to tailor linewidth, frequency noise, and wavelength to specific applications, fully integrating a stabilized laser onto a chip without sacrificing performance and versatility has remained elusive. Here, we report integration of the precision stabilized laser in the low-loss silicon nitride photonic platform, combining a flexible isolator-free core laser design with a modulation-free stabilization cavity. We demonstrate a stabilized widely tunable self-isolating extended cavity tunable laser monolithically integrated with an on-chip coil-loaded Mach-Zehnder interferometer (CL-MZI). This design yields a fundamental linewidth of 1.7 - 10.5 Hz across a 60 nm tuning range, integral linewidth of 299 - 505 Hz over a 30 nm tuning range, frequency noise reduction of over 5 orders of magnitude, and an Allan-Deviation (ADEV) of 6.5x10-13 at 0.08 ms. We next highlight the versatility of this approach by demonstrating a self-isolating stimulated Brillouin scattering (SBS) laser, that provides nonlinear noise suppression of high frequency noise by multiple orders of magnitude, stabilized to an on-chip CL-MZI. The stabilized SBS laser achieves 4 Hz fundamental linewidth, 74 Hz integral linewidth, and ADEV of 2.8x10-13 at 5 ms. These results bring the performance and versatility of table-top stabilized laser systems to a chip for the first time, providing a path to scalable, low-cost, and manufacturable precision lasers for portable quantum, sensing, and communications applications.
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All authors David A. S. Heim, Kaikai Liu, Rahul Chawlani, Karl. D. Nelson, Daniel J. Blumenthal

Fluid Dynamics

On the spatial structure and intermittency of soot in a lab-scale gas turbine combustor: Insights from large-eddy simulations

Leonardo Pachano, Daniel Mira, Abhijit Kalbhor et al. (+1 more)

This work presents a numerical investigation of soot formation in the Cambridge lab-scale gas turbine combustor. Large-eddy simulations (LES) of a swirl-stabilized ethylene flame are performed using the flamelet generated manifold method coupled with a discrete sectional model to account for soot formation, growth, and oxidation. The study aims to elucidate the mechanism governing the spatial structure and intermittency of soot, supported by comparisons with experimental data. The predicted soot distribution agrees well with measurements, with peak concentrations near the bluff body. Flow recirculation is identified as the key mechanism driving soot accumulation in fuel-rich regions, where surface reactions dominate soot mass growth. Soot intermittency arises from fluctuations in the flow field driven by interactions between the flame front and the recirculation vortex. Two soot modeling approaches are evaluated, differing in their treatment of soot model quantities: the first approach employs on-the-fly computation of source terms (FGM-C), while the second uses fully pre-tabulated source terms (FGM-T). Their predictive performance and computational cost are compared in the context of unsteady, sooting flames in swirl-stabilized combustors.
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All authors Leonardo Pachano, Daniel Mira, Abhijit Kalbhor, Jeroen van Oijen

Fluid Dynamics · Cross-listed from cond-mat.soft

Rheological properties and shear-induced structures of ferroelectric nematic liquid crystals

Ashish Chandra Das, Sathyanarayana Paladugu and Oleg D. Lavrentovich

Recently discovered ferroelectric nematic (NF) liquid crystals are fluids with a polar orientational order. The electric polarization vector can be aligned by an electric field and by surface anchoring. Here, we explore how the polarization field and effective viscosity of the NF materials are affected by shear flows. We explore three NF materials, abbreviated RM734, DIO, and a room-temperature FNLC919, all of which exhibit a paraelectric nematic (N) and the NF phase. All materials show an increase of the viscosity upon cooling, with an Arrhenius behavior. In DIO and FNLC919, the antiferroelectric SmZA phase shows a strong dependence of the effective viscosity on the shear rate: this viscosity is lower than the viscosity of the N and NF phases at high shear rates but is much higher when the shear rate is low. The behavior is associated with the layered structure of the SmZA phase. All mesophases exhibit shear-thinning behavior at low shear rates and a nearly Newtonian behavior at higher shear rates. In terms of alignment, we observe three regimes in the N and NF phases: flow-alignment at low shear rates, log-rolling regime with the director and polarization along the vorticity axis at high shear rates, and polydomain structures at intermediate rates. In the flow-aligning regime, the NF polarization does not tilt away from the shear direction, which is in sharp contrast to the flow-induced tilt of the N director. The effect is attributed to the avoidance of splay deformations and associated space charge in the flowing NF. The temperature and shear rate dependencies of the viscosity and the uncovered shear-induced structural effects of NF advance our understanding of these materials and potentially facilitate their applications.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG

Partial recovery of meter-scale surface weather

Jonathan Giezendanner, Qidong Yang, Ruizhe Huang et al. (+7 more)

Near-surface weather varies over tens to hundreds of meters, yet remains unresolved in analyses and forecasts. We test whether this variation can be inferred without resolving atmospheric dynamics. Combining sparse weather stations, high-resolution Earth observation, and coarse atmospheric dynamics, we infer temperature, dewpoint, and wind at 30-m resolution across the contiguous United States. Against measurements held out in space and time, estimates reduce error by 11-28% relative to the strongest baseline. Within held-out $0.25^\circ$ grid cells, we recover more spatial variance than baselines, explaining nearly half of temperature variability in the median cell. The method captures time-varying differences between locations and produces coherent patterns associated with topography and land cover. Beyond weather, our findings illustrate how sparse observations of a dynamical system can be combined with dense observations of persistent environmental structure to recover otherwise unresolved spatial variability.
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All authors Jonathan Giezendanner, Qidong Yang, Ruizhe Huang, Eric Schmitt, Anirban Chandra, Yawen Zhang, Jeremy Vila, Detlef Hohl, Campbell Watson, Sherrie Wang

Instrumentation and Detectors

Charge collection parameterization of MALTA2, a depleted monolithic active pixel sensor

L. Fasselt, P. Behera, D. V. Berlea et al. (+22 more)

A fast simulation method is presented for a depleted monolithic active pixel sensor, which uses a data driven parameterization of the charge collection and propagation. This approach provides an efficient alternative to TCAD simulations, particularly for sensors whose proprietary process details - such as doping profiles or implant geometries - are unavailable. Data was obtained with a MALTA2 sensor fabricated in a 180 nm CMOS imaging technology on 30 {\mu}m epitaxial silicon using the MALTA beam telescope at CERN SPS. The model reproduces the measured inpixel efficiency with high accuracy and enables a realistic yet computationally lightweight analog pixel simulation. This method will be further employed in optimizing the digital sensor design for applications in high-rate particle tracking and high-granularity calorimetry.
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All authors L. Fasselt, P. Behera, D. V. Berlea, D. Bortoletto, C. Buttar, T. Chembakan, V. Dao, G. Dash, S. Haberl, T. Inada, F.K. Isik, P. Jana, X. Li, L. Li, H. Pernegger, P. Riedler, W. Snoeys, C. A. Solans Sánchez, A. Swoboda, I. Turk Cakir, M. van Rijnbach, M. Vázquez Núñez, A. Vijay, J. Weick, S. Worm

Fluid Dynamics · Cross-listed from math.AP

Viscous vortex crystals

Michele Dolce and Martin Donati

We study the solution to the two-dimensional incompressible Navier-Stokes equations arising from a sum of Dirac masses in a particular co-rotating configuration. This configuration consists of a polygonal vortex crystal with or without a central vortex. By exploiting the symmetries and stability properties of the system, we describe and control the solution up to sub-diffusive time scales, prior to the expected onset of vortex merging.
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Data Analysis and Statistics

Titanic overconfidence – dark uncertainty can sink hybrid metrology for semiconductor manufacturing

Ronald G. Dixson, Adam L. Pintar, R. Joseph. Kline et al. (+4 more)

Hybrid metrology for semiconductor manufacturing is on a collision course with dark uncertainty. An IEEE technology roadmap for this venture has targeted a linewidth uncertainty of +/- 0.17 nm at 95 % coverage and advised the hybridization of results from different measurement methods to hit this target. Related studies have applied statistical models that require consistent results to compel a lower uncertainty, whereas inconsistent results are prevalent. We illuminate this lurking issue, studying how standard methods of uncertainty evaluation fail to account for the causes and effects of dark uncertainty. We revisit a comparison of imaging and scattering methods to measure linewidths of approximately 13 nm, applying contrasting statistical models to highlight the potential effect of dark uncertainty on hybrid metrology. A random effects model allows the combination of inconsistent results, accounting for dark uncertainty and estimating a total uncertainty of +/- 0.8 nm at 95 % coverage. In contrast, a common mean model requires consistent results for combination, ignoring dark uncertainty and underestimating the total uncertainty by as much as a factor of five. To avoid such titanic overconfidence, which can sink a venture, we outline good practices to reduce dark uncertainty and guide the combination of indeterminately consistent results.
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All authors Ronald G. Dixson, Adam L. Pintar, R. Joseph. Kline, Thomas A. Germer, J. Alexander Liddle, John S. Villarrubia, Samuel M. Stavis

Atomic Physics · Cross-listed from cond-mat.quant-gas

A Maxwell Fish-Eye Lens in a Bose-Einstein Condensate

Jelte Duchêne, Elinor Kath, Floriane Arrouas et al. (+7 more)

We experimentally realize an analogue of the optical Maxwell fish-eye lens (MFEL) using phononic excitations in a Bose-Einstein condensate (BEC). A MFEL is characterized by a radially symmetric, spatially varying refractive index with the remarkable property that rays emitted from any point within the lens are perfectly focused at their antipodal points. While the implementation of such gradient-index lenses is challenging in conventional optical systems, BECs offer a highly tunable platform in which the spatially varying speed of sound of collective excitations – phonons, the acoustic analogues of photons – can be engineered and their dynamics observed in real time. Time-resolved measurements of phonon wavefronts reveal focusing behavior that shows good agreement with analytical theory and numerical simulations. This work provides both a geometric and physical framework for engineering effective refractive indices using ultracold atoms, and simulating wave propagation on effective spherical geometries.
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All authors Jelte Duchêne, Elinor Kath, Floriane Arrouas, Hanyi Jang, Helmut Strobel, Markus K. Oberthaler, Jay Mehta, Liam M. Farrell, Wyatt Kirkby, Duncan H.J. O'Dell

Optics

HELIOS: A surface integral equation software for light scattering in homogeneous, periodic, and stratified environments

Parmenion S. Mavrikakis and Olivier J. F. Martin

We present HELIOS (HomogEneous and Layered medIa Optical Scattering), an open-source surface integral equation (SIE) software designed for modeling light scattering by particles embedded in homogeneous or layered media and periodic backgrounds. The code implements the Poggio-Miller-Chang-Harrington-Wu-Tsai (PMCHWT) formulation that has demonstrated exceptional reliability in solving scattering problems with penetrable objects. Domain boundaries are discretized using triangular meshes, upon which the electric and magnetic surface current densities are expanded using the Rao-Wilton-Glisson (RWG) basis functions. For periodic structures, such as photonic crystals and metasurfaces, HELIOS employs Ewald's transformation to efficiently evaluate the infinite series associated with 2D lattices. Regarding stratified media, the code utilizes a matrix-friendly approach for the layered media Green's tensor, computing Sommerfeld integrals and accelerating calculations through a tabulation-interpolation scheme. The source code is implemented in C++, while a Python interface manages the workflow, including simulation setup, solver run, and post-processing. The accuracy and versatility of HELIOS are demonstrated through various examples that cover all its functionalities.
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Physics and Society · Cross-listed from cs.AI

Three AI-agents walk into a bar . . . . `Lord of the Flies' tribalism emerges among smart AI-Agents

Dhwanil M. Mori and Neil F. Johnson

Near-future infrastructure systems may be controlled by autonomous AI agents that repeatedly request access to limited resources such as energy, bandwidth, or computing power. We study a simplified version of this setting using a framework where N AI-agents independently decide at each round whether to request one unit from a system with fixed capacity C. An AI version of "Lord of the Flies" arises in which controlling tribes emerge with their own collective character and identity. The LLM agents do not reduce overload or improve resource use, and often perform worse than if they were flipping coins to make decisions. Three main tribal types emerge: Aggressive (27.3%), Conservative (24.7%), and Opportunistic (48.1%). The more capable AI-agents actually increase the rate of systemic failure. Overall, our findings show that smarter AI-agents can behave dumber as a result of forming tribes.
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Optics · Cross-listed from cond-mat.mtrl-sci

Highly Efficient Second/Third Harmonic Generation in van der Waals Layered Material AgScP2S6 with Anisotropic Polarization and Temperature Dependence

Mohamed Yaseen Noor, Ryan Siebenaller, Wenhao Liu et al. (+12 more)

Single-crystal X-ray diffraction and nonlinear optical measurements, especially second- and third-harmonic generation (SHG/THG) are comprehensively investigated for the van der Waals layered material AgScP2S6 with a non-centrosymmetric P31c (159) space group. Linear optical constants are extracted using spectroscopic ellipsometry and applied in fitting the harmonic generation behavior. Polarization-resolved SHG and THG measurements exhibit pronounced anisotropy, with emission patterns well-described by theoretical models derived from the khi(2) and khi(3) tensor elements. The material demonstrates exceptionally high nonlinear susceptibilities, with khi(2) ~ 10^(-8) m/V and khi(3) ~ 10^(-17) m^2/V^2 which is a few orders of magnitude greater than comparable 2D materials reported in the literature. Temperature-dependent SHG and THG measurements from 300 K to 25 K reveal exponential decay in harmonic signal intensities, attributed to reduced carrier mobility, with no evidence of structural phase transitions, consistent with results from single crystal diffraction and heat capacity measurements. Polarization-resolved SHG and THG measurements also reveal distinct orientation and ellipticity trends, highlighting the anisotropic nonlinear tensor contributions and contrasting polarization selection rules in the material. These results establish AgScP2S6 as a high-performance, thermally stable, and highly anisotropic nonlinear candidate material suitable for compact photonic applications such as ultrafast optical modulators, polarization-sensitive detectors, and wavelength-tunable light sources.
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All authors Mohamed Yaseen Noor, Ryan Siebenaller, Wenhao Liu, Zixin Zhai, Conrad Kuz, Simin Zhang, Mousumi Upadhyay Kahaly, Gergely Nagy, Aamir Mushtaq, Rahul Rao, Emmanuel Rowe, Benjamin S. Conner, Bing Lv, Michael A. Susner, Enam Chowdhury

Plasma Physics

Merging of zonal flows in gyrofluid resistive drift-wave turbulence

Fabian Grander, Tobias Gröfler, Franz Ferdinand Locker et al. (+2 more)

Non-linear dynamics of zonal flows is investigated in the context of the gyrofluid modified Hasegawa-Wakatani model. Merging of zonal flows and the chaotic developement of the initial zonal flow pattern is explored. Conservation equations for zonal flow momentum and energy with consistent finite Larmor radius (FLR) effects are derived and used for a quantitative analysis of zonal flow mergers in numerical simulations. The nonlinear local Reynolds stress transfer as opposed to (hyper)viscous dissipation is found to be the main cause of merging. The applicability of the concept of a phase transition in the strict thermodynamical sense is discussed in context of zonal flow transition hysteresis.
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All authors Fabian Grander, Tobias Gröfler, Franz Ferdinand Locker, Manuel Rinner, Alexander Kendl

Optics

Hard X-Ray Zernike-Type Phase-Contrast Imaging with a Two-Block Crystal System

Levon Haroutunyan

A novel scheme for Zernike-type hard X-ray phase-contrast imaging is proposed. The scheme relies on X-ray dynamical diffraction in a two-block crystal system with parallel crystal plates of equal thickness. A phase shifter providing a $\pi/2$ phase shift is placed in the inter-block gap of the crystal system. The method operates in a scanning geometry. The proposed imaging setup is compact and does not require conventional focusing optics. Numerical simulations of phase-contrast image formation are performed.
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Space Physics

Investigating potential benefits of future sub-L1 missions with STEREO-A

Eva Weiler, Emma E. Davies, Christian Möstl et al. (+4 more)

We present the first statistical study of geomagnetic storm forecasting using in situ data from the STEREO-A spacecraft as a sub-L1 monitor. Between November 2022 and June 2024, STEREO-A crossed the Sun-Earth line, covering longitudinal and radial separations of +/-15{\deg} from the Sun-Earth line and 0.01-0.06 au from Earth. This passage provides a unique opportunity to assess future sub-L1 mission concepts by ESA, such as HENON and SHIELD. We identify 32 coronal mass ejections (CMEs) observed by both STEREO-A and L1 spacecraft. Eight of these 32 CME events are first detected at L1, indicating that radial spacecraft separations of up to ~0.05 au do not always yield lead time advantages. Furthermore, we find greater (smaller) gains in lead time when STEREO-A is east (west) of the Sun-Earth line. We develop a baseline methodology for the use of future sub-L1 in situ data to enable time-shifting and real-time modeling of the geomagnetic SYM-H index. This is run continuously over the entire time period, therefore modeling the geomagnetic response of all solar wind structures. Our methodology is empirically motivated and should be considered a first approach in addressing the use of sub-L1 data. Following this methodology, 26 of 47 observed geomagnetic storms are correctly identified from STEREO-A data. Intense events (82%, SYM-H<-100 nT) are well detected, most of which are also associated with an identified CME event. Most SYM-H minima are predicted later (72%) and stronger (58%) than those observed due to biases introduced by our methodology.
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All authors Eva Weiler, Emma E. Davies, Christian Möstl, Noé Lugaz, Astrid Veronig, Rachel Bailey, Martin Reiss

Instrumentation and Detectors · Cross-listed from astro-ph.IM

Demonstrating Single Photon Counting with Kinetic Inductance Detectors from 3.8 to 25 $\mu$m

Wilbert G. Ras-Vinke, Kevin Kouwenhoven, Jochem J.A. Baselmans et al. (+4 more)

One of the primary objectives of modern astronomy is the atmospheric characterization of Earth-like exoplanets at visible and infrared wavelengths. Achieving this goal requires extremely sensitive detectors capable of measuring faint signal of the exoplanet at the single-photon level while maintaining near-zero dark count rates. In the infrared, however, conventional semiconducting detector technologies struggle to meet these stringent requirements. In this work we demonstrate single-photon counting with superconducting Microwave Kinetic Inductance Detectors at the wavelengths 3.8, 8.5, 18.5, and 25 $\mu$m and measure resolving powers ($E/\delta E$) of 9.9, 5.9, 3.2, and 3.3, respectively, with corresponding dark count rates of 4, 8, 34, and 48 mHz. Our membrane-based devices reach phonon-loss limited performance at 3.8 $\mu$m, more than doubling the performance attainable with comparable solid-substrate devices. These results showcase the detector technology in the mid-infrared and the intricate measurement setup required for these sensitive detectors. We discuss how the detector design and measurement setup can be further optimized to increase the detector performance in the mid-infrared.
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All authors Wilbert G. Ras-Vinke, Kevin Kouwenhoven, Jochem J.A. Baselmans, Kenichi Karatsu, David J. Thoen, Vignesh Murugesan, Pieter J. de Visser

Computational Physics

Discovery of Interpretable Physical Laws in Materials via Language-Model-Guided Symbolic Regression

Yifeng Guan, Chuyi Liu, Dongzhan Zhou et al. (+4 more)

Discovering interpretable physical laws from high-dimensional data is a fundamental challenge in scientific research. Traditional methods, such as symbolic regression, often produce complex, unphysical formulas when searching a vast space of possible forms. We introduce a framework that guides the search process by leveraging the embedded scientific knowledge of large language models, enabling efficient identification of physical laws in the data. We validate our approach by modeling key properties of perovskite materials. Our method mitigates the combinatorial explosion commonly encountered in traditional symbolic regression, reducing the effective search space by a factor of approximately $10^5$. A set of novel formulas for bulk modulus, band gap, and oxygen evolution reaction activity are identified, which not only provide meaningful physical insights but also outperform previous formulas in accuracy and simplicity.
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All authors Yifeng Guan, Chuyi Liu, Dongzhan Zhou, Lei Bai, Wan-jian Yin, Jingyuan Li, Mao Su

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

Growth-controlled photochromism in yttrium oxyhydride thin films deposited by HiPIMS and pulsed-DC magnetron sputtering

M. Zubkins, E. Letko, E. Strods et al. (+6 more)

The present study investigates photochromic oxygen-containing yttrium hydride (YHO) thin films deposited by reactive high power impulse magnetron sputtering (HiPIMS) and compares their photochromic, optical, and structural properties with those of films synthesized by reactive pulsed direct current magnetron sputtering (pulsed-DCMS). Optical emission spectroscopy reveals that, unlike pulsed-DCMS where Ar$^{+}$ ions dominate, HiPIMS discharges are characterised by strong Y$^{+}$ emission, evidencing high yttrium ionisation and substantial self-sputter recycling. The critical working pressure (P$_c$) required to obtain transparent and photochromic films is higher for HiPIMS (Pc $\approx$ 1.0 Pa) than for pulsed-DCMS (Pc $\approx$ 0.5 Pa). Although films deposited near Pc exhibit similar solar transmittance (~72 %) and lattice parameters (5.38–5.39 Å), the pulsed-DCMS film shows a substantially higher relative photochromic contrast (34 %) and a lower optical band gap (2.70 eV) compared with the HiPIMS film (9 % contrast and 2.94 eV). This difference is partly attributed to a lower oxygen-to-hydrogen atomic ratio in the pulsed-DCMS film. Structurally, HiPIMS films are largely polycrystalline with random out-of-plane crystallographic orientation, whereas pulsed-DCMS films exhibit a pronounced <100> out-of-plane preferred orientation. These results demonstrate that, beyond composition, thin-film growth conditions and microstructure play a crucial role in governing the photochromic performance of YHO.
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All authors M. Zubkins, E. Letko, E. Strods, V. Vibornijs, D. Moldarev, K. Sarakinos, K. Mizohata, K. Kundzins, J. Purans

Chemical Physics

Benchmarking short-range machine learning potentials for atomistic simulations of metal/electrolyte interfaces

Lucas B. T. de Kam, Jia-Xin Zhu, Ankit Mathanker et al. (+2 more)

Atomistic simulations of electrochemical interfaces remain challenging due to the long time scales required to adequately sample the structure of the electric double layer. The emergence of efficient, short-range machine learning interatomic potentials (MLIPs) offers a promising alternative to computationally expensive density functional theory-based molecular dynamics (DFT-MD) simulations in this regard. However, in standard periodic DFT calculations of metal surfaces, the surface charge is implicitly set by the number of counterions in the simulation cell, making it a global property that is difficult to represent with strictly local MLIPs. Here, we benchmark common MLIP architectures (DP, ACE, MACE) for charged Au/water interfaces containing solvated sodium ions. We find that MLIPs trained on datasets spanning multiple surface charge states yield inconsistent predictions of interfacial water orientation and ion distributions, although message-passing models with a larger receptive field exhibit greater robustness to training on mixed-charge datasets. In contrast, models trained on a single charge state produce consistent equilibrium interfacial properties. Finally, we assess the performance of the eSEN model trained on the recently released Open Catalyst 2025 dataset, which includes solid/liquid interfaces that span a wide range of surface charge densities. Overall, our results characterize the limitations of short-range MLIPs for simulations of electrochemical interfaces and provide practical guidance for constructing training datasets for simulations of charged metal/electrolyte interfaces.
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All authors Lucas B. T. de Kam, Jia-Xin Zhu, Ankit Mathanker, Katharina Doblhoff-Dier, Nitish Govindarajan