Peer Revenue Equity in science

Papers

Fresh from arXiv, typeset properly. Highlighted words trade on the market.

Physics Physics

physics Watch Physics

Wednesday 25 March

Biological Physics · Cross-listed from nlin.PS

Self-organized pattern synchronization modulated by stochasticity in coupled plankton ecosystems

Ju Kang, Yiyuan Niu, Yuanzhi Li et al. (+2 more)

Spatial patterning and synchronization are pervasive features of plankton communities, yet the mechanisms that allow such patterns to persist coherently under environmental noise remain unresolved. In vertically structured aquatic ecosystems, plankton populations are often organized into distinct layers, raising the question of how interactions between layers shape both spatial self-organization and robustness. Here, we develop a spatiotemporal ecosystem model of a two-layer plankton community to examine the role of passive diffusive coupling under stochastic environmental fluctuations. We show that interlayer diffusion induces a sharp transition from independent, layer-specific Turing patterns to fully synchronized spatial patterns once the coupling strength exceeds a critical threshold. Importantly, the same coupling mechanism markedly enhances the stability of spatial patterns against environmental noise, extending their persistence far beyond that of non-coupled layers. Moreover, we uncover a trophic hierarchy in noise sensitivity, with zooplankton exhibiting substantially greater vulnerability than phytoplankton. Together, these results identify passive diffusive coupling as a unifying mechanism that simultaneously promotes spatial synchronization and robustness, providing a mechanistic explanation for the persistence of coherent plankton patterns in fluctuating aquatic environments.
Read the full abstract

All authors Ju Kang, Yiyuan Niu, Yuanzhi Li, Quan-Xing Liu, Chengjin Chu

Geophysics · Cross-listed from cs.LG

Transcending Classical Neural Network Boundaries: A Quantum-Classical Synergistic Paradigm for Seismic Data Processing

Zhengyi Yuan, Xintong Dong, Xinyang Wang et al. (+2 more)

In recent years, a number of neural-network (NN) methods have exhibited good performance in seismic data processing, such as denoising, interpolation, and frequency-band extension. However, these methods rely on stacked perceptrons and standard activation functions, which imposes a bottleneck on the representational capacity of deep-learning models, making it difficult to capture the complex and non-stationary dynamics of seismic wavefields. Different from the classical perceptron-stacked NNs which are fundamentally confined to real-valued Euclidean spaces, the quantum NNs leverage the exponential state space of quantum mechanics to map the features into high-dimensional Hilbert spaces, transcending the representational boundary of classical NNs. Based on this insight, we propose a quantum-classical synergistic generative adversarial network (QC-GAN) for seismic data processing, serving as the first application of quantum NNs in seismic exploration. In QC-GAN, a quantum pathway is used to exploit the high-order feature correlations, while the convolutional pathway specializes in extracting the waveform structures of seismic wavefields. Furthermore, we design a QC feature complementarity loss to enforce the feature orthogonality in the proposed QC-GAN. This novel loss function can ensure that the two pathways encode non-overlapping information to enrich the capacity of feature representation. On the whole, by synergistically integrating the quantum and convolutional pathways, the proposed QC-GAN breaks the representational bottleneck inherent in classical GAN. Experimental results on denoising and interpolation tasks demonstrate that QC-GAN preserves wavefield continuity and amplitude-phase information under complex noise conditions.
Read the full abstract

All authors Zhengyi Yuan, Xintong Dong, Xinyang Wang, Zheng Cong, Shiqi Dong

Optics

Machine vision with small numbers of detected photons per inference

Shi-Yuan Ma, Jérémie Laydevant, Mandar M. Sohoni et al. (+3 more)

Machine vision, including object recognition and image reconstruction, is a central technology in many consumer devices and scientific instruments. The design of machine-vision systems has been revolutionized by the adoption of end-to-end optimization, in which the optical front end and the post-processing back end are jointly optimized. However, while machine vision currently works extremely well in moderate-light or bright-light situations – where a camera may detect thousands of photons per pixel and billions of photons per frame – it is far more challenging in very low-light situations. We introduce photon-aware neuromorphic sensing (PANS), an approach for end-to-end optimization in highly photon-starved scenarios. The training incorporates knowledge of the low photon budget and the stochastic nature of light detection when the average number of photons per pixel is near or less than 1. We report a proof-of-principle experimental demonstration in which we performed low-light image classification using PANS, achieving 73% (82%) accuracy on FashionMNIST with an average of only 4.9 (17) detected photons in total per inference, and 86% (97%) on MNIST with 8.6 (29) detected photons – orders of magnitude more photon-efficient than conventional approaches. We also report simulation studies showing how PANS could be applied to other classification, event-detection, and image-reconstruction tasks. By taking into account the statistics of measurement results for non-classical states or alternative sensing hardware, PANS could in principle be adapted to enable high-accuracy results in quantum and other photon-starved setups.
Read the full abstract

All authors Shi-Yuan Ma, Jérémie Laydevant, Mandar M. Sohoni, Logan G. Wright, Tianyu Wang, Peter L. McMahon

Medical Physics · Cross-listed from math.OC

Accelerating Low-Frequency Convergence for Limited-Angle DBT via Two-Channel Fidelity in PDHG

Taro Iyadomi, Ricardo Parada, Anna Kim et al. (+3 more)

Reconstruction in limited-angle digital breast tomosynthesis (DBT) suffers from slow convergence of low spatial-frequency components when using weighted data-fidelity terms within primal-dual optimization. We introduce a two-channel fidelity strategy that decomposes the sinogram residual into complementary low-pass and high-pass bands using square-root Hanning (Hann^{1/2}) filter families, each driven by an independent \ell_2-ball constraint and dual update in the PDHG (Chambolle-Pock) algorithm with He-Yuan predictor-corrector relaxation. By assigning a larger dual step size and slightly looser tolerance to the low-frequency channel, the method delivers stronger per-iteration correction to the near-DC band without violating global PDHG stability. Experiments on a 2D digital breast phantom across multiple resolutions demonstrate that the two-channel approach yields 19%–61% RMSE improvement over the single-channel baseline, with larger gains at coarser discretizations where problem conditioning is more favorable, supporting more balanced spectral convergence in clinically realistic limited-angle regimes.
Read the full abstract

All authors Taro Iyadomi, Ricardo Parada, Anna Kim, Lily Jiang, Emil Sidky, William Chang

Optics

Ultrawide Bandwidth Optomechanical Magnetometry Using Flux Concentration

Benjamin J. Carey, Nathaniel Bawden, Fernando Gottardo et al. (+4 more)

Low-frequency magnetic fields carry vital information for neuroscience, navigation, and Earth science. However, they are generally weak, making it challenging to measure them with compact, room-temperature magnetometers. To overcome this challenge, we combine an on-chip optomechanical magnetometer with a high-permeability flux concentrator. Beyond boosting sensitivity and bandwidth, exploiting the concentrator's nonlinear response converts low-frequency magnetic fluctuations into higher-frequency signals where the sensor is intrinsically most responsive. This sidesteps the technical noise that has long constrained the application of optomechanical magnetometry at low frequencies. Our measurements show order-of-magnitude improvements in sensitivity and extend performance into the sub-hertz regime, achieving below 20 nT Hz$^{-1/2}$ down to 3 Hz and less than 100 nT Hz$^{-1/2}$ at 0.1 Hz. Because this approach requires no redesign of the underlying architecture, it can be readily applied across magnetometer technologies, opening the way to practical low-frequency sensing for applications from brain activity mapping to undersea navigation and biomedical diagnostics.
Read the full abstract

All authors Benjamin J. Carey, Nathaniel Bawden, Fernando Gottardo, James S. Bennett, Douglas Bulla, Scott Foster, Warwick P. Bowen

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

A generalized method for estimating solar wind speeds and densities using spectral broadening for a Kolmogorov turbulence spectrum

Keshav Aggarwal, R. K. Choudhary, Abhirup Datta et al. (+3 more)

We present a unified method to derive both solar wind velocities and coronal electron densities in the near-Sun corona using Doppler spectral broadening of spacecraft radio signals. The method is generalized to be frequency independent under the assumption that electron density fluctuations follow a Kolmogorov spectrum. We validate the approach using S-band data from India's Mars Orbiter Mission during the October 2021 superior conjunction at 5-8 R$_\odot$, and X-band data from Japan's Akatsuki during June 2016 and October 2022 conjunctions spanning 1.4-10 R$_\odot$. From S-band we obtained wind speeds of 100-150 km s$^{-1}$ and electron densities of order $10^{10}$ m$^{-3}$. X-band results show speeds ranging from $\sim$150 km s$^{-1}$ near the equator to $\sim$400 km s$^{-1}$ in coronal-hole regions, with consistent radial trends in density. We provide a compact, frequency-scaled relation that maps Doppler spectral width to both $v$ and $N_e$. The formulation enables consistent application across telecommunication bands and complements in-situ probes for coronal plasma studies.
Read the full abstract

All authors Keshav Aggarwal, R. K. Choudhary, Abhirup Datta, Roopa M.V., Takeshi Imamura, Hiroki Ando

Optics

Inverse-Designed Metasurfaces for Compact Optical Skyrmion Generation with High Topological Fidelity

Donghyun Park, Alex Song, Haejun Chung et al. (+1 more)

Optical skyrmions are structured vector fields with nontrivial polarization topology and subwavelength-scale features. One common approach to generating optical skyrmions is the superposition of a zeroth-order Bessel beam and a higher-order Bessel beam carrying orbital angular momentum, with each beam possessing an orthogonal circular polarization state. However, creating such complex beams typically requires bulky free-space optical setups; therefore, recent efforts have focused on compact optical skyrmion generators based on metasurfaces. Nevertheless, achieving the degrees of freedom required for simultaneous phase and polarization control remains challenging because of the limited design flexibility of conventional meta-atoms. Here, we address this challenge by employing an inverse-design approach and demonstrate a single-layer metasurface that generates high-fidelity optical skyrmions. We employ an adjoint-based topology-optimization method to design a silicon metasurface that converts an incident beam into an optical skyrmion without the need for additional optical components. The optimized metasurface generates an optical skyrmion with skyrmion number $(N_\mathrm{sk}) = 0.970$. This work demonstrates that inverse design can be a promising route to compact skyrmion generators, and our approach provides a basis for near-field particle manipulation and the generation of independent topological bits in dense photonic integration.
Read the full abstract

All authors Donghyun Park, Alex Song, Haejun Chung, Sejeong Kim

Fluid Dynamics

High-Reynolds-number turbulent boundary layers under adverse pressure gradients. Part 2. A composite mean velocity profile

Ahmad Zarei, Mitchell Lozier, Rahul Deshpande et al. (+1 more)

A robust composite mean velocity profile is developed for turbulent boundary layers (TBLs) subjected to adverse pressure gradients (APGs), extending the composite formulation for generic pressure-gradient TBLs proposed by \citeauthor{nickels} (J.\ Fluid Mech., vol.\ 521, 2004). Several modifications are introduced to capture key features of APG flows. A new parameter accounts for pressure-gradient history effects in the wake region, a velocity-overshoot function is incorporated in the inner region, and the wake function is reformulated using an independent, physically motivated definition of boundary-layer thickness. A compilation of APG TBL datasets from the literature, including the new dataset presented in Part~1, is used to assess and refine the formulation. The resulting composite profile contains three physically meaningful parameters that capture pressure-gradient effects on the mean velocity profile, determined through nonlinear curve fitting. These parameters provide a framework for identifying `well-behaved' APG TBLs and quantifying the strength of pressure-gradient history effects. The profile also enables reliable estimation of the friction velocity and boundary-layer thickness in well-behaved APG TBLs, providing a practical tool for scaling analyses when these quantities are not directly measurable. Its analytical form yields improved estimates of mean velocity gradients, facilitating evaluation of the indicator function and identification of inflection points. Finally, the formulation predicts both the coefficients and spatial extent of the logarithmic region of the mean streamwise velocity profile, enabling assessment of its universality in high-Reynolds-number APG TBLs. This shows that the von K'arm'an coefficient approaches an invariant value of $\kappa \approx 0.39$ at sufficiently high Reynolds numbers, independent of pressure-gradient effects.
Read the full abstract

All authors Ahmad Zarei, Mitchell Lozier, Rahul Deshpande, Ivan Marusic

Chemical Physics

Spectral convergence of sum-of-Gaussians tensor neural networks for many-electron Schrödinger equation

Teng Wu, Qi Zhou, Huangjie Zheng et al. (+2 more)

We present an improved version of the sum-of-Gaussians tensor neural network (SOG-TNN) architecture for solving many-electron Schrödinger equation for one-dimensional soft-Coulomb systems. Model reduction techniques are introduced to reduce the number of tensor-factorized bases under the SOG approximation of the kernel. The Slater determinant ansatz is employed so that the anti-symmetric property of the wave function can be strictly preserved. Numerical results show that the SOG-TNN achieves high accuracy with remarkably small basis sizes. Robust spectral convergence with respect to the basis size is also observed, consistently characterized by a mixed algebraic-exponential model for the error decay. These findings validate that the SOG-TNN architecture provides an ultra-efficient and low-rank representation of complex multi-electron wave functions, shedding light on high-fidelity quantum calculations in larger-scale many-electron systems.
Read the full abstract

All authors Teng Wu, Qi Zhou, Huangjie Zheng, Hehu Xie, Zhenli Xu

Physics and Society · Cross-listed from cs.AI

When AI output tips to bad but nobody notices: Legal implications of AI's mistakes

Dylan J. Restrepo, Nicholas J. Restrepo, Frank Y. Huo et al. (+1 more)

The adoption of generative AI across commercial and legal professions offers dramatic efficiency gains – yet for law in particular, it introduces a perilous failure mode in which the AI fabricates fictitious case law, statutes, and judicial holdings that appear entirely authentic. Attorneys who unknowingly file such fabrications face professional sanctions, malpractice exposure, and reputational harm, while courts confront a novel threat to the integrity of the adversarial process. This failure mode is commonly dismissed as random `hallucination', but recent physics-based analysis of the Transformer's core mechanism reveals a deterministic component: the AI's internal state can cross a calculable threshold, causing its output to flip from reliable legal reasoning to authoritative-sounding fabrication. Here we present this science in a legal-industry setting, walking through a simulated brief-drafting scenario. Our analysis suggests that fabrication risk is not an anomalous glitch but a foreseeable consequence of the technology's design, with direct implications for the evolving duty of technological competence. We propose that legal professionals, courts, and regulators replace the outdated `black box' mental model with verification protocols based on how these systems actually fail.
Read the full abstract

All authors Dylan J. Restrepo, Nicholas J. Restrepo, Frank Y. Huo, Neil F. Johnson

Biological Physics · Cross-listed from cond-mat.soft

A simple model for conserved intracellular dynamics exhibits multiscale pattern formation, traveling protein domains and arrested coarsening of lipid domains

Benjamin Winkler, Sergio Alonso and Markus Bär

We model the spatiotemporal dynamics of cellular protein concentrations relevant to cell polarity near membranes composed of different lipids. Therefore, we consider a three-variable continuum model for membrane-bound protein, cytosolic protein, and the local composition of a binary lipid membrane. The model contains two globally conserved quantities: the total protein content and the average fractions of the two lipid species. It combines a conserved reaction-diffusion model for the protein dynamics, undergoing an active phase separation, with a Cahn-Hilliard equation for lipid demixing. Linear stability analysis of the homogeneous steady state and direct numerical simulations show that the lipid dynamics undergoes classical phase separation, whereas the protein dynamics exhibits oscillatory phase separation for intermediate total protein contents, associated with a long-wavelength instability and traveling domains. In parameter regions where both instabilities are present, we find multiscale patterns with larger-scale traveling and rotating protein domains coexisting with smaller-scale stationary lipid domains. In this regime, traveling protein domains coexist with arrested coarsening of stationary lipid domains above a critical coupling. We further show that the main instabilities and phase diagram are well captured by an extension of a recently proposed conserved FitzHugh-Nagumo model for non-reciprocal pattern formation. The extended model consists of two non-reciprocally coupled Cahn-Hilliard equations with different interface tensions, reflecting the distinct physical properties of lipids and proteins. This also explains the observed asymmetry between static lipid patterns and traveling protein patterns.
Read the full abstract

Instrumentation and Detectors

The read-out electronics for the FLASH experiment

Luigi Calligaris, Claudio Puglia and Gianluca Lamanna

We introduce the FLASH haloscope experiment and present its electronic read-out system, currently under development. FLASH searches for Dark Matter (DM) particles and High-Frequency Gravitational Waves (HFGWs) using two cryogenic resonant cavities to scan the radio frequency spectrum between 117 and 360 MHz, looking for signals as weak as 10-22 W. The signal read-out uses Microstrip Superconducting Quantum Interference Amplifiers (MSAs) as low-noise amplifiers and Software-Defined Radio (SDR) techniques to acquire, preprocess and reduce the physics signal to a format suitable for permanent storage and offline analysis.
Read the full abstract

Fluid Dynamics

DMR effect on drag reduction of a streamlined body measured by Magnetic Suspension and Balance System

Aiko Yakeno, Hiroyuki Okuizumi, Kento Inokuma et al. (+1 more)

This study experimentally investigates the aerodynamic drag reduction capabilities of distributed micro-roughness (DMR) coatings on a streamlined model, utilising the 1-m magnetic suspension and balance system (MSBS) at Tohoku University. Previous direct numerical simulations (DNS) indicated that DMR can mitigate turbulent-energy growth by suppressing Tollmien–Schlichting (TS) waves and influencing the breakdown of streamwise vortices. The present work provides the first experimental validation of these effects using an interference-free MSBS, which is essential for accurate measurement in the laminar and transitional regimes. A streamlined model was tested with two rows of artificial tripping tape to induce transition; the DMR height was approximately 1% of the local boundary layer thickness, significantly smaller than typical roughness elements. Direct aerodynamic drag measurements using the MSBS revealed a substantial reduction of up to 43.6% within the transitional flow regime. Crucially, integrated analysis using wall-resolved large-eddy simulations (LES) and dynamic oil-flow visualisation confirmed that this benefit does not mainly originate from the suppression of flow separation. The LES drag decomposition established that the total pressure-drag budget is subordinate to skin friction, a finding complemented by oil-flow observations, which revealed qualitatively similar flow patterns regardless of the surface condition. Consequently, the observed drag reduction is primarily ascribed to friction drag reduction achieved through the modification of the boundary layer state. These findings provide compelling experimental evidence for the efficacy of DMR and offer valuable insights for optimising surface designs for passive flow control.
Read the full abstract

All authors Aiko Yakeno, Hiroyuki Okuizumi, Kento Inokuma, Yoshiyuki Watanabe

Accelerator Physics

Convexity of the longitudinal variation of third-order resonance driving terms and its application in dynamic aperture optimization

Wanbin Li, Zihan Wang, Yuejing Huang et al. (+2 more)

The optimization of the dynamic aperture (DA) of a storage ring is typically a non-convex problem with multiple local optima. Recent studies showed that reducing the variation of resonance driving terms (RDTs) along the longitudinal position improves DA very effectively, as the reduction in the longitudinal variation of lower-order RDTs suppresses higher-order nonlinear terms. Therefore, minimizing the longitudinal variation of third-order RDTs is crucial for DA optimization. In this paper, we prove that the longitudinal variation of third-order RDTs, quantified using their RMS value $f_{3,\mathrm{rms}}$ at sextupole locations, is a special convex function. In the space of sextupole strengths, the iso-surfaces of $f_{3,\mathrm{rms}}$ are a series of concentric and coaxial ellipsoidal surfaces, with the central position possessing minimum $f_{3,\mathrm{rms}}$. The scanning results of a storage ring lattice show a strong consistency between the distributions of $f_{3,\mathrm{rms}}$ and DA, indicating that the optimization of DA can be regarded as a roughly approximate convex optimization problem. Based on this, a fast DA optimization method based on particle tracking is developed, where a high-quality initial population for an intelligent algorithm is generated with a Gaussian distribution based on the geometric structure of $f_{3,\mathrm{rms}}$.
Read the full abstract

All authors Wanbin Li, Zihan Wang, Yuejing Huang, Bingfeng Wei, Zhenghe Bai

Optics

Visible Spectral-Domain Optical Coherence Tomography for Photonic Integrated Circuits Characterization

Yin Min Goh, Chao Li, Yunchan Hwang et al. (+4 more)

Visible photonic integrated circuits underpin applications ranging from AR/VR to quantum control, yet lack a high-resolution, nondestructive diagnostic comparable to the optical frequency-domain reflectometry used in infrared silicon photonics. Here we adapt spectral-domain optical coherence tomography to measure guided-mode back-reflections in visible PICs. Broadband visible light injected into a circuit generates back-reflections that interfere with a depth-referencing local oscillator, and the resulting spectral fringes are recorded on a spectrometer. We validate the approach by resolving multiple round-trip echoes in a waveguide-coupled ring resonator using only single-port access. We then extend it to circuits integrated with diamond quantum micro-chiplets, clearly resolving input and output facets as well as PIC–QMC transition regions. The system achieves shot-noise-limited sensitivity, 50 dB dynamic range, 8 um axial resolution in silicon nitride, and a 2 mm imaging depth at 6 dB roll-off. SD-OCT therefore provides a practical, high-resolution diagnostic for visible PICs that uses a broadband probe source and requires only single-port optical access, enabling rapid characterization of propagation loss, backscattering, and dispersion.
Read the full abstract

All authors Yin Min Goh, Chao Li, Yunchan Hwang, Helaman Flores, Mahmoud Jalali Mehrabad, James G. Fujimoto, Dirk R. Englund

Plasma Physics

Clumps in the Resistive-Drift-Wave turbulence

S. I. Krasheninnikov and R. D. Smirnov

The results of numerical simulations of the Hasegawa-Wakatani equation demonstrate that, similarly to decaying turbulence in 2D fluids, at a small electron adiabaticity parameter, the resistive-drift-wave (RDW) turbulence is dominated by the vortices. Occasionally, vortices with different signs become coupled and propagate ballistically as a dipole over a large distance, entraining plasma density. Such ballistic motion of the vortex-density clumps in radial direction provides a non-local feature of plasma transport associated with the RDW turbulence. Large magnitude of plasma parameters perturbations associated with clumps can initiate other plasma instabilities and nonlinear phenomena.
Read the full abstract

Plasma Physics

Laser ion acceleration from concave targets by subpicosecond pulses

K. V. Lezhnin, V. Ospina-Bohórquez, J. Griff-McMahon et al. (+6 more)

Laser-driven proton acceleration provides a powerful route for generating ultrashort, high-charge proton beams. Many applications, including secondary neutron sources and inertial fusion, benefit from tight proton beam focusing. Concave targets offer a robust solution, yet the scaling of proton focusing with laser and target parameters remains poorly understood. Here, we present a numerical study of laser-driven proton acceleration and focusing from hemispherical targets using the fully kinetic, relativistic Particle-In-Cell code EPOCH. We focus on the sub-picosecond laser-pulse regime (duration $\lesssim 10^2$ fs), centering on the laser parameters of our recent experiment at the CSU ALEPH laser facility. We investigate the proton acceleration mechanisms, characterize proton focusing, and assess how focal spot parameters scale with laser and target parameters. We identify Target Normal Sheath Acceleration as the dominant mechanism, supplemented by a secondary post-acceleration stage near the geometrical center of the hemisphere. We demonstrate that both the proton focal spot size and focal plane position scale approximately linearly with the hemisphere radius, with the focal plane consistently located downstream of the geometrical center. The opening angle of the concave target mainly affects the proton beam waist. Energy-dependent proton focusing is interpreted as a consequence of the evolving curvature of the accelerating structure, which departs from the target curvature. Evidence for self-similar proton focusing is found in the regime of nearly uniform target irradiation.
Read the full abstract

All authors K. V. Lezhnin, V. Ospina-Bohórquez, J. Griff-McMahon, K. Bhutwala, R. Nedbailo, R. Davis, X. Vaisseau, I. D. Kaganovich, S. Malko

Tuesday 24 March

Fluid Dynamics

A simplified model for coupling Darrieus-Landau and diffusive-thermal instabilities

Prabakaran Rajamanickam

A simplified phenomenological model is proposed to couple the long-wave Darrieus–Landau (DL) instability and the short-wave diffusive-thermal (DT) instability in premixed flames. By identifying a cubic coupling term in the linear dispersion relation, representing the leading-order interaction between hydrodynamic expansion and diffusive transport, this framework moves beyond the traditional treatment of these instabilities in isolation. Two distinct asymptotic regimes are identified: the first recovers the classical Michelson–Sivashinsky equation for order-unity positive Markstein numbers $\mathcal M>0$, the second reveals a distinguished DL-DT crossover regime where both instabilities participate at equal order. In this crossover limit, where the Markstein number is small ($\mathcal M \sim \sqrt{\epsilon}$ with $\epsilon$ measuring thermal expansion), a generalized evolution equation is derived featuring a nonlocal stabilising term controlled by the hydro-diffusive number $\mathcal{N} = \mathcal A/\delta_L^2$, where $\mathcal A$ is the hydro-diffusive area – the characteristic area over which hydrodynamic and diffusive transport processes interact. This term remains active even when Markstein stabilisation vanishes. Numerical solutions in sufficiently large domains based on our model reveal a distinctive chaotic regime in which the characteristic DL cusp structures are in persistent competition with small-scale wrinkles. This minimal unified framework thus captures the essential coupled dynamics governing flame front instability and provides a tractable explanation for the fine-scale cellular structures and accelerated growth rates observed, without recourse to the full complexity of the complete conservation equations.
Read the full abstract

Applied Physics

Scaling atom-by-atom inverse design with nano-topology optimization and diffusion models

Chun-Teh Chen and Denvid Lau

The mechanical properties of metallic nanostructures are governed not only by topology but also by crystal symmetry and face-specific surface physics, which are typically absent from continuum topology optimization. We develop an atom-by-atom inverse design framework that combines Nano-Topology Optimization (Nano-TO) with conditional denoising diffusion probabilistic models. Nano-TO treats each atom as a discrete design variable and evaluates stiffness from the symmetric curvature of the total energy, removing residual surface-stress bias. A crystallography-aligned multi-shell sensitivity filter stabilizes the optimization and enables designs containing more than 6.5 x 10^5 atoms. Using aluminum nanocantilevers, we identify a surface-physics-driven topology selection rule: thickness-periodic beams favor brace-dominated trusses, whereas finite-thickness beams favor nearly closed walls that provide efficient shear paths and reduce surface penalties. At sufficiently small scales, these walls become mechanically unstable, and truss-like layouts reappear. In nanopillar studies, atomistic optimization outperforms continuum topology-optimized designs. Finally, conditional diffusion models trained on Nano-TO data generate diverse high-performance candidates near the optimization frontier. These results establish nanoscale inverse design as a coupled problem of topology and surface physics.
Read the full abstract

Physics and Society

Possible Reforms of the Tibetan Lunisolar Calendar

Tsogtgerel Gantumur

The family of Tibetan lunisolar calendars operates on a shared arithmetic axiom (67 lunar months = 65 solar months) that provides a rigid structure but causes observable seasonal drift. This study deconstructs the calendar through a progressive analytical sequence, first presenting it as an explicit computational procedure, then isolating its structural core of incidence rules and mean-motion models. This separation distinguishes structurally forced features from tradition-dependent ones, allowing inaccuracies to be rigorously decomposed into internal arithmetic drift, sidereal misalignment, and anomaly-phase defects. Crucially, computational analysis also reveals remarkable historical robustness: the discrete arithmetic of traditional day rules renders boundary tie-cases operationally absent, while large internal temporal buffers and the multi-hour inaccuracy of the classical lunar model insulated the calendar against geographic variation. On this basis, the paper develops a stratified reform space rather than a single replacement proposal. The resulting standards range from conservative rational repairs preserving traditional arithmetic to explicit astronomical reconstructions culminating in fully dynamical models of true solar and lunar motion. The guiding question is how far astronomical correction can be carried without discarding the Tibetan calendrical identity embodied in the structural rules for month and day labeling. Finally, calendric reform requires more than new formulas and constants; it demands precise numerical semantics. The proposed standards are thus formulated not merely as abstract models, but as executable, reproducible specifications suitable for implementation, validation, and long-term transmission across computational environments.
Read the full abstract

Computational Physics · Cross-listed from math.NA

Fast elementwise operations on tensor trains with alternating cross interpolation

Marc K. Ritter

Tensor trains (TTs), also known as matrix product states (MPS), are compressed representations of high-dimensional data that can be efficiently manipulated to perform calculations on the data. In many applications, such as TT-based solvers for nonlinear partial differential equations, the most expensive step is an elementwise multiplication or similar elementwise operation on multiple TTs. Known error-controlled algorithms for such operations scale as $O(\chi^4)$, where $\chi$ is the TT rank. If the rank of the output is smaller than $\chi^2$, it is possible to formulate algorithms with better scaling. In this work, we present the alternating cross interpolation (ACI) algorithm that performs such operations in $O(\chi^3)$, while maintaining error control. We demonstrate these properties on benchmark problems, achieving a significant speedup for TT ranks that are commonly encountered in practical applications.
Read the full abstract

Instrumentation and Detectors

The chemRIXS Instrument for the LCLS-II X-Ray Free Electron Laser

David J. Hoffman, Douglas Garratt, Matthew Bain et al. (+28 more)

The chemRIXS instrument at the Linac Coherent Light Source offers new opportunities for studying solution-phase systems with time-resolved soft X-ray spectroscopy through the recently commissioned high-repetition-rate LCLS-II X-ray free electron laser. The orders-of-magnitude X-ray flux improvement provided by the superconducting accelerator, combined with corresponding advances in the optical laser system and the liquid jet recirculation system, enables studies on dilute systems with high signal-to-noise compared to what was possible with the LCLS-I copper accelerator. These capabilities open up time-resolved X-ray absorption spectroscopy and resonant inelastic X-ray scattering to entirely new classes of samples, as well as enabling the development of new soft X-ray spectroscopies on liquid samples. An overview of the beamline components and the first LCLS-II commissioning results are presented.
Read the full abstract

All authors David J. Hoffman, Douglas Garratt, Matthew Bain, Christina Y. Hampton, Benjamin I. Poulter, Jyoti Joshi, Giacomo Coslovich, Frank P. O'Dowd, Daniel P. DePonte, Alexander H. Reid, Lingjia Shen, Daniel Jost, Mina R. Bionta, Joshua J. Turner, Ming-Fu Lin, Philip Heimann, Stefan P. Moeller, Jake D. Koralek, Tyler Johnson, K Ninh, Raybel Almeida, Adam Berges, Stephanie Fung, Shuai Li, Eetu Pelimanni, Amke Nimmrich, Munira Khalil, Linda Young, Thomas J.A. Wolf, Kristjan Kunnus, Georgi L. Dakovski

Physics Education

Canadian Physics Counts: Considering How Identity Relates to Experiences of Harm within the Canadian Physics Community

Adrianna Tassone, Eden J. Hennessey, Anastasia Smolina et al. (+3 more)

Harmful experiences such as harassment and discrimination continue to push many people out of science. To better understand identities and experiences of harm among physicists, we conducted Canadian Physics Counts, the first comprehensive national survey examining equity, diversity, and inclusion within Canada's physics community. To better understand identities and experiences of harm among physicists, we conducted Canadian Physics Counts, the first comprehensive national survey examining equity, diversity, and inclusion within Canada's physics community. We explored experiences of harm focusing on personal harassment, sexual harassment, and sexual assault. We measured both direct experiences of harm and awareness of harm happening to others. Our analyses revealed that women and gender-diverse physicists reported experiencing personal harassment at twice the rate of men, a pattern consistent across all academic positions, including students and early-career researchers. An intersectional focus revealed even deeper inequities. Black women and men reported the highest rates of personal harassment, while Indigenous women and men faced elevated levels of sexual harassment. Physicists with disabilities were disproportionately affected. Disabled women and gender-diverse respondents reported the highest rates of personal and sexual harassment and sexual assault, and disabled men experienced more personal harassment than men without disabilities. These findings are a clear call to action to the physics community to confront racism, sexism, homophobia, and ableism so every physicist can thrive and contribute to solving society's greatest challenges.
Read the full abstract

All authors Adrianna Tassone, Eden J. Hennessey, Anastasia Smolina, Skye Hennessey, Kevin Hewitt, Shohini Ghose

Plasma Physics

Microtearing Thresholds and Second-Stable Ballooning in the DIII-D Pedestal: Reduced Modeling and Core-Edge Implications

David R. Hatch, Leonhard A. Leppin, Mike T. Kotschenreuther et al. (+4 more)

Global and local linear gyrokinetic simulations of 42 pedestal equilibria from three DIII-D discharges are used to investigate pedestal stability and its impact on pedestal structure and confinement. Microtearing modes (MTMs) and kinetic ballooning modes (KBMs) represent the main ion scale instabilities. For all three discharges, MTMs lie near a stability boundary in the mid-pedestal and exhibit threshold behavior, with growth rates increasing at and beyond pre-ELM pressure gradients. Pedestal MTMs retain conventional signatures but also show enhanced particle transport and partial density-gradient drive, indicating they can constrain pedestal pressure rather than electron temperature alone. KBMs are typically second-stable in this region due to low magnetic shear and large pressure gradients, though they can become active near the pedestal foot where magnetic shear is higher. These findings suggest MTMs play the role of inter-ELM pressure limit in the mid-pedestal when KBM is second stable. A preliminary quasilinear mixing-length transport model, with properly tuned free parameters, reproduces experimental temperature and density profiles when coupled to ASTRA. When applied to a case with doubled separatrix density, the model predicts reduced pedestal pressure consistent with ITPA H-mode confinement trends, attributable to increased MTM and ETG transport. These results clarify pedestal-limiting mechanisms and establish a physics-based link between separatrix conditions, pedestal structure, and global confinement. This work lays the foundation for new predictive modeling capabilities for core-edge integration in burning plasma regimes.
Read the full abstract

All authors David R. Hatch, Leonhard A. Leppin, Mike T. Kotschenreuther, Saeid Houshmandyar, Swadesh M. Mahajan, Joseph Schmidt, Ping-Yu Li

Geophysics · Cross-listed from eess.IV

Sentinel-2 for Crop Yield Estimation: A Systematic Review

Mohammadreza Narimani, Alireza Pourreza, Ali Moghimi et al. (+1 more)

Accurate and timely crop yield estimation is critical for global food security, agricultural policy, and farm management. The Copernicus Sentinel-2 satellite constellation, with high spatial, temporal, and spectral resolution, has transformed agricultural monitoring by enabling field- and sub-field-scale analysis. This review synthesizes recent advances in Sentinel-2-based crop yield estimation. A key trend is the shift from regional models to high-resolution field-level assessments driven by three main approaches: (i) empirical models using vegetation indices combined with machine and deep learning methods such as Random Forest and Convolutional Neural Networks; (ii) integration of process-based crop growth models (e.g., WOFOST, SAFY) via data assimilation of Sentinel-2-derived variables like Leaf Area Index (LAI); and (iii) data fusion techniques combining Sentinel-2 optical data with Sentinel-1 SAR to mitigate cloud-related limitations. The review shows that machine learning, deep learning, and hybrid modeling frameworks can explain substantial within-field yield variability across crops and regions. However, performance remains constrained by limited ground-truth data, cloud-induced gaps, and challenges in model transferability across years and locations. Future directions include tighter integration of multi-modal data and improved in-season observations to support robust, operational decision-making in precision agriculture and sustainable intensification.
Read the full abstract

All authors Mohammadreza Narimani, Alireza Pourreza, Ali Moghimi, Parastoo Farajpoor

Fluid Dynamics

Suppression of Rayleigh-Bénard convection and restratification by horizontal convection

Florian Rein, Stefan. G. Llewellyn Smith and William. R. Young

We investigate the competition between horizontal convection (HC) and Rayleigh-Bénard convection (RBC) in a fluid layer subject to a uniform destabilizing buoyancy flux at the bottom and a horizontally varying buoyancy distribution at the top. The RBC forcing imposes negative horizontal mean vertical buoyancy gradients at the top and bottom of the fluid layer. But if the HC forcing is sufficiently strong then the volume averaged vertical buoyancy gradient, $\langle b_z \rangle$, is positive i.e.~opposite in sign to destabilizing RBC buoyancy gradients at the boundaries. If $\langle b_z \rangle>0$ we say that the layer has been ”restratified”. Using scaling analysis based on power integrals together with two-dimensional direct numerical simulations at Rayleigh numbers up to $10^{10}$, we identify two cases: a neutral stratification state, in which HC first offsets RBC so that $\langle b_z \rangle = 0$, and a strong stratification regime, in which HC dominates and $\langle b_z \rangle$ is opposite in sign, and greater in magnitude, than the prescribed destabilizing vertical buoyancy gradient at the layer boundaries. For the range of parameters explored in this study, we derive scaling laws for the onset of these regimes in terms of the horizontal and vertical flux Rayleigh numbers, $\RaH$ and $\RaV$, finding $\RaHN \sim \RaV^{4/5}$ for the neutral state and $\RaHstrg \sim \RaV$ for the onset of strong stratification. The results highlight the controlling role of the top boundary layer in setting the mean stratification and clarify the conditions under which HC suppresses RBC. These findings are relevant to geophysical environments such as subglacial lakes, and the oceans of Snowball Earth and icy moons, where bottom heating and horizontal buoyancy variations jointly shape ocean stratification.
Read the full abstract

Applied Physics

Generalized virtual wave reconstruction for vibrothermography: Overcoming the wavefront-free behavior and quantification challenges in the diffusion-wave field

Pengfei Zhu, Julien Lecompagnon, Mathias Ziegler et al. (+2 more)

Wavefront-free behavior and the resulting quantification difficulties are intrinsic limitations of vibrothermography due to the diffusive nature of thermal fields. This work proposes a generalized virtual wave reconstruction framework to address the absence of propagation features in thermal diffusion-wave fields and its impact on quantitative defect characterization. Unlike conventional virtual wave formulations restricted to Dirac-type excitations, the proposed approach establishes a rigorous spatiotemporal mapping between diffusion-wave fields and virtual wave fields under arbitrary heat-generation conditions without simplifying assumptions on thermo-mechanical coupling. The resulting ill-posed inversion problem is solved using truncated singular value decomposition (T-SVD) and the alternating direction method of multipliers (ADMM) to enhance numerical stability and suppress noise amplification. Numerical simulations demonstrate that the reconstructed virtual wave fields recover propagation characteristics absent in temperature distributions, leading to improved defect boundary definition, contrast enhancement, and depth-resolved analysis. Experiments on CFRP laminates validate the robustness of the approach and show significantly improved signal-to-noise ratio, spatial clarity, and defect size estimation compared with conventional thermographic processing methods.
Read the full abstract

All authors Pengfei Zhu, Julien Lecompagnon, Mathias Ziegler, Clemente Ibarra-Castanedo, Xavier Maldague

Chemical Physics

Application of the aperiodic defect model to a negatively charged monovacancy in phosphorene

Charlotte Rickert, Lily Barta, Ernst-Christian Flach et al. (+2 more)

We apply the recently introduced aperiodic defect model (ADM) to a negatively charged monovacancy in a phosphorene monolayer. In contrast to conventional supercell approaches, the ADM treats a single defect embedded in the true non-defective crystalline mean field thereby avoiding spurious defect-defect interactions and the need for charge corrections. At the same time, it effectively reduces the calculation to a fragment, enabling the use of high-level molecular electronic-structure methods. Converging the Hartree-Fock and correlation contributions to the thermodynamic limit yields a benchmark CCSD(T)/POB-TZVP-rev2 formation energy of 0.81 eV for the negatively charged monovacancy in the (5|9) configuration. The excitation energy to the lowest singlet excited state of this defect at the EOM-CCSD/POB-TZVP-rev2 level is found to be 1.95 eV. Overall, the ADM provides a highly promising route towards quantitatively accurate and systematically improvable descriptions of defects in solids and on surfaces, bridging the gap between solid-state physics and molecular quantum chemistry.
Read the full abstract

All authors Charlotte Rickert, Lily Barta, Ernst-Christian Flach, Daniel Kats, Denis Usvyat

Optics

Coherent multi-dimensional widefield microscopy

Mohammadjavad Azarm, Rizwan Asif, Alessandra Milloch et al. (+14 more)

Understanding how electronic excitations evolve across space and time is essential for revealing the microscopic processes underlying quantum and optoelectronic materials. However, existing approaches cannot simultaneously resolve ultrafast coherent dynamics with microscopic spatial information: pump-probe microscopy lacks access to quantum coherence, while two-dimensional electronic spectroscopy (2DES) requires slow point-by-point scanning for spatial resolution. Here we introduce a widefield two-dimensional electronic spectroscopy microscope (2DESM) combining multidimensional coherent spectroscopy with widefield imaging, enabling simultaneous femtosecond temporal and micrometer spatial resolution across a broadband spectral range. Applying 2DESM to hBN-encapsulated WSe2, we directly visualize spatial variations in exciton coherence and relaxation associated with the local environment, establishing 2DESM as a powerful platform for probing many-body interactions, energy transport, and structure-function relationships in low-dimensional materials and devices.
Read the full abstract

All authors Mohammadjavad Azarm, Rizwan Asif, Alessandra Milloch, Francesco Proietto, Donna Datta, Ambrine Lanseur, Sreyan Raha, Filippo Fabbri, Federica Bianco, Fabrizio Preda, Antonio Perri, Suman Chatterjee, Ziliang Ye, Giulio Cerullo, Stefania Pagliara, Gabriele Ferrini, Claudio Giannetti

Chemical Physics · Cross-listed from cond-mat.mes-hall

Quantum-classical dynamics of Rashba spin-orbit coupling

Paul Bergold, Giovanni Manfredi and Cesare Tronci

Mixed quantum-classical models are widely used to reduce the computational cost of fully quantum simulations. However, their general applicability across different classes of problems remains an open question. Here, we address this issue for systems featuring spin-orbit coupling. In particular, we study the interaction dynamics of quantum spin-1/2 and classical orbital momentum in one-dimensional models of Rashba nanowires. We tackle this problem by resorting to a new quantum-classical Hamiltonian model that, unlike conventional approaches, retains the Heisenberg principle and captures correlation effects beyond the common Ehrenfest method. Based on Koopman wavefunctions in classical mechanics, the new model was recently implemented numerically via a particle scheme – the koopmon method – which is extended here to treat spin-orbit coupling. We apply the koopmon method to study the quantum-classical dynamics of nanowire models, with and without the presence of a harmonic potential and in both Rashba-dominated (strong coupling) and Zeeman-dominated (weak coupling) regimes. Considering realistic semiconductor parameters, the results are contrasted with both fully quantum and quantum-classical Ehrenfest dynamics. In the absence of external potential, the koopmon method qualitatively reproduces the features of the fully quantum evolution for all coupling regimes. While it exhibits a slight loss in spin accuracy compared to Ehrenfest simulations, the latter fail to capture the orbital dynamics. In the presence of a harmonic potential, the koopmon scheme reproduces several features of full quantum dynamics with accuracy levels that are unachievable by the Ehrenfest model. We conclude by presenting a test case that exhibits the formation of cat-like states.
Read the full abstract