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Physics Physics

physics Watch Physics

Sunday 16 November

Fluid Dynamics · Cross-listed from cs.CE

Modelling Heterogeneous Interfaces using Element-based Finite Volumes

Suhaib Ardah, Francisco J. Profito and Daniele Dini

Accurately depicting multiphysics interactions in interfacial systems requires computational frameworks capable of reconciling geometric adaptability with strict conservation fidelity. However, traditional spatiotemporal discretisation methods often compromise between mesh flexibility and flow conservation enforcement, hence constraining their effectiveness in elucidating the underlying mechanisms. Here, we respond to these computational demands by developing a novel three-dimensional adaptation of the Element-based Finite Volume Method (EbFVM) – a hybrid numerical strategy that merges the geometric flexibility of Finite Element Methods with the conservation-centric principles of Finite Volume Methods. The proposed framework introduces advanced discretisation techniques tailored to unstructured, irregular mesh entities, including detailed parametric shape functions, robust flux integration schemes and rigorous body-fitted curvilinear coordinate mappings. Through a series of lubrication-driven benchmark problems, we demonstrate the EbFVM's capacity to capture intricate transport phenomena, strong field couplings and scale disparities across geometrically complex domains. By enabling accurate modelling in geometrically and physically challenging interfacial systems, the three-dimensional EbFVM offers a versatile and generalisable tool for simulating transport phenomena in a plethora of multiphysics applications.
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Biological Physics · Cross-listed from cond-mat.soft

A Complex Topological Phase in C-Spin Active Matter

Alessandro Scirè

This work introduces a new theoretical model for active matter ("complementary-spins" or c-spins), exploring the interplay of positional and orientational order in mobile agents with rotational freedom, divided into two populations with contrasting interactions. The system's behavior depends on its size and a control parameter (circular anisotropy) that splits the agents' natural rotational frequencies. Key findings include distinct phases based on anisotropy: Small Anisotropy: Stable, regular equilibrium patterns emerge. Moderate Anisotropy: Formation of complex, non-equilibrium topological point defects (vortex states), which are bistable with uniform patterns. These robust, self-repairing defects exhibit counter-rotating c-spin loop trains, spin-momentum locking, and dissipationless flow, classified by a two-valued topological charge. High Anisotropy: Transition to active turbulence and loss of order. Statistical analysis reveals a double phase transition at a critical value: a standard symmetry-breaking transition and a novel topological phase transition activating the vortex complexes. Increasing system size enhances organizational complexity and the development of spin-momentum locked transport networks. This model provides a new framework for understanding robustness and morphogenesis in living systems.
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Applied Physics · Cross-listed from eess.AS

Eardrum sound pressure prediction from ear canal reflectance based on the inverse solution of Webster's horn equation

Reinhild Roden, Tobias Sankowsky-Rothe, Nick Wulbusch et al. (+2 more)

To derive ear canal transfer functions for individualized equalization algorithms of in-ear hearing systems, individual ear canal models are needed. In a one-dimensional approach, this requires the estimation of the individual area function of the ear canal. The area function can be effectively and reproducibly calculated as the inverse solution of Webster's horn equation by finite difference approximation of the time domain reflectance. Building upon previous research, the present study further investigates the termination of the approximation at an optimal spatial resolution, addressing the absence of higher frequencies in typical ear canal measurements and enhancing the accuracy of the inverse solution. Compared to the geometric reference, more precise area functions were achieved by extrapolating simulated input impedances of ear canal geometries up to a frequency of 3.5 MHz, corresponding to 0.1 mm spatial resolution. The low pass of the previous work was adopted but adjusted for its cut-off frequency depending on the highest frequency of the band-limited input impedance. Robust criteria for terminating the area function at the approximated ear canal length were found. Finally, three-dimensional simulated and measured ear canal transfer impedances were replicated well employing the previously introduced and herein validated one-dimensional electro-acoustic model fed by the area functions.
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All authors Reinhild Roden, Tobias Sankowsky-Rothe, Nick Wulbusch, Alexey Chernov, Matthias Blau

Optics · Cross-listed from quant-ph

Sparsity-Driven Entanglement Detection in High-Dimensional Quantum States

Stav Lotan, Hugo Defienne, Ronen Talmon et al. (+1 more)

The characterization of high-dimensional quantum entanglement is crucial for advanced quantum computing and quantum information algorithms. Traditional methods require extensive data acquisition and suffer from limited visibility due to experimental noise. Here, we introduce a sparsity-driven framework to enhance the detection and certification of high-dimensional entanglement in spatially entangled photon pairs. By applying $\ell_1$-regularized reconstruction to sample covariance matrices obtained from measurements on photons produced via spontaneous parametric down-conversion (SPDC) measurements, we enhance the visibility of the correlation signal while suppressing noise. We demonstrate, using a position-momentum Einstein-Podolsky-Rosen (EPR) entanglement criterion, that this approach enables certification of an entanglement dimensionality that cannot be achieved without regularization. Our method is scalable, simple to use and compatible with existing quantum-optics platforms, thus paves the way for efficient, real-time analysis of high-dimensional quantum states.
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All authors Stav Lotan, Hugo Defienne, Ronen Talmon, Guy Bartal

Fluid Dynamics

Benjamin-Feir Instability of Interfacial Gravity-Capillary Waves in a Two-Layer Fluid. Part II. Surface-Tension Effects

Olga Avramenko and Volodymyr Naradovyi

This second part of the study develops a geometric and asymptotic description of how surface tension governs the modulational stability of interfacial waves in a two-layer fluid. Extending the analytical framework of Part~I, surface tension is treated as a freely adjustable parameter, enabling one to trace how nonlinear and dispersive properties evolve across a broad range of depth ratios and density contrasts. Using the nonlinear Schrödinger reduction together with long-wave asymptotics, the mechanisms shaping the boundaries between stable and unstable regimes are identified and their dependence on surface tension is quantified. The long-wave structure is governed by two density values that determine the bases of the loop and the corridor on the stability diagrams. Their ordering switches only when the lower layer is deeper, and loop-type structures arise exclusively in this regime. A second organising parameter is the classical Bond threshold, at which the dispersive and nonlinear singularities coincide. When surface tension exceeds this value and the upper layer is sufficiently deep, resonant and dispersive effects generate a capillary cut that replaces the corridor and characterises strongly capillary, upper-layer-dominated configurations. To unify these observations, full three-dimensional critical surfaces separating different types of nonlinear and dispersive behaviour are computed. The loop, corridor, and cut arise as planar sections of these surfaces, and their transitions follow from the deformation of the intersection between the resonant and dispersive sheets. Two depth ratios correspond to geometric degeneracies: equal layer depths, where the intersection reduces to a straight line, and the golden-ratio configuration, where the critical surface becomes horizontally tangent at the Bond threshold.
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Atomic Physics · Cross-listed from cond-mat.quant-gas

Small Clusters of $^4$He Atoms in Finite-Cutoff Effective Field Theory

Betzalel Bazak

Small clusters of $^4$He atoms are benchmark systems for universal few-body physics near the unitary limit. We study these systems using a finite-cutoff effective field theory calibrated to low-energy observables from the realistic LM2M2 potential. The chosen two-body cutoff reproduces both the atom–atom scattering length and effective range, while a regulated three-body interaction is adjusted to the trimer and tetramer ground-state energies. We distinguish total binding energies from the one-atom separation energies $S_A^*=B_A^*-B_{A-1}$ of the shallow excited states. Ground-state energies through $A=8$ are reproduced at the few-percent level, but threshold-sensitive observables are less accurate. In particular, the calculated tetramer separation energy is $S_4^*=2.85$~mK, compared with $0.92$–$0.96$~mK in converged LM2M2 calculations, and the atom–trimer scattering length differs substantially from modern LM2M2 benchmarks. For $A\ge5$, the available excited-state benchmarks are sparse and strongly method dependent. Comparison with another soft-core interaction suggests that the discrepancies primarily reflect short-distance physics and higher-order operators omitted from the finite-cutoff Hamiltonian rather than numerical convergence of the stochastic variational calculation. Finite-cutoff EFT therefore provides an efficient description of ground-state systematics, whereas shallow excited states and atom–cluster scattering require a controlled higher-order and cutoff-dependence analysis.
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Fluid Dynamics

Using Physics Informed Neural Network (PINN) and Neural Network (NN) to Improve a $k-\omega$ Turbulence Model

Lars Davidson

l flows and flat-plate boundary layers. However, it predicts too low a turbulent kinetic energy. This is a feature it shares with most other two-equation turbulence models. When comparing the terms in the k equations with DNS data it is found that the production and dissipation terms are well predicted but the turbulent diffusion is not. In the present work the poor modeling of the turbulent diffusion is improved using Physics Informed Neural Network (PINN) and Neural Network (NN).The k equation is turned into an ordinary differential equation for the turbulent viscosity in the k equation, nu_{t,PINN}, which is solved using PINN. A new turbulent Prandtl number is then computed as sigma_{k} = nu_{t}/nu_{t,PINN} where nu_t = k/omega.To compensate for the new, larger turbulent kinetic energy, three coefficients in the new k-omega model are computed using three NN models. The new turbulence model, called the k-omega-PINN-NN model, is shown to produce excellent velocity, skin friction and turbulent kinetic profiles in channel flow at Re_tau = 2 000, 5 200 and Re_tau = 10 000 as well as in flat-plate boundary layer flow (slightly too large a k for the latter case). The k-omega-PINN-NN model is also used for predicting the flow over a periodic hill and the agreement with DNS is very good. At the end of the Conclusions, we give an example on how a NN model can be replaced with a Python symbolic regression (pySR); the latter may conveniently be imported in commercial CFD codes. All Python PINN, NN and pySR scripts as well as the Python CFD code can be downloaded (Davidson, 2025a).
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Fluid Dynamics

Generative Reconstruction of Spatiotemporal Wall-Pressure in Turbulent Boundary Layers via Patchwise Latent Diffusion

Xiantao Fan, Meet Hemant Parikh, Yi Liu et al. (+4 more)

Wall-pressure fluctuations in turbulent boundary layers drive flow-induced noise, structural vibration, and hydroacoustic disturbances, especially in underwater and aerospace systems. Accurate prediction of their wavenumber-frequency spectra is critical for mitigation and design, yet empirical/analytical models rely on simplifying assumptions and miss the full spatiotemporal complexity, while high-fidelity simulations are prohibitive at high Reynolds numbers. Experimental measurements, though accessible, typically provide only pointwise signals and lack the resolution to recover full spatiotemporal fields. We propose a probabilistic generative framework that couples a patchwise (domain-decomposed) conditional neural field with a latent diffusion model to synthesize spatiotemporal wall-pressure fields under varying pressure-gradient conditions. The model conditions on sparse surface-sensor measurements and a low-cost mean-pressure descriptor, supports zero-shot adaptation to new sensor layouts, and produces ensembles with calibrated uncertainty. Validation against reference data shows accurate recovery of instantaneous fields and key statistics.
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All authors Xiantao Fan, Meet Hemant Parikh, Yi Liu, Xin-Yang Liu, Junyi Guo, Meng Wang, Jian-Xun Wang

Biological Physics · Cross-listed from q-bio.OT

Self-Organization Dynamics Beyond Equilibrium: Discreteness, Computation, and Rules of Life

Hyun Youk

Living systems self-organize in ways that conventional physical frameworks-based on forces, energies, and continuous fields-cannot fully capture. Processes like gene regulation and cellular decision-making involve rule-based logic and computational interactions. Here, I introduce the concept of non-equilibrium capacity (NEC) to denote the finite capacity of living systems to generate and sustain life-associated dynamics-the very capacity that defines viability-and whose irreversible loss constitutes death. I argue that two lines of inquiry are especially promising for understanding why this capacity is inevitably lost. First, experiments that slow or suspend all cellular processes reveal "low speed limits" below which life collapses. Second, generalized cellular automata-where cells interact over diffusion-defined neighborhoods and obey discrete rules-provide a framework to understand how order emerges or persists. Together, these approaches suggest a new grammar of biology that complements energy-based physics and explains how living systems sustain and ultimately lose their NEC.
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Physics and Society

Manipulating Collective Opinion through Social Network Intervention

Shigefumi Hata, Renaud Lambiotte, Hiroya Nakao et al. (+1 more)

Social media platforms have transformed the dynamics of collective opinion formation, enabling rapid, large-scale interactions while simultaneously exposing online discourse to polarization and manipulation. Traditional models of opinion dynamics often predict convergence to a consensus, yet empirical evidence consistently highlights persistent polarization and radicalization, especially on contentious issues. This paper analytically investigates a mathematical model that captures the complex interplay of polarization, radicalization, and consensus within networked societies. By analyzing the emergence and stability of opinion clusters, we identify critical thresholds marking phase transitions in collective behavior, interpreted via a stability landscape. We further explore network-based interventions to manipulate the collective opinion, revealing that reducing inter-agent interactions can lead to unintended, irreversible shifts in opinion distributions. Our results underscore the dual-edged nature of intervention strategies, offering theoretical insight into the fragility and manipulability of public opinion in digital environments.
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All authors Shigefumi Hata, Renaud Lambiotte, Hiroya Nakao, Ryota Kobayashi

Fluid Dynamics

Dynamics of levitation during rolling over a thin viscous film

Siqi Chen, Cheng Liu, Neil J. Balmforth et al. (+2 more)

A mathematical model is derived for the dynamics of a cylinder, or wheel, rolling over a thin viscous film. The model combines the Reynolds lubrication equation for the fluid with an equation of motion for the wheel. Two asymptotic limits are studied in detail to interrogate the dynamics of levitation: an infinitely wide wheel and a relatively narrow one. In both cases the front and back of the fluid-filled gap are either straight or nearly so. To bridge the gap between these two asymptotic limits, wheels of finite width are considered, introducing a further simplying approximation: although the front and back are no longer expected to remain straight for a finite width, the footprint of the fluid-filled gap is still taken to be rectangular, with boundary conditions imposed at the front and back in a wheel-averaged sense. The Reynolds equation can then be solved by separation of variables. For wider wheels, with a large amount of incoming flux or a relatively heavy loading of the wheel, the system is prone to flooding by back flow with fluid unable to pass underneath. Otherwise steady planing states are achieved. Both lift-off and touch-down are explored for a wheel rolling over a film of finite length. Theoretical predictions are compared with a set of experimental data.
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All authors Siqi Chen, Cheng Liu, Neil J. Balmforth, Sheldon Green, Boris Stoeber

Optics

Spectro-Polarimetric Holographic Multiplexing Metasurface with Super-High Capacity Empowered by Mechanical Rotation

Ting Ma, Xianjin Liu, Qiwen Bao et al. (+2 more)

Mechanically reconfigurable metasurfaces capable of translation, rotation, and permutation have attracted considerable attention for high-capacity optical information storage and full-color holographic displays, owing to their low-power and high functional scalability, despite the additional system-level complexity introduced by precision rotation stages. This study presents a differentiable inverse design framework for such metasurfaces, creating an accurate mapping between meta-atom geometries and their multi-channel optical responses across diverse optical dimensions. Using a deep neural network-driven, end-to-end optimization pipeline, the framework enables intelligent, iterative refinement of rotatable metasurface within constrained design space. Using this approach, we show high-fidelity holographic video display by rotating a single element in a cascaded metasurface doublet around the optical axis. The doublet enables pixel-resolved holographic imaging with 288 independent channels, and by switching input/output polarization states, the system demonstrates four distinct full-color dynamic holographic videos. This work establishes an alternative paradigm for optical parameter multiplexing and end-to-end inverse design in mechanically reconfigurable metasurfaces, suggesting applications in compact optical systems, dynamic holography, information processing, and optical computing.
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All authors Ting Ma, Xianjin Liu, Qiwen Bao, Bolun Zhang, Jun-Jun Xiao

Saturday 15 November

Geophysics

Determination of new national highpoints of five African and Asian countries, Saudi Arabia, Uzbekistan, Gambia, Guinea-Bissau, and Togo

Eric Gilbertson and Matthew Gilbertson

Not all nations on earth have previously been surveyed accurately enough to know for certain which peak is the national highpoint, the highest peak in the country. Knowledge of these peaks is important for understanding the physical geography of these countries in terms of natural resource availability, watershed management, and tourism potential. For this study, ground surveys were conducted between 2018-2025 with modern professional surveying equipment, including differential GPS units and Abney levels, to accurately determine the national highpoints in five African and Asian countries where uncertainty existed. New national highpoints were determined for Saudi Arabia (Jabal Ferwa), Uzbekistan (Alpomish), Gambia (Sare Firasu Hill), Guinea-Bissau (Mt Ronde), and Togo (Mt Atilakoutse). Elevations were measured with sub-meter vertical accuracy for candidate peaks in Saudi Arabia, Gambia, Guinea-Bissau, and Togo. Relative elevations were measured between contender peaks in Uzbekistan with sufficient accuracy to determine the highpoint.
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Data Analysis and Statistics · Cross-listed from cond-mat.stat-mech

A matrix form solution of the multi-dimensional generalized Langevin equation in the quadratic potential

Rana Imran Mushtaq, Chunyang Wang, Shi Zhi et al. (+2 more)

In this research paper, we present an exact matrix form analytical solution of the multi-dimensional generalized Langevin equation with quadratic potentials. Our investigation provides detailed expressions for the two-dimensional probability distribution and extends the understanding of the dynamics governed by harmonic potentials. By utilizing the inverse Laplace transformation, we offer a precise method to solve these equations, corroborated by specific examples. This study contributes to the fundamental understanding of stochastic processes in multi-dimensional systems with harmonic potentials and clarifies the limitations of our approach. While the findings are specific to quadratic potentials, they provide a robust framework for exploring related phenomena within this context.
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All authors Rana Imran Mushtaq, Chunyang Wang, Shi Zhi, Zengxuan Zhao, J M Nyasulu

Data Analysis and Statistics

Human-aligned Quantification of Numerical Data

Anton Kolonin

Quantifying numerical data involves addressing two key challenges: first, determining whether the data can be naturally quantified, and second, identifying the numerical intervals or ranges of values that correspond to specific value classes, referred to as "quantums," which represent statistically meaningful states. If such quantification is feasible, continuous streams of numerical data can be transformed into sequences of "symbols" that reflect the states of the system described by the measured parameter. People often perform this task intuitively, relying on common sense or practical experience, while information theory and computer science offer computable metrics for this purpose. In this study, we assess the applicability of metrics based on information compression and the Silhouette coefficient for quantifying numerical data. We also investigate the extent to which these metrics correlate with one another and with what is commonly referred to as "human intuition." Our findings suggest that the ability to classify numeric data values into distinct categories is associated with a Silhouette coefficient above 0.65 and a Dip Test below 0.5; otherwise, the data can be treated as following a unimodal normal distribution. Furthermore, when quantification is possible, the Silhouette coefficient appears to align more closely with human intuition than the "normalized centroid distance" method derived from information compression perspective.
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Optics

Generation of Bright and Controllable Isolated Attosecond X-Ray Pulses from Synchronized Mid-Infrared and Ultra-short Ultraviolet Laser Fields

Davis Robinson, Kyle A. Hamer, Chelsea Kincaid et al. (+2 more)

We investigate, by solving the time-dependent Schrödinger equation in the single-active-electron approximation in helium, a two-color scheme for tabletop high-order harmonic generation (HHG) that combines a mid-infrared (MIR) driving field with an ultrashort ultraviolet (UV) pulse that could be generated via resonant dispersive wave emission in gas-filled hollow-core fibers. This configuration enables the generation of bright, isolated, and tunable attosecond X-ray pulses. In contrast to single-color driving schemes, which suffer from low conversion efficiency, unfavorable wavelength scaling, and limited spectral control, the MIR+UV approach provides a practical and controllable route for advancing tabletop ultrafast spectroscopy and real-time molecular imaging within current experimental capabilities.
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All authors Davis Robinson, Kyle A. Hamer, Chelsea Kincaid, Michael Chini, Nicolas Douguet

Optics

Direct Photochemical Patterning of Lithium Niobate Thin Films for Scalable Nonlinear Optical Metasurfaces

Rana Faryad Ali and Guillermo Aguilar

Lithium niobate is one of the most sought-after materials for nanophotonic devices, including frequency converters, modulators, and quantum light sources. Integration of lithium niobate into optical devices, however, is hampered by significant top-down fabrication challenges due to its exceptional chemical resistance. Scalable fabrication methods that preserve material quality while reducing fabrication complexity and cost are, therefore, crucial to advancing lithium niobate devices. We present a photochemical metal-organic decomposition technique for the scalable patterning of lithium niobate at ambient conditions, eliminating the need for harsh etching conditions and cleanroom protocols. The method utilizes a solution of a custom-prepared photosensitive organometallic precursor as a negative photoresist. The UV light exposure of the thin films of the precursor through a photomask, followed by rinsing with ethanol, yields amorphous patterns, which transform into crystalline lithium niobate after a calcination step. This method enables a scalable fabrication of a range of complex geometric shapes with a feature resolution down to $30\,\mu\mathrm{m}$. The patterned lithium niobate structures exhibit a tunable second harmonic generation activity with an isotropic optical response. This approach offers a scalable and low-cost pathway for manufacturing lithium niobate photonics and the potential to fabricate other materials (e.g., barium titanite and lithium tantalate).
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Computational Physics · Cross-listed from astro-ph.IM

QuaRT: A toolkit for the exploration of quantum methods for radiation transport

Rasmit Devkota and John H. Wise

QuaRT is a Python library for quantum simulation of radiative transfer in astrophysical and cosmological problems. It features a novel angular redistribution methodology for lattice Boltzmann methods which improves the isotropy of simulations of objects such as stars in non-scattering media.
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Physics and Society · Cross-listed from astro-ph.IM

AstroMLab 5: Structured Summaries and Concept Extraction for 400,000 Astrophysics Papers

Yuan-Sen Ting, Alberto Accomazzi, Tirthankar Ghosal et al. (+4 more)

We present a dataset of 408,590 astrophysics papers from arXiv (astro-ph), spanning 1992 through July 2025. Each paper has been processed through a multi-stage pipeline to produce: (1) structured summaries organized into six semantic sections (Background, Motivation, Methodology, Results, Interpretation, Implication), and (2) concept extraction yielding 9,999 unique concepts with detailed descriptions. The dataset contains 3.8 million paper-concept associations and includes semantic embeddings for all concepts. Comparison with traditional ADS keywords reveals that the concepts provide denser coverage and more uniform distribution, while analysis of embedding space structure demonstrates that concepts are semantically dispersed within papers-enabling discovery through multiple diverse entry points. Concept vocabulary and embeddings are publicly released at https://github.com/tingyuansen/astro-ph_knowledge_graph.
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All authors Yuan-Sen Ting, Alberto Accomazzi, Tirthankar Ghosal, Tuan Dung Nguyen, Rui Pan, Zechang Sun, Tijmen de Haan

Geophysics

LiDAR Accuracy on North American Mountain Summits

Eric Gilbertson, Richard Hensley, Andrew Kirmse et al. (+2 more)

Mountainous terrain is increasingly being measured and mapped by airplane-based LiDAR (Light Detection and Ranging) techniques, but the accuracy of these measurements in such topographically variable terrain is not well understood. For this study we measured 179 mountain summits with differential GNSS static surveys and compared summit elevation and location measurements to those measured by LiDAR in point cloud data sets. We measured summits in 13 US states (Washington, Idaho, Montana, Utah, California, Nevada, Arizona, New Mexico, Michigan, Wisconsin, Kentucky, Colorado, and Pennsylvania) and two Canadian provinces (British Columbia and Nova Scotia). Summits included icecapped peaks, open rocky peaks, and tree-covered peaks ranging in elevation from 490m to over 4000m. LiDAR-point-cloud-derived summit elevations and locations were computed using four different methods: manual processing, highest ground return, highest return, and Lastools reclassification. The average one-sigma LiDAR vertical errors for each method were 0.50m, 1.09m, 9.83m, and 1.96m, respectively. Average one-sigma horizontal errors were 3.03m, 2.41m, 5.17m, 3.78m, respectively. Errors are also presented separately for each type of summit. Error sources include sharp summits being unsampled, dense vegetation misclassified as ground, human-created structures misclassified as ground, snow/ice that can melt over time, and summit erosion over time.
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All authors Eric Gilbertson, Richard Hensley, Andrew Kirmse, Kyle Bretherton, Kathryn Stanchak

Geophysics

Determination of the National Highpoint of Botswana using GNSS

Eric Gilbertsona, Mooketsi Segobye, Yashon Ouma et al. (+1 more)

Botswana has not previously been surveyed with sufficient accuracy to determine the highest peak in the country. Otse Hill and Monalanong Hill have been identified as the highest peaks, but there was uncertainty on which is highest. For this study, ground surveys were conducted on each of these peaks using an Abney level to identify the peak location and a GNSS unit to measure the elevation of each hill with sub-meter vertical accuracy. Monalanong Hill was measured to be 1.87m +/-0.02m taller than Otse hill, with an elevation of 1492.12m +/-0.01m (orthometric height, EGM2008 geoid, 95% confidence interval) above mean sea level (MSL). Otse Hill was measured to be 1490.25m +/-0.01m. Thus, Monalanong Hill is the highest hill in Botswana.
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All authors Eric Gilbertsona, Mooketsi Segobye, Yashon Ouma, Boipuso Nkwae

Instrumentation and Detectors

Measurement of the X-ARAPUCA's Absolute Photon Detection Efficiency for the Deep Underground Neutrino Experiment's Vertical Drift Far Detector

G. Botogoske, F. Bruni, E. Calvo et al. (+41 more)

The DUNE experiment will implement a photon detection system composed of X-ARAPUCA (XA) devices. These trap incoming VUV photons by internal reflection in a wavelength shifter light guide to be collected onto silicon photomultiplier arrays, sensitive to visible light. In the baseline design, dichroic filters are used to prevent photons from escaping. The configuration proposed for DUNE's Vertical Drift (VD) module has been characterised in liquid argon for the first time using dedicated cryogenic setups developed at CIEMAT and INFN Naples. Additionally, several alternative configurations, based on the design optimisation studies of an R&D campaign, have been evaluated. The results show an efficiency of up to 4.5$\pm$4~% at 4.5~V overvoltage, representing a significant improvement over previous XA implementations. Most notably, configurations without dichroic filters show an improvement of up to 18~%, attributed to transmittance losses in the dichroic filters.
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All authors G. Botogoske, F. Bruni, E. Calvo, R. Calabrese, N. Canci, A. Canto, C.M. Cattadori, A. Cervera Villanueva, S. Coleman, J.I. Crespo-Anadón, C. Cuesta, F. Di Capua, N. Durand, G. Fiorillo, F. Galizzi, I. Gil-Botella, C. Gotti, G. Grauso, J. Jablonski, A.A. Machado, S. Manthey Corchado, J. Martín-Albo, G. Matteucci, L. Meazza, A.P. Mendoça, A. Minotti, D. Navas-Nicolás, L. Pagliuso, C. Palomares, L. Pérez-Molina, V. Pimentel, I. López de Rego, Z. Rautio, J. Romeo-Araujo, D. Rudik, E. Segreto, Y. Suvorov, M. Sturdivant, F. Terranova, J. Ureña, A. Verdugo de Osa, D. Warner, R. Wilson, K. Zhu

Plasma Physics

Non-invasive 2D spatial measurements of electric fields within a plasma sheath

Mykhailo Vorobiov, Rob Behary, Luke Payne et al. (+10 more)

We introduce an all-optical quantum-enhanced diagnostic for electric fields in low-temperature plasmas. Trace amounts of rubidium vapor, added to an argon plasma, allow us to employ spectrally narrow electric field-sensitive optical resonances via the quantum optical effect of Rydberg electromagnetically induced transparency. This non-invasive technique enables measurements of electric fields in plasma with a 1~V/cm precision and a 1.5~V/cm lower detection limit. By collecting the fluorescence from the illuminated region of interest, we reconstruct a 2D spatial profile of the electric field magnitude with $56~\mu$m resolution. As a proof-of-principle demonstration, we measured the changes in the electric field within the plasma sheath surrounding a biased Langmuir probe tip. This method holds significant potential for studying sheath structures in low-temperature plasmas.
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All authors Mykhailo Vorobiov, Rob Behary, Luke Payne, Nicolas DeStefano, William Torg, Saskia Mordijck, Charles T. Fancher, Neel Malvania, Edward Thomas Jr., Saikat Chakraborty Thakur, Seth Aubin, Eugeniy E. Mikhailov, Irina Novikova

Fluid Dynamics

Effect of cavity-induced perturbation interactions on the transitional flow after the trailing edge

Md Rashidul Islam and Yiyang Sun

We investigate the modal and non-modal linear amplification mechanisms in the flow over a subsonic open cavity and their subsequent interactions to identify optimal flow perturbations that propagate downstream the cavity and trigger flow transitions. Using both the stationary and time-varying base flows from a Direct Numerical Simulation of a cavity flow at Mach 0.6, we employ classical and harmonic resolvent analyses to explain the role of the cavity-generated perturbations in destabilizing the flow downstream. Our analysis of perturbation amplification about the mean flow identifies structures that resemble Tollmien-Schlichting (T-S) waves at the Rossiter frequency in the attached boundary layer region after the cavity. A low-frequency centrifugal instability dominates inside the cavity. The mean flow also amplifies stationary streaks via a lift-up mechanism that extends throughout the boundary layer region downstream of the cavity. The harmonic resolvent analysis (HRA) reveals the amplification of additional perturbations by the unsteady Rossiter base flow. By restricting the input and output at the same frequency in the HRA, we find the amplification of the stationary perturbation to be the most dominant 3D instability mechanism. This amplification is driven by the interaction of the 3D streaks with the unsteady Rossiter base flow, which generates internal forcing in the form of oblique T-S waves, thereby further amplifying the streaks. The interaction between the centrifugal perturbation and the unsteady flow also generates streamwise elongated structures in the boundary layer region after the cavity. Together, the centrifugal-Rossiter and streak-Rossiter interactions synergistically amplify perturbations downstream of the cavity.
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Instrumentation and Detectors

High frame rate RIXS spectroscopy using a JUNGFRAU detector with an iLGAD sensor

Nuno Duarte, Loïc Le Guyader, Viktoria Hinger et al. (+17 more)

Resonant inelastic X-ray scattering (RIXS) is a powerful photon-in, photon-out spectroscopy technique for probing electronic, magnetic, and lattice excitations in matter. Time-resolved RIXS extends this capability through a stroboscopic optical pump-probe scheme to characterize the time evolution of the photoexcitation and subsequent relaxation dynamics of a sample. This technique is, however, extremely photon-hungry, requiring high-repetition-rate and intense X-ray facilities. The Heisenberg RIXS (hRIXS) spectrometer at the Spectroscopy and Coherent Scattering (SCS) instrument of the European X-ray Free-Electron Laser (EuXFEL) is designed to exploit high-repetition-rates, while maintaining optimal time and energy resolution. In this work, we demonstrate the successful deployment of a JUNGFRAU detector equipped with an inverse Low Gain Avalanche Diode (iLGAD) sensor for time-resolved RIXS studies in the soft X-ray range, using the hRIXS spectrometer. A spatial resolution of $19.71 \pm 0.7~\mu\mathrm{m}$ and a resolving power exceeding 10,000 were achieved at an unprecedented frame rate of 47 kHz. Intra-train resolved data measured with a high FEL peak fluence of $1.8~\mathrm{mJ/cm^{2}}$ for a 928.5 eV ph photon energy and 1.1 MHz repetition rate from cupric oxide (CuO) revealed a decrease in the emitted signal by ~10% over a time interval of $340~\mu\mathrm{s}$, indicating FEL-induced effects that require monitoring when conducting high-repetition-rate experiments. These results establish the JUNGFRAU-iLGAD as a promising detector to harvest the full potential of the hRIXS spectrometer, and validate its suitability for soft X-ray applications.
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All authors Nuno Duarte, Loïc Le Guyader, Viktoria Hinger, Marco Ramilli, Justine Schlappa, Robert Carley, Maria Carulla, Yi-Ping Chang, Devesh Chopra, Natalia Gerasimova, Michael Grimes, Aldo Mozzanica, Sergii Parchenko, Le Phuong Hoang, Urs Staub, Jiaguo Zhang, Anna Bergamaschi, Andreas Scherz, Bernd Schmitt, Monica Turcato

Physics and Society

Climate determinism reborn

Richard S.J. Tol

Environmental determinism in the past followed from the belief that the gods bestowed political power and the best possible weather on the sponsors of early scholars. Although later discredited in academia because of the associations with racism and the lack of support for any monocausal explanation of history, environmental determinism in popular culture has morphed into the unfounded idea of catastrophic climate change. Although a handful of papers in the literature on the economic impact of climate change appear to support this concern, closer inspection reveals severe methodological and conceptual issues with the analyses. Climate policy will not dominate major economies, because politicians will pull back before it does, but small economies may be overwhelmed by the export of carbon credits.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci

Reinforcement Learning for Chemical Ordering in Alloy Nanoparticles

Jonas Elsborg, Emma L. Hovmand and Arghya Bhowmik

We approach the search for optimal element ordering in bimetallic alloy nanoparticles (NPs) as a reinforcement learning (RL) problem and have built an RL agent that learns to perform such global optimization using the geometric graph representation of the NPs. To demonstrate the effectiveness, we train an RL agent to perform composition-conserving atomic swap actions on the icosahedral nanoparticle structure. Trained once on randomized $Ag_{X}Au_{309-X}$ compositions and orderings, the agent discovers previously established ground state structure. We show that this optimization is robust to differently ordered initialisations of the same NP compositions. We also demonstrate that a trained policy can extrapolate effectively to NPs of unseen size. However, the efficacy is limited when multiple alloying elements are involved. Our results demonstrate that RL with pre-trained equivariant graph encodings can navigate combinatorial ordering spaces at the nanoparticle scale, and offer a transferable optimization strategy with the potential to generalize across composition and reduce repeated individual search cost.
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Atomic Physics · Cross-listed from quant-ph

Separation-Dependent Bell Correlations from Prepared Coherence in Dirac Wavepackets

Ju Gao and Fang Shen

We calculate separation-dependent Bell correlations for a fixed pair of Dirac electron wavepackets in a free, weakly relativistic packet model, treating the prepared joint wave as a physical wave–entity. Each station separation is sampled at the corresponding central packet arrival time. For the illustrated phase \(\chi=\pi/4\), the magnitude of the prescribed-setting Bell–CHSH response decreases and revives; optimizing the spin measurement directions retains the modulation. It occurs already at leading spin order, including for equal prepared branch weights. Interference between direct and exchanged assignments of the electron waves to the stations changes the relative weights and phases of the sampled spin amplitudes, thereby modulating the optimized response. Representative finite spatial and timing windows reduce visibility while retaining broader suppression and revival. This wave–entity account gives a quantitative, testable correlation pattern from prepared coherence, deterministic propagation, and local sampling, without postulating transmission between detectors.
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Optics

Pulsed heterodyne detection enables fiber-compatible, high-specificity Brillouin biomechanics in intact tissue and the living brain

Zixuan Du, Shuai Yao, Yun Qi et al. (+16 more)

Brillouin microscopy provides label-free, three-dimensional mechanical characterization of biological specimens, but current dispersive detection imposes two limits: the fiber background folds onto the sample spectrum, precluding single-fiber operation, and a ~250 MHz dispersion-induced instrumental broadening blurs mechanically distinct components within a focal volume. Here, we introduce pulsed heterodyne Brillouin detection (PHBD), which retrieves the spectrum electronically from temporal beat notes, overcoming both limitations. The fiber background beats outside the detection band and is rejected; elimination of dispersive broadening yields 25-MHz spectrometer resolution. Pulsed excitation reaches Brillouin-signal-shot-noise-limited detection, attaining 9.0-MHz shift precision in 3 ms at 30 mW in water with 53-fold improvement in energy efficiency over continuous-wave excitation. Through a bare 125-um fiber, PHBD resolves regional contrast along a 4-mm insertion track in the living mouse brain; in free space, it resolves distinct Brillouin components from the cell wall and adjacent cytoplasm in strongly scattering Arabidopsis root tips with epi-mode.
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All authors Zixuan Du, Shuai Yao, Yun Qi, Jinrui Zhang, Junlin You, Xiaoyang Liu, Yangxuan Liu, Yun Luo, Ting Mi, Yuan Wang, Guanyi Zhu, Fei He, Jingjing Xie, Shiqing Cai, Weibing Yang, Zhisheng Yang, Long Zhang, Weibiao Chen, Fan Yang

Applied Physics · Cross-listed from quant-ph

Skyrmionic qubits stabilized by Dzyaloshinskii-Moriya interaction as platforms for qubits and quantum gates

Doru Sticlet, Romulus Tetean and Coriolan Tiusan

Quantum computation departs from the classical paradigm of deterministic, bit-based processing by exploiting inherently quantum phenomena such as superposition and entanglement. We propose a framework for qubit realization based on skyrmionic states stabilized by the Dzyaloshinskii-Moriya interaction (DMI) in two-dimensional spin lattices. The model incorporates competing exchange interactions, perpendicular magnetic anisotropy, and Zeeman coupling, solved via exact diagonalization under periodic (PBC) and open boundary conditions (OBC). A quantum skyrmionic phase emerges for PBC within a parameter space defined by DMI, exchange, field, and anisotropy, while OBC favor classical-like, topologically protected skyrmions. Quantum logic gates (Pauli X, Y, Z, Hadamard) are implemented on both skyrmion types. Energy density and entanglement entropy analyses reveal that quantum skyrmions suffer from DMI-driven decoherence and reduced gate fidelity, whereas classical-like skyrmions maintain stability. Exact simulations of qubit dynamics, including drive effects and Lindblad decoherence, demonstrate tunable anharmonic energy levels and coherent Bloch-sphere manipulation, making these skyrmionic states promising candidates for qubit implementation. Overall, the Dzyaloshinskii-Moriya interaction plays a dual role-stabilizing skyrmionic qubits while simultaneously inducing decoherence during gate operations.
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