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Physics Physics

physics Watch Physics

Friday 7 November

Data Analysis and Statistics · Cross-listed from q-fin.ST

From sectorial coarse graining to extreme coarse graining of S&P 500 correlation matrices

Manan Vyas, M. Mijaíl Martínez-Ramos, Parisa Majari et al. (+1 more)

Starting from the Pearson Correlation Matrix of stock returns and from the desire to obtain a reduced number of parameters relevant for the dynamics of a financial market, we propose to take the idea of a sectorial matrix, which would have a large number of parameters, to the reduced picture of a real symmetric $2 \times 2$ matrix, extreme case, that still conserves the desirable feature that the average correlation can be one of the parameters. This is achieved by averaging the correlation matrix over blocks created by choosing two subsets of stocks for rows and columns and averaging over each of the resulting blocks. Averaging over these blocks, we retain the average of the correlation matrix. We shall use a random selection for two equal block sizes as well as two specific, hopefully relevant, ones that do not produce equal block sizes. The results show that one of the non-random choices has somewhat different properties, whose meaning will have to be analyzed from an economy point of view.
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All authors Manan Vyas, M. Mijaíl Martínez-Ramos, Parisa Majari, Thomas H. Seligman

Instrumentation and Detectors

Development and characterization of MPGD-based transition radiation detectors

Lauren Kasper, Alexander Austregesilo, Fernando Barbosa et al. (+8 more)

Transition Radiation Detectors (TRDs) are useful for electron identification and hadron suppression in high energy nuclear and particle physics experiments. Conventional wire-chamber TRDs face operational limitations due to space charge effects, motivating the replacement of the amplification stage with MicroPattern Gaseous Detectors (MPGDs). This work explores different MPGD technologies - Gas Electron Multiplier (GEM), Micro-Mesh Gaseous Structure (Micromegas), and Resistive Micro-Well ($\mu$RWELL) - as alternative TRD amplification stages. We report on the design, construction, and in-beam characterization of multiple MPGD-based TRD prototypes exposed to 3-20 GeV mixed electron-hadron beams at the Fermilab Test Beam Facility and at the CERN SPS H8 beamline. Each detector consisted of a multi-layered radiator, an approximately 2 cm deep drift region, an MPGD amplification stage optimized for X-ray transition radiation detection in a Xe:CO$_{2}$ (90:10) gas mixture, and a two-dimensional readout. The GEM-based TRD prototype achieved a pion suppression factor of about 8 at 90% electron efficiency, while the Micromegas-based prototype - with an added GEM preamplification layer - demonstrated improved operational stability and clear TR photon discrimination. The $\mu$RWELL prototype achieved stable operation but limited signal gain. Geant4-based studies confirmed the observed trends and highlighted the sensitivity of the TR yield to cathode material and radiator configuration. These studies represent the first in-beam measurements of Micromegas- and $\mu$RWELL-based TRDs, along with discussion of the performance capabilities of a triple-GEM-TRD. The results demonstrate the feasibility of MPGDs as scalable, high-rate amplification structures for next-generation TRD applications.
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All authors Lauren Kasper, Alexander Austregesilo, Fernando Barbosa, Cody Dickover, Sergey Furletov, Yulia Furletova, Kondo Gnanvo, Senta Vicki Greene, Lubomir Pentchev, Sourav Tarafdar, Julia Velkovska

Computational Physics · Cross-listed from stat.ML

Self-adaptive weighting and sampling for physics-informed neural networks

Wenqian Chen, Amanda Howard and Panos Stinis

Physics-informed deep learning has emerged as a promising framework for solving partial differential equations (PDEs). Nevertheless, training these models on complex problems remains challenging, often leading to limited accuracy and efficiency. In this work, we introduce a hybrid adaptive sampling and weighting method to enhance the performance of physics-informed neural networks (PINNs). The adaptive sampling component identifies training points in regions where the solution exhibits rapid variation, while the adaptive weighting component balances the convergence rate across training points. Numerical experiments show that applying only adaptive sampling or only adaptive weighting is insufficient to consistently achieve accurate predictions, particularly when training points are scarce. Since each method emphasizes different aspects of the solution, their effectiveness is problem dependent. By combining both strategies, the proposed framework consistently improves prediction accuracy and training efficiency, offering a more robust approach for solving PDEs with PINNs.
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Instrumentation and Detectors · Cross-listed from cond-mat.mtrl-sci

An improved reliability factor for quantitative low-energy electron diffraction

Alexander M. Imre, Lutz Hammer, Ulrike Diebold et al. (+2 more)

Quantitative low-energy electron diffraction [LEED $I(V)$ or LEED $I(E)$, the evaluation of diffraction intensities $I$ as a function of the electron energy] is a versatile technique for the study of surface structures. The technique is based on optimizing the agreement between experimental and calculated intensities. Today, the most commonly used measure of agreement is Pendry's $R$ factor $R_\mathrm{P}$. While $R_\mathrm{P}$ has many advantages, it also has severe shortcomings, as it is a noisy target function for optimization and very sensitive to small offsets of the intensity. Furthermore, $R_\mathrm{P} = 0$, which is meant to imply perfect agreement between two $I(E)$ curves can also be achieved by qualitatively very different curves. We present a modified $R$ factor $R_\mathrm{S}$, which can be used as a direct replacement for $R_\mathrm{P}$, but avoids these shortcomings. We also demonstrate that $R_\mathrm{S}$ is as good as $R_\mathrm{P}$ or better in steering the optimization to the correct result in the case of imperfections of the experimental data, while another common $R$ factor, $R_\mathrm{ZJ}$ (suggested by Zanazzi and Jona) is worse in this respect.
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All authors Alexander M. Imre, Lutz Hammer, Ulrike Diebold, Michele Riva, Michael Schmid

Optics

Galvanometer-scanning transient phase microscopy with balanced detection and arbitrary pump polarization

Cameron N. Coleal, Randy A. Bartels and Jesse W. Wilson

Transient absorption microscopy measures excited-state kinetics based on the imaginary part of the pump-induced perturbation to the complex refractive index, i.e. $\Im \{\Delta\mathcal N\}$, with applications in both materials and biomedical sciences. Its complement, transient phase microscopy, enabled by stable inline birefringent interferometry, measures the real part $\Re\{\Delta \mathcal N\}$. The ability to switch between absorption and phase measurements may yield a stronger signal, depending on the sample and probe wavelength. To date, however, transient phase has not been coupled with galvanometer scanners, thus limiting it to materials science applications and non-imaging spectroscopy. Here, we extend transient phase microscopy to operate in a galvanometer-scanning microscope with balanced detection, comparing amplitude and phase measurements in graphene (in which amplitude detection has the advantage), hemoglobin and red blood cells (in which phase detection has the advantage). We examine the impacts and limitations introduced by galvanometer scanning, in addition to relocation of the pump-probe combining dichroic to permit arbitrary polarization of the pump.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci

Point Defects Limited Carrier Mobility in Janus MoSSe monolayer

Nguyen Tran Gia Bao, Ton Nu Quynh Trang, Phan Bach Thang et al. (+3 more)

Point defects, often formed during the growth of Janus MoSSe, act as built-in scatterers and affect carrier transport in electronic devices based on Janus MoSSe. In this study, we employ first-principles calculations to investigate the impact of common defects, such as sulfur vacancies, selenium vacancies, and chalcogen substitutions, on electron transport, and compare their influence with that of mobility limited by phonons. Here, we define the saturation defect concentration ($C_{\mathrm{sat}}$) as the highest defect density that still allows the total mobility to remain within 90% of the phonon-limited value, providing a direct measure of how many defects a device can tolerate. Based on $C_{\mathrm{sat}}$, we find a clear ranking of defect impact: selenium substituting for sulfur is relatively tolerant, with $C_{\mathrm{sat}}\approx2.07\times10^{-4}$, while selenium vacancies are the most sensitive, with $C_{\mathrm{sat}}\approx3.65\times10^{-5}$. Our $C_{\mathrm{sat}}$ benchmarks and defect hierarchy provide quantitative, materials-specific design rules that can guide the fabrication of high-mobility field-effect transistors, electronic devices, and sensors based on Janus MoSSe.
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All authors Nguyen Tran Gia Bao, Ton Nu Quynh Trang, Phan Bach Thang, Nam Thoai, Vu Thi Hanh Thu, Nguyen Tuan Hung

Atmospheric and Oceanic Physics

A Satellite Remote Sensing and Doppler LiDAR-based Framework for Evaluating Mesoscale Flows Driven by Surface Heterogeneity

Tyler Waterman, Peter Germ, Marc Calaf et al. (+2 more)

Surface heterogeneity, particularly complex patterns of surface heating, significantly influences mesoscale atmospheric flows, yet observational constraints and modeling limitations have hindered comprehensive understanding and model parameterization. This study introduces a framework combining satellite remote sensing and Doppler LiDAR to observationally evaluate heterogeneity-driven mesoscale flows in the atmospheric boundary layer. We quantify surface heterogeneity using metrics derived from GOES land surface temperature fields, and assess atmospheric impact through the Dispersive Kinetic Energy (DKE) calculated from a network of Doppler LiDAR profiles at the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site. Results demonstrate that DKE and its ratio to the Mean Kinetic Energy (MKE) serve as effective indicators of heterogeneity driven flows, including breezes and circulations. The DKE and DKE ratio are correlated with metrics for surface heterogeneity, including the spatial correlation lengthscale, the spatial standard deviation, and the orientation of the surface heating gradient relative to the wind. The correlation becomes stronger when other flows that would affect DKE, including deep convection, low level jets, and storm fronts, are accounted for. Large Eddy Simulations contextualize the findings and validate the metric's behavior, showing general agreement with expectations from prior literature. Simulations also illustrate the sensitivity to configuration of LiDAR networks using virtual LiDAR sites, indicating that even smaller networks can be used effectively. This approach offers a scalable, observationally grounded method to explore heterogeneity-driven flows, advancing understanding of land-atmosphere interactions as well as efforts to parameterize these dynamics in climate and weather prediction models.
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All authors Tyler Waterman, Peter Germ, Marc Calaf, Eric Pardyjak, Nathaniel Chaney

Fluid Dynamics

Interscale energy transfer in turbulent channels

Joy Chen and Ricardo Garcia-Mayoral

We investigate the energy cascade in wall-bounded turbulence by analysing the interscale transfer between streamwise and spanwise length scales in periodic channels. This transfer originates from the nonlinear interactions in the advective term of the Navier-Stokes equations, which satisfy the classical triadic compatibility relations. Each triadic interaction is examined individually, and its corresponding nonlinear momentum and energy transfer are mapped to assess its relative importance in sustaining turbulence. Motivated by the anisotropy of the flow, we interpret each contribution $\partial_i(u_i u_j)$ to the advection term as carrying distinct physical information, and therefore analyse them separately. Time-averaged maps of the energy transfer across all length scales and wall-normal positions for a channel flow at $Re_\tau \approx 180$ are used to explore the mechanisms underlying the cascade process. As a proof of concept, reduced-order simulations are performed by retaining only the interactions identified as responsible for significant energy transfer based on our framework. Turbulent dynamics are successfully reproduced when 30% or more of the total interactions are included, while noticeable deviations emerge in the near-wall region when this proportion is further reduced.
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Space Physics

Quasi-constant time gap in multiple rings of elves

The Pierre Auger Collaboration: A. Abdul Halim, P. Abreu, M. Aglietta et al. (+358 more)

We present evidence that the time delay between the multiple rings of elves is not caused by the ground reflection of the electromagnetic pulse produced by intracloud lightning. To investigate temporal differences of multi-elves, we analyzed data from four storms occurring at various times and distances from the Pierre Auger Observatory in Malargüe, Argentina. The Auger fluorescence detector's high temporal resolution of 100 ns enabled the frequent observation of multi-elves, accounting for approximately 23% of the events. By examining the traces of 70 double and 24 triple elves, we demonstrate that the time delay between the rings remains relatively constant regardless of the arc distance to the lightning. These results deviate from the trend expected from the electromagnetic pulse (EMP) ground reflection model, which predicts a decreasing time delay with increasing arc distance from an intracloud lightning at a given height. The first emission ring is due to a direct path of the EMP to the ionosphere, with the reflected EMP creating the second ring. Simulations conducted with this model demonstrate that short energetic in-cloud pulses can generate four-peak elves, and a temporal resolution of at least 25 $\mu$s is required to separate them. Therefore, temporal resolution is crucial in the study of multi-elves. Our observations in the Córdoba province, central Argentina, indicate that the current understanding of the mechanism generating these phenomena may be incomplete, and further studies are needed to assess whether multi-elves are more likely related to the waveform shape of the lightning than to its altitude.
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All authors The Pierre Auger Collaboration: A. Abdul Halim, P. Abreu, M. Aglietta, I. Allekotte, K. Almeida Cheminant, A. Almela, R. Aloisio, J. Alvarez-Muñiz, A. Ambrosone, J. Ammerman Yebra, G.A. Anastasi, L. Anchordoqui, B. Andrada, L. Andrade Dourado, S. Andringa, L. Apollonio, C. Aramo, E. Arnone, J.C. Arteaga Velázquez, P. Assis, G. Avila, E. Avocone, A. Bakalova, F. Barbato, A. Bartz Mocellin, J.A. Bellido, C. Berat, M.E. Bertaina, M. Bianciotto, P.L. Biermann, V. Binet, K. Bismark, T. Bister, J. Biteau, J. Blazek, J. Blümer, M. Boháčová, D. Boncioli, C. Bonifazi, L. Bonneau Arbeletche, N. Borodai, J. Brack, P.G. Brichetto Orchera, F.L. Briechle, A. Bueno, S. Buitink, M. Buscemi, M. Büsken, A. Bwembya, K.S. Caballero-Mora, S. Cabana-Freire, L. Caccianiga, F. Campuzano, J. Caraça-Valente, R. Caruso, A. Castellina, F. Catalani, G. Cataldi, L. Cazon, M. Cerda, B. Čermáková, A. Cermenati, J.A. Chinellato, J. Chudoba, L. Chytka, R.W. Clay, A.C. Cobos Cerutti, R. Colalillo, R. Conceição, A. Condorelli, G. Consolati, M. Conte, F. Convenga, D. Correia dos Santos, P.J. Costa, C.E. Covault, M. Cristinziani, C.S. Cruz Sanchez, S. Dasso, K. Daumiller, B.R. Dawson, R.M. de Almeida, E.-T. de Boone, B. de Errico, J. de Jesús, S.J. de Jong, J.R.T. de Mello Neto, I. De Mitri, J. de Oliveira, D. de Oliveira Franco, F. de Palma, V. de Souza, E. De Vito, A. Del Popolo, O. Deligny, N. Denner, L. Deval, A. di Matteo, C. Dobrigkeit, J.C. D'Olivo, L.M. Domingues Mendes, Q. Dorosti, J.C. dos Anjos, R.C. dos Anjos, J. Ebr, F. Ellwanger, M. Emam, R. Engel, I. Epicoco, M. Erdmann, A. Etchegoyen, C. Evoli, H. Falcke, G. Farrar, A.C. Fauth, T. Fehler, F. Feldbusch, A. Fernandes, B. Fick, J.M. Figueira, P. Filip, A. Filipčič, T. Fitoussi, B. Flaggs, T. Fodran, M. Freitas, T. Fujii, A. Fuster, C. Galea, B. García, C. Gaudu, P.L. Ghia, U. Giaccari, F. Gobbi, F. Gollan, G. Golup, M. Gómez Berisso, P.F. Gómez Vitale, J.P. Gongora, J.M. González, N. González, D. Góra, A. Gorgi, M. Gottowik, F. Guarino, G.P. Guedes, E. Guido, L. Gülzow, S. Hahn, P. Hamal, M.R. Hampel, P. Hansen, V.M. Harvey, A. Haungs, T. Hebbeker, C. Hojvat, J.R. Hörandel, P. Horvath, M. Hrabovský, T. Huege, A. Insolia, P.G. Isar, P. Janecek, V. Jilek, K.-H. Kampert, B. Keilhauer, A. Khakurdikar, V.V. Kizakke Covilakam, H.O. Klages, M. Kleifges, J. Köhler, F. Krieger, M. Kubatova, N. Kunka, B.L. Lago, N. Langner, M.A. Leigui de Oliveira, Y. Lema-Capeans, A. Letessier-Selvon, I. Lhenry-Yvon, L. Lopes, J.P. Lundquist, A. Machado Payeras, M. Mallamaci, D. Mandat, B.C. Manning, P. Mantsch, F.M. Mariani, A.G. Mariazzi, I.C. Mariş, G. Marsella, D. Martello, S. Martinelli, M.A. Martins, H.-J. Mathes, J. Matthews, G. Matthiae, E. Mayotte, S. Mayotte, P.O. Mazur, G. Medina-Tanco, J. Meinert, D. Melo, A. Menshikov, C. Merx, S. Michal, M.I. Micheletti, L. Miramonti, M. Mogarkar, S. Mollerach, F. Montanet, L. Morejon, K. Mulrey, R. Mussa, W.M. Namasaka, S. Negi, L. Nellen, K. Nguyen, G. Nicora, M. Niechciol, D. Nitz, D. Nosek, A. Novikov, V. Novotny, L. Nožka, A. Nucita, L.A. Núñez, J. Ochoa, C. Oliveira, L. Östman, M. Palatka, J. Pallotta, S. Panja, G. Parente, T. Paulsen, J. Pawlowsky, M. Pech, J. Pękala, R. Pelayo, V. Pelgrims, L.A.S. Pereira, E.E. Pereira Martins, C. Pérez Bertolli, L. Perrone, S. Petrera, C. Petrucci, T. Pierog, M. Pimenta, M. Platino, B. Pont, M. Pourmohammad Shahvar, P. Privitera, M. Prouza, K. Pytel, S. Querchfeld, J. Rautenberg, D. Ravignani, J.V. Reginatto Akim, A. Reuzki, J. Ridky, F. Riehn, M. Risse, V. Rizi, E. Rodriguez, G. Rodriguez Fernandez, J. Rodriguez Rojo, M.J. Roncoroni, S. Rossoni, M. Roth, E. Roulet, A.C. Rovero, A. Saftoiu, M. Saharan, F. Salamida, H. Salazar, G. Salina, P. Sampathkumar, N. San Martin, J.D. Sanabria Gomez, F. Sánchez, E.M. Santos, E. Santos, F. Sarazin, R. Sarmento, R. Sato, P. Savina, V. Scherini, H. Schieler, M. Schimassek, M. Schimp, D. Schmidt, O. Scholten, H. Schoorlemmer, P. Schovánek, F.G. Schröder, J. Schulte, T. Schulz, S.J. Sciutto, M. Scornavacche, A. Sedoski, A. Segreto, S. Sehgal, S.U. Shivashankara, G. Sigl, K. Simkova, F. Simon, R. Šmída, P. Sommers, R. Squartini, M. Stadelmaier, S. Stanič, J. Stasielak, P. Stassi, S. Strähnz, M. Straub, T. Suomijärvi, A.D. Supanitsky, Z. Svozilikova, Z. Szadkowski, F. Tairli, A. Tapia, C. Taricco, C. Timmermans, O. Tkachenko, P. Tobiska, C.J. Todero Peixoto, B. Tomé, A. Travaini, P. Travnicek, M. Tueros, M. Unger, R. Uzeiroska, L. Vaclavek, M. Vacula, I. Vaiman, J.F. Valdés Galicia, L. Valore, E. Varela, V. Vašíčková, A. Vásquez-Ramírez, D. Veberič, I.D. Vergara Quispe, S. Verpoest, V. Verzi, J. Vicha, J. Vink, S. Vorobiov, J.B. Vuta, C. Watanabe, A.A. Watson, A. Weindl, M. Weitz, L. Wiencke, H. Wilczyński, D. Wittkowski, B. Wundheiler, B. Yue, A. Yushkov, E. Zas, D. Zavrtanik, M. Zavrtanik

Atomic Physics

Sagnac Tractor Atom Interferometer on Photonic Integrated Circuit

Lefeng Zhou, Anne Graf and Georg Raithel

We study the theory of, and propose an experimental design for, a Sagnac tractor atom interferometer based on a photonic integrated circuit (PIC). The atoms are trapped in counter-rotating azimuthal optical lattices, formed by interfering evanescent fields of laser modes injected into circular PIC waveguides. We develop quantum models for the radial and azimuthal dynamics of the interfering atoms in adiabatic frames, which provide computational efficiency. The theory is applied to an exemplary PIC, for which we first compute field modes and atom trapping potentials for $^{87}$Rb. We then evaluate non-adiabaticity, fidelity, and sensitivity of the exemplary PIC.
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Chemical Physics

Bayesian learning for accurate and robust biomolecular force fields

Vojtech Kostal, Brennon L. Shanks, Pavel Jungwirth et al. (+1 more)

Molecular dynamics is a valuable tool to probe biological processes at the atomistic level - a resolution often elusive to experiments. However, the credibility of molecular models is limited by the accuracy of the underlying force field, which is often parametrized relying on ad hoc assumptions. To address this gap, we present a Bayesian framework for learning physically grounded parameters directly from ab initio molecular dynamics data. By representing both model parameters and data probabilistically, the framework yields interpretable, statistically rigorous models in which uncertainty and transferability emerge naturally from the learning process. This approach provides a transparent, data-driven foundation for developing predictive molecular models and enhances confidence in computational descriptions of biophysical systems. We demonstrate the method using 18 biologically relevant molecular fragments that capture key motifs in proteins, nucleic acids, and lipids, and, as a proof of concept, apply it to calcium binding to troponin - a central event in cardiac regulation.
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All authors Vojtech Kostal, Brennon L. Shanks, Pavel Jungwirth, Hector Martinez-Seara

Atmospheric and Oceanic Physics

Retrieving Tropical Cyclone Intensity from Climate Reanalysis using Deep Learning

Minh-Khanh Luong and Chanh Kieu

Traditional methods for improving tropical cyclone (TC) intensity from climate model outputs or projections have primarily relied on either dynamical or statistical downscaling. With recent advances in deep learning (DL) techniques, an important question is how DL can provide an alternative approach for enhancing TC intensity and structure retrieval from climate data. Using a common DL architecture based on convolutional neural networks (CNN) and a set of key environmental features relevant to TCs, we show that TC intensity and size can be effectively retrieved from climate reanalysis data without requiring super-resolution enhancement as in previous studies, even when applied to coarse-resolution climate data. This approach allows for retrieving TC intensity metrics and size that are dynamically constrained by the data, rather than estimating these quantities independently. Our results highlight that TC intensity and size are governed not only by TC internal processes but also by local environments during TC development for which DL models can learn and capture. The performance of our DL model depends on several factors such as season, the stage of TC development, or ocean basins, with root-mean-square errors ranging from $\approx$8-10 m s$^{-1}$ for the maximum 10-m wind, $\approx$10-13 hPa for minimum central pressure, and $\approx$13-21 km for the radius of the maximum wind. Although these errors are better than any direct vortex detection or statistical downscaling methods applied to the same data, their wide ranges also suggest that a 0.5$^\circ$-resolution climate data may contain limited TC information for DL models to learn from, regardless of model optimizations or architectures. Possible improvements and challenges in addressing the lack of fine-scale TC information in coarse-resolution climate reanalysis datasets are discussed.
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Instrumentation and Detectors · Cross-listed from quant-ph

Strain-engineered nanoscale spin polarization reversal in diamond nitrogen-vacancy centers

Zhixian Liu, Jiahao Sun, Ganyu Xu et al. (+7 more)

The ability to control solid-state quantum emitters is fundamental to advancing quantum technologies. The performance of these systems is fundamentally governed by their spin-dependent photodynamics, yet conventional control methods using cavities offer limited access to key non-radiative processes. Here we demonstrate that anisotropic lattice strain serves as a powerful tool for manipulating spin dynamics in solid-state systems. Under high pressure, giant shear strain gradients trigger a complete reversal of the intrinsic spin polarization, redirecting ground-state population from $|0\rangle$ to $|\pm 1\rangle$ manifold. We show that this reprogramming arises from strain-induced mixing of the NV center's excited states and dramatic alteration of intersystem crossing, which we quantify through a combination of opto-magnetic spectroscopy and a theoretical model that disentangles symmetry-preserving and symmetry-breaking strain contributions. Furthermore, the polarization reversal is spatially mapped with a transition region below 120 nm, illustrating sub-diffraction-limit control. Our work establishes strain engineering as a powerful tool for tailoring quantum emitter properties, opening avenues for programmable quantum light sources, high-density spin-based memory, and hybrid quantum photonic devices.
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All authors Zhixian Liu, Jiahao Sun, Ganyu Xu, Bo Yang, Yuhang Guo, Yu Wang, Cunliang Xin, Hongfang Zuo, Mengqi Wang, Ya Wang

Biological Physics · Cross-listed from cond-mat.stat-mech

Coarse-graining nonequilibrium diffusions with Markov chains

Ramón Nartallo-Kaluarachchi, Renaud Lambiotte and Alain Goriely

We investigate nonequilibrium steady-state dynamics in both continuous- and discrete-state stochastic processes. Our analysis focuses on planar diffusion dynamics and their coarse-grained approximations by discrete-state Markov chains. Using finite-volume approximations, we derive an approximate master equation directly from the underlying diffusion and show that this discretisation preserves key features of the nonequilibrium steady-state. In particular, we show that the entropy production rate of the approximation converges as the number of discrete states goes to the limit. These results are illustrated with analytically solvable diffusions and numerical experiments on nonlinear processes, demonstrating how this approach can be used to explore the dependence of the entropy production rate on model parameters. Finally, we address the problem of inferring discrete-state Markov models from continuous stochastic trajectories. We show that discrete-state models significantly underestimate the true entropy production rate. However, we also show that they can provide tests to determine if a stationary planar diffusion is out of equilibrium. This property is illustrated with both simulated data and empirical trajectories from schooling fish.
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Applied Physics · Cross-listed from cs.LG

Diffusion-Based Electromagnetic Inverse Design of Scattering Structured Media

Mikhail Tsukerman, Konstantin Grotov and Pavel Ginzburg

We present a conditional diffusion model for electromagnetic inverse design that generates structured media geometries directly from target differential scattering cross-section profiles, bypassing expensive iterative optimization. Our 1D U-Net architecture with Feature-wise Linear Modulation learns to map desired angular scattering patterns to 2x2 dielectric sphere structure, naturally handling the non-uniqueness of inverse problems by sampling diverse valid designs. Trained on 11,000 simulated metasurfaces, the model achieves median MPE below 19% on unseen targets (best: 1.39%), outperforming CMA-ES evolutionary optimization while reducing design time from hours to seconds. These results demonstrate that employing diffusion models is promising for advancing electromagnetic inverse design research, potentially enabling rapid exploration of complex metasurface architectures and accelerating the development of next-generation photonic and wireless communication systems. The code is publicly available at https://github.com/mikzuker/inverse_design_metasurface_generation.
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Fluid Dynamics

When is a sloshing vortex an analogue black hole bomb?

Sam Patrick, Leonardo Solidoro, Maurício Richartz et al. (+4 more)

Draining vortices provide a powerful platform for simulating black hole phenomena in tabletop experiments. In realistic fluid systems confined within a finite container, low-frequency waves amplified by the vortex are reflected at the walls, rendering the system unstable. This process, known in the gravitational context as the black hole bomb, manifests as a sloshing motion of the free surface. The analogy, however, becomes more nuanced when a realistic vortex core with a non-singular vorticity distribution is considered. We investigate this by analysing a non-draining Rankine vortex in the shallow-water and inviscid limits. At low circulation, the sloshing corresponds to an instability of the vorticity field, whereas at high circulation where fluid is expelled from the vortex core, the destabilising mechanism coincides with that of the black hole bomb. Our variational framework distinguishes the energetic contributions of vorticity and irrotational perturbations, offering new insight into the rotating-polygons instability reported by, e.g. Jansson et al. (2006). From the analogue-gravity perspective, we identify hollow core vortices as an optimal regime for exploring black-hole-like instabilities in fluids.
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All authors Sam Patrick, Leonardo Solidoro, Maurício Richartz, Pietro Smaniotto, Patrik Švančara, Silke Weinfurtner, Ruth Gregory

Instrumentation and Detectors

Modelling the Performance of Tritium Process Monitors from First Principles

Nicolas J. Sovare and Walter T. Shmayda

Ionization chamber-based, in-line tritium process monitors play an important part in determining the behavior of a tritium system. The one-liter detection volume monitor has been characterized well through experiment and to respond linearly to tritium concentrations for the range of $1 {\mu}Ci/m^3$ to $1 Ci/m^3$. Additionally, it has been shown to behave nonlinearly for low voltage on the central anode and low pressure of the carrier gas. A computational model was developed from first principles that successfully describes the behavior of the one-liter monitor for each of these regimes. Predictions from the model are compared to previously-collected experimental data in order to determine validity and tune the model. The model will be expanded to incorporate additional detector geometries and designs in the future.
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Chemical Physics

Fine-Tuning Unifies Foundational Machine-learned Interatomic Potential Architectures at ab initio Accuracy

Jonas Hänseroth, Aaron Flötotto, Muhammad Nawaz Qaisrani et al. (+1 more)

This work demonstrates that fine-tuning transforms foundational machine-learned interatomic potentials (MLIPs) to achieve consistent, near-ab initio accuracy across diverse architectures. Benchmarking five leading MLIP frameworks (MACE, GRACE, SevenNet, MatterSim, and ORB) across seven chemically diverse compounds reveals that fine-tuning universally enhances force predictions by factors of 5-15 and improves energy accuracy by 2-4 orders of magnitude. The investigated models span both equivariant and invariant, as well as conservative and non-conservative, architectures. While general-purpose foundation models are robust, they exhibit architecture-dependent deviations from ab initio reference data; fine-tuning eliminates these discrepancies, enabling quantitatively accurate predictions of atomistic and structural properties. Using datasets constructed from equidistantly sampled frames of short ab initio molecular dynamics trajectories, fine-tuning reduces force errors by an order of magnitude and harmonizes performance across all architectures. These findings establish fine-tuning as a universal route to achieving system-specific predictive accuracy while preserving the computational efficiency of MLIPs. To promote widespread adoption, we introduce the aMACEing Toolkit, which provides a unified and reproducible interface for fine-tuning workflows across multiple MLIP frameworks.
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All authors Jonas Hänseroth, Aaron Flötotto, Muhammad Nawaz Qaisrani, Christian Dreßler

Instrumentation and Detectors

$^{42}$Ar Production and Injection to a Liquid Argon Environment for Background Mitigation Studies

Mario Schwarz, Christoph Vogl, Niko N. P. N. Lay et al. (+6 more)

Atmosphere-sourced argon contains traces of $^{42}$Ar, whose $\beta^-$-decaying progeny $^{42}$K represents a significant intrinsic background for rare-event experiments using liquid argon (LAr) as detector or shielding medium. Understanding and mitigating this background is crucial for current and future large-scale detectors in neutrino and dark-matter physics. To enable controlled studies of $^{42}$K behavior and suppression techniques, $^{42}$Ar was produced by irradiating natural argon with 34 MeV $^{7}$Li$^{3+}$ ions at the Maier-Leibnitz-Laboratorium tandem accelerator, using beam currents of $101 \pm 5$ nA and $140 \pm 5$ nA, yielding $476 \pm 9$ Bq within two weeks, corresponding to a production rate of $\sim 1 \times 10^{6}$ atoms$\,$s$^{-1}$. The activated argon was injected into the one-ton SCARF cryostat, where two HPGe detectors monitored the subsequent $^{42}$K activity build-up. A time-dependent model describing $^{42}$Ar mixing and $^{42}$K equilibration in LAr yielded characteristic mixing time constants between one and two days. The established production and injection capability provides a reproducible platform for high-statistics $^{42}$K background studies, essential for developing and validating suppression strategies for next-generation LAr-based rare-event experiments such as LEGEND-1000.
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All authors Mario Schwarz, Christoph Vogl, Niko N. P. N. Lay, Tommaso Comellato, Gunther Korschinek, Moritz Neuberger, Oskar Moras, Patrick Krause, Stefan Schönert

Chemical Physics · Cross-listed from cond-mat.other

Directional Photocurrent Generated by Quantum Interference Control

Yiming Gong, Kai Wang and Steven T. Cundiff

Although the absorption of light in a bulk homogeneous semiconductor produces photocarriers with non-zero momentum, it generally does not produce a current in the absence of an applied electric field because equal amounts of carriers with opposite momentum are injected. The interference of absorption processes, for example, between one-photon and two-photon absorption, can produce a current because constructive interference for carriers with one momentum can correspond to destructive interference for carriers with the opposite momentum. We show that for the interference between two-photon and three-photon absorption, the current has a narrower angular spread, i.e., a “beam” of electrons in a specified direction is produced in the semiconductor.
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Applied Physics

High Thermoelectric Cooling Performance of Junction Thermoelectric Transistors

Chen Tang, Bohang Nan, Xiaodong Liu et al. (+1 more)

To achieve high performance thermoelectric materials and devices, thermoelectric transistors, which integrate thermoelectric effects with transistor technology, represent a promising approach. Here p type Bi0.5Sb1.5Te3 and n type Bi2Te2.97Se0.03 are used as the constituent materials for an NPN transistor. By applying forward bias to the emitter and reverse bias to the collector to form a common-base triode configuration, the thermoelectric effect, transistor effect, and interfacial effects within the NPN heterostructure are coupled. This NPN heterostructure induces temperature increase (heat release) at the forward biased end and temperature decrease (heat absorption) at the reverse biased end. Therefore, this device becomes a new type of thermoelectric transistor cooler. Furthermore, a DC equivalent circuit method is introduced to analyze the cooling performance of the thermoelectric transistor cooler. The results show that when the emitter voltage of the NPN thermoelectric transistor cooler is 0.01925V, the collector voltage is 0.2124V, the corresponding base region width is 0.17nm, the maximum temperature difference of 242.89K can be obtained. Even if the base region width is limited to a level of 10 nanometers, for example when the base region width is 12.78nm, the maximum temperature differenced can still reach 174.15K. The research results above indicate that the thermoelectric transistor, which synergistically combines the thermoelectric effect with transistor technology, can effectively enhance the maximum temperature difference that typical thermoelectric cooling can achieve.
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All authors Chen Tang, Bohang Nan, Xiaodong Liu, Guiying Xu

Optics · Cross-listed from astro-ph.IM

Optimizing broadband microwave absorbers for applications in the 70-200 GHz range

Gaganpreet Singh, Rustam Balafendiev, Mahesh Singh Bist et al. (+4 more)

We present results of an extensive suite of numerical simulations that probe square-tiled microwave absorber performance as a function of material properties, frequency, geometry, and unit cell size. The work, which probes both specular reflection and total absorption, highlights the critical importance of the absorber scale size relative to the incidence wavelength while suggesting that material properties have a comparatively weaker impact on overall performance. We show that some absorber designs can achieve 99.5-99.9% frequency-averaged absorption across the 70 to 200 GHz range for normal incidence and that low specular reflectance does not necessarily guarantee optimal absorption performance. Our results indicate that exponential, Klopfenstein, and linear impedance tapers provide comparable performance as long as a unit cell size of 1 to 4 mm is chosen. Simulation results are validated against measurements of specular reflectance.
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All authors Gaganpreet Singh, Rustam Balafendiev, Mahesh Singh Bist, Thomas J.L.J. Gascard, Gagandeep Kaur, Vid Primožič, Jon E. Gudmundsson

Chemical Physics

Spin covalent chemistry of carbon

E.F. Sheka

This review presents the covalent chemistry of carbon within the spin-radical concept of electron interaction. Using the language of valence bond trimodality, the regions of classical spinless covalence and its spin counterpart are defined. Carbon is the only element exhibiting spin covalent chemistry. Classical covalent chemistry of carbon concerns molecular substances whose valence bond structure includes segregate or chained single sp3C-C bonds. Substances with double sp2C-C and triple sp1C-C bonds are the subject of spin covalent chemistry of carbon. The mathematical apparatus of spin covalence forms the basis of algorithms governing the chemical modification of carbon substances, polymerization processes, and catalysis involving them, making it possible to supplement the empirical spin covalent chemistry of carbon with its virtual analog.
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Chemical Physics · Cross-listed from quant-ph

Open quantum-classical systems: A hybrid MASH master equation

Kasra Asnaashari and Jeremy O. Richardson

We propose a method which combines the quantum-classical mapping approach to surface hopping (MASH) with the dissipative quantum dynamics of the Lindblad master equation. Like conventional surface-hopping methods, our approach is based on classical trajectories coupled to the dynamics of a quantum subsystem. However, instead of evolving the subsystem wavefunction according to the time-dependent Schrödinger equation, we use stochastic quantum trajectories derived from secular Redfield theory. This enables the simulation of open quantum systems coupled simultaneously to Markovian quantum baths and anharmonic non-Markovian classical degrees of freedom. Applications to the spin–boson model and to the cavity-enhanced fluorescence of an electronically nonadiabatic molecule show excellent agreement with fully quantum-mechanical benchmarks.
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Computational Physics

Impact of higher-order exchange on the lifetime of skyrmions and antiskyrmions

Hendrik Schrautzer, Moritz A. Goerzen, Bjarne Beyer et al. (+3 more)

Reliable control of skyrmion lifetime is essential for realizing spintronic devices, yet the role of higher-order exchange - which can lead to skyrmion stabilization - remains largely unexplored. Here we calculate lifetimes of isolated skyrmions and antiskyrmions at transition-metal interfaces based on an atomistic spin model that includes all fourth-order exchange terms. Within harmonic transition-state theory, we evaluate both energetic and entropic contributions and find substantially enhanced lifetimes when higher-order exchange is included. The four-spin four-site interaction raises the energy barrier and lowers the curvature of the energy landscape at the collapse saddle point, increasing the pre-exponential factor. We show that skyrmions and antiskyrmions can remain thermally stable even without Dzyaloshinskii-Moriya interaction (DMI), and that tuning the four-spin term by a small amount modulates the prefactor over orders of magnitude. Our results identify higher-order exchange as a promising route to stabilize topological magnetic textures - in particular in systems lacking DMI - and to engineer their thermally activated decay.
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All authors Hendrik Schrautzer, Moritz A. Goerzen, Bjarne Beyer, Soumyajyoti Haldar, Pavel F. Bessarab, Stefan Heinze

Plasma Physics

Gigagauss magnetic fields generated via theta-pinching driven by multiple petawatt-class lasers

Huanyu Song, Zhengming Sheng, Linzheng Wang et al. (+4 more)

Extremely high axial magnetic fields above the gigagauss (GG) level are supposed to exist in neutron stars, which may be a one of the critical parameters for their internal structures and be responsible for the X and gamma-ray emission from these stars. Here we show that such ultrahigh magnetic fields can be produced by multiple petawatt-class lasers interacting with a cuboid solid target with a cylindrical microtube in the middle. It is found that the obliquely incident intense lasers at the target surfaces enable the produced hot electrons to form an azimuthal current and subsequently induce a seed magnetic field along the cylindrical axis inside the microtube as the hot electrons transport into it. This current-field configuration is similar to a theta-pinch device. When the hot electrons and energetic ions produced via target normal sheath acceleration converge towards the microtube axis, the seed magnetic field is dramatically amplified. This process continues until the magnetic pressure near the axis becomes comparable to the thermal pressure contributed both by hot electrons and energetic ions. Later on, as the plasma in the center start to be expelled outward by the magnetic pressure, an electron current ring with extremely high densities is formed, leading to a further boost of the magnetic fields to well above the GG-level. A scaling of the magnetic field strength with laser intensities, pulse durations, incident angles, and target sizes is presented and verified by numerical simulations, which demonstrates the robustness of our scheme. Our scheme is well suited for experimental realization on 100 terawatt-class to petawatt-class femtosecond or picosecond laser facilities with multiple linearly polarized laser beams.
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All authors Huanyu Song, Zhengming Sheng, Linzheng Wang, Min Chen, Suming Weng, Masakatsu Murakami, Jie Zhang

Chemical Physics

Fuzzy Neural Network Performance and Interpretability of Quantum Wavefunction Probability Predictions

Pedro H. M. Zanineli, Matheus Zaia Monteiro, Vinicius Francisco Wasques et al. (+2 more)

Predicting quantum wavefunction probability distributions is crucial for computational chemistry and materials science, yet machine learning (ML) models often face a trade-off between accuracy and interpretability. This study compares Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) in modeling quantum probability distributions for the H$_{2}^+$ ion, leveraging data generated via Physics-Informed Neural Networks (PINNs). While ANN achieved superior accuracy (R$^2$ = 0.99 vs ANFIS's 0.95 with Gaussian membership functions), it required over 50x more parameters (2,305 vs 39-45). ANFIS, however, provided unique interpretability: its Gaussian membership functions encoded spatial electron localization near proton positions ($\mu = 1.2 A$), mirroring Born probability densities, while fuzzy rules reflected quantum superposition principles. Rules prioritizing the internuclear direction revealed the system's 1D symmetry, aligning with Linear Combination of Atomic Orbitals theory–a novel data-driven perspective on orbital hybridization. Membership function variances ($\sigma$) further quantified electron delocalization trends, and peak prediction errors highlighted unresolved quantum cusps. The choice of functions critically impacted performance: Gaussian/Generalized Bell outperformed Sigmoid, with errors improving as training data increased, showing scalability. This study underscores the context-dependent value of ML: ANN for precision and ANFIS for interpretable, parameter-efficient approximations that link inputs to physical behavior. These findings advocate hybrid approaches in quantum simulations, balancing accuracy with explainability to accelerate discovery. Future work should extend ANFIS to multi-electron systems and integrate domain-specific constraints (e.g., kinetic energy terms), bridging data-driven models and fundamental physics.
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All authors Pedro H. M. Zanineli, Matheus Zaia Monteiro, Vinicius Francisco Wasques, Francielle Santo Pedro Simões, Gabriel R. Schleder

Data Analysis and Statistics · Cross-listed from gr-qc

Poissonian Analysis of Glitches Observed in the LIGO Gravitational Wave Interferometers

Giovanna Souza Rodrigues Costa, Julio Cesar Martins and Odylio Denys Aguiar

This work investigates the temporal distribution of glitches detected by LIGO, focusing on the morphological classification provided by the Gravity Spy project. Starting from the hypothesis that these events follow a Poisson process, we developed a statistical methodology to evaluate the agreement between the empirical distribution of glitches and an ideal Poisson model, using the coefficient of determination ($R^2$) as the main metric. The analysis was applied to real data from the LIGO detectors in Livingston and Hanford throughout the O3 run, as well as to synthetic datasets generated from pure Poisson distributions. The results show that while several morphologies exhibit good agreement with the proposed model, classes such as 1400Ripples, Fast Scattering, and Power Line display significant deviations ($R^2 \leq 0.6$), suggesting that their origins do not strictly follow Poissonian statistics. In some cases, a dependence on the detector or the observing run was also observed. This analysis provides a quantitative basis for distinguishing glitch classes based on their degree of "Poissonness", potentially supporting the development of more effective glitch mitigation strategies in gravitational wave detector data.
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Optics

Resonantly Pumped Tunable Tm,X:CaF2 Lasers: Effect of Buffer Ions (X = Y, La, Gd, and Lu)

Dominika Popelová, Karel Veselský, Pavel Loiko et al. (+5 more)

We report on the eye-safe laser performance of Tm3+-doped calcium fluoride crystals, modified with optically inactive "buffer" cations (Y3+, Lu3+, Gd3+, and La3+), under in-band diode-pumping at 1.68 um. In the free-running regime, the 1.5 at.% Tm, 4 at.% Y:CaF2 laser operates with a high slope efficiency of 47% with respect to absorbed pump power. By employing an MgF2 birefringent plate, the emission wavelength of this laser is continuously tuned over 242 nm (1820 - 2062 nm) highlighting its potential for broadly tunable and ultrafast oscillators. The spectroscopic properties of Tm3+ ions in CaF2 crystals with and without buffer ions are also compared.
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All authors Dominika Popelová, Karel Veselský, Pavel Loiko, Abdelmjid Benayad, Alain Braud, Patrice Camy, Jan Šulc, Helena Jelínková

Computational Physics

Structure Matters: A Scale-Resolved Numerical Operando Approach for Lithium-Sulfur Batteries

Max Okraschevski, Torben Prill, Paul Maidl et al. (+2 more)

Lithium-Sulfur batteries (LSBs) are believed to have a high potential for aerospace applications due to their high gravimetric energy density. However, despite decades of research and advances, they still suffer from poor rate capability and low power output, eventually preventing their practical implementation. One particular aspect we want to shed light on is the influence of the porous cathode structure on the rate performance during discharge. Therefore, we present a scale-resolved simulation methodology involving high-performance computing (HPC), which aims to provide structural insights into the electrochemical cell behavior that are experimentally hardly accessible even for modern operando methods. Our numerical operando approach employs scaling analysis for efficient model parametrization as well as rigorous parameter transfer between models of different dimensionality and is based on a coarse-grained continuum model. The latter is spatially discretized with a Discontinuous Galerkin (DG) method and advanced in time by an adaptive controller. The models and methods as well as HPC aspects of our toolbox will be critically discussed, finally showcasing the capabilities of our workflow to improve LSBs.
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All authors Max Okraschevski, Torben Prill, Paul Maidl, Arnulf Latz, Timo Danner