Atomic Physics
Transformation of vector modes by the Faraday effect in strong magnetic fields
Sphinx J. Svensson, Craig J.A. Millar, Danielle Pizzey et al. (+2 more)
Large Faraday rotations can be generated by circular birefringence of atomic samples in an axial
magnetic field in the vicinity of atomic resonance lines. The Faraday angle is a function of the
magnetic field strength, the optical density of the atomic sample which may be varied by changing the temperature of the atomic gas, and of course the optical detuning from the transition frequencies. More generally, magneto-optical effects in atomic samples include circular dichroism in addition to birefringence, resulting in a modification of the ellipticity as well as the polarisation
alignment. Usually such effects are investigated for homogeneous linear polarisations, but the mechanisms apply also to polarisation structures such as vector
vortices. We investigate the effect of optical activity of a rubidium vapour in the Hyperfine Paschen-Back regime, for the example of an azimuthally polarised input light beam. We show that for low atomic densities, circular birefringence dominates over dichroism, and azimuthal polarisation is rotated towards radial polarisation. The rotation angle increases with increasing optical densities. At high vapour temperatures, dichroism becomes more and more relevant, leading to intricate variations of both
alignment and ellipticity.
Read the full abstract ▾
All authors Sphinx J. Svensson, Craig J.A. Millar, Danielle Pizzey, Ifan G. Hughes, Sonja Franke-Arnold
Fluid Dynamics
Split Complex-Valued Physics-Informed Neural Networks for Forward and Inverse Nonlinear Partial Differential Equations
Biswanath Barman, Rajendra K. Ray and Debdeep Chatterjee
Physics-informed neural networks (PINNs) can solve forward and inverse PDE problems but may struggle with spectral bias and oscillatory, high-frequency, or phase-dependent solutions. We introduce a generalized split complex-valued PINN (SCV-PINN) framework with complex-valued parameters and latent representations. Split activations act separately on real and imaginary components while complex operations preserve their coupling, enabling amplitude–phase representations with practical optimization. Ablation studies evaluate split activation functions and collocation sampling strategies. Forward and inverse
benchmarks include the Burgers, Allen–Cahn, Korteweg–de Vries, nonlinear Schrödinger, Helmholtz, and Poisson equations on regular and irregular domains; Kovasznay flow ($\mathrm{Re}=20$); lid-driven cavity flow ($\mathrm{Re}=100$); the Lorenz system; and inverse Burgers and Navier–Stokes problems ($\mathrm{Re}=100$). A three-dimensional Navier–Stokes Beltrami flow further demonstrates applicability to higher-dimensional nonlinear dynamics, with a relative $L_2$ error of $4.07\times10^{-5}$. Across these tests, SCV-PINN yields high-fidelity solutions and effective parameter identification, improving on real-valued PINNs and selected variants. The results suggest that split complex-valued representations can help address spectral-bias-related difficulties in nonlinear and oscillatory physical systems.
Read the full abstract ▾
Fluid Dynamics
A Thermodynamically Consistent Manifold Model for Premixed Deflagrations & Detonations
John B. Boerchers, Laura T. Thompson, Matthew X. Yao et al. (+1 more)
Accurate modeling of compressible premixed flames, encompassing both deflagrations and detonations, remains a significant challenge for predictive Large Eddy Simulation (LES) due to the strong coupling between the thermochemical state and the local thermodynamic state. This work presents a
manifold-based turbulent combustion model that ensures a fully consistent thermodynamic state between model and flow solver through an iterative procedure. The framework reproduces critical quantities including temperature, radical species, and source term profiles, addressing limitations of existing approaches that rely on low-Mach perturbations or tabulated ZND detonations without thermodynamic consistency. Validation is performed against one-dimensional and high-fidelity RDE-like data, demonstrating that the thermodynamically consistent model consistently outperforms existing approaches across a broad range of compressible flame regimes - including both deflagration and detonation. The results highlight the importance of fully accounting for the thermodynamic state to achieve accurate predictions. By capturing both deflagrative and detonative behavior within a single framework, the model provides a unified, versatile tool for LES of high-speed reacting flows and offers a foundation for future studies of compressible reacting flows, including applications to rotating detonation engines and other supersonic combustion systems.
Read the full abstract ▾
All authors John B. Boerchers, Laura T. Thompson, Matthew X. Yao, Michael E. Mueller
Plasma Physics
Mitigation of Initial Transients in Total-f Gyrokinetic Turbulence Simulations Using Neoclassically Relaxed Distribution Function
S. Ku, R. Hager, C.S. Chang et al. (+2 more)
Total-f five-dimensional gyrokinetic simulations are essential for self-consistent studies of multiscale, multiphysics transport in the edge region of diverted tokamak
plasmas. However, conventional initialization with a local Maxwellian distribution often generates large-amplitude transients, particularly geodesic acoustic modes (GAMs). These transients are especially severe in the
plasma edge because of steep profile gradients, strong radial electric fields, and high safety factors, and they can interfere with early-time
turbulence and transport diagnostics. To address this problem, we present a new initialization scheme for the total-f XGC code that uses a relaxed particle distribution obtained from a computationally inexpensive axisymmetric simulation. Before the distribution is transferred to the full
turbulence simulation, phase-space smoothing is applied to reduce particle noise while preserving its neoclassical structure. Simulations of the Cyclone Base Case and an ASDEX Upgrade I-mode discharge show that the method reduces particle noise and substantially suppresses initialization-driven transients.
Read the full abstract ▾
All authors S. Ku, R. Hager, C.S. Chang, S.-J. Lee, A. Scheinberg
Chemical Physics
Interaction energies of H$_2$ and CO on transition-metal surfaces computed by a range-separated hybrid van der Waals density functional
Per Hyldgaard
Dissociative chemisorption (DC) of H$_2$ on the Cu(111) surface is a prototypical problem for understanding elements of heterogeneous catalysis [Science 326, 832 (2009)]. The challenge lies in modeling the reaction dynamics that in turn reflects a classical potential for atomic deformations, friction, and inelastic scattering. Here, I test the use of a set of range-separated hybrid (RSH) van der Waals density functionals (vdW-DFs) [JPCM 37, 211501 (2025)] on their ability to describe the classical barrier for dynamics in this H$_2$+Cu(111) DC problem. I furthermore document use of a variant for fast accurate predictions of the molecular quasi-particles (QPs), finding excellent performance across a set of small molecules that are often studied in catalysis. Finally, I suggest and implement a way to use that QP focus to identify what I consider a best-possible non-empirical (yet adsorbate specific) RSH vdW-DF version, denoted AHBR($\gamma^*$) for H$_2$ DC modeling, navigating what are partly conflicting requirements on the molecule and metal sides. I find that the AHBR($\gamma^*$) can determine the classical H$_2$+Cu(111) DC barrier height close to chemical accuracy. I suggest that DC modeling can test broader relevance of the physics underpinning these RSH vdW-DFs.
Read the full abstract ▾
Physics and Society · Cross-listed from cs.DL
Female participation in science in the past 125 years: An analysis of the Matilda effect over time
Felix Bittmann and Lutz Bornmann
The Matilda effect describes the systematic under-recognition of women's scientific contributions. We investigated its historical
evolution by analyzing over 220 million publications (1900-2025) from OpenAlex, inferring the gender of roughly 60 million authors. To quantify this under-recognition, we calculated the ratio between the overall share of female authors and female corresponding authors. Because corresponding authorship denotes intellectual leadership and primary academic credit, systematic exclusion from this role directly measures the Matilda effect. Our analysis reveals that overall female participation rose from approximately 10% in the 1910s to over 40% recently. For most of the 20th century, women were disproportionately excluded from corresponding authorship, confirming a historical Matilda effect. However, this trend inverted over the past two decades, indicating a global decline. Despite this overall progress, distinct disparities persist: the physical sciences and Asian countries lag behind, whereas the health sciences and Latin America approach gender parity.
Read the full abstract ▾
Optics
Analysis of the Topology of a Plasmonic Target-Skyrmion Texture
Alexander Neuhaus, Pascal Dreher, Philipp Gessler et al. (+5 more)
Topological concepts are frequently used to describe structured optical fields, including plasmonic near fields. Topological descriptions in terms of skyrmion numbers implicitly assume the compactness of the underlying
manifold. Even when skyrmion-like textures appear locally, the compactness is usually not fulfilled in extended optical fields. Here, we use photoemission electron microscopy to investigate a plasmonic nano-focus that exhibits a sequence of radially extending alternating skyrmion and antiskyrmion textures. The full spatio-temporal reconstruction of the electric field vectors and their
topology is accessible by vector polarimetry. The experiments confirm the expected oscillatory behavior of the skyrmion number and demonstrate that a global skyrmion number cannot be assigned in such non-compact fields.
Read the full abstract ▾
All authors Alexander Neuhaus, Pascal Dreher, Philipp Gessler, Bettina Frank, Timothy J. Davis, Harald Giessen, Karin Everschor-Sitte, Frank-J. Meyer zu Heringdorf
Computational Physics · Cross-listed from quant-ph
Implicit differentiation of tensor network algorithms
Lander Burgelman, Anna Francuz, Paul Brehmer et al. (+4 more)
The current leading approach to the variational optimization of projected entangled-pair states (PEPS) is based on automatic differentiation, which allows for a convenient evaluation of the energy gradient with respect to the local variational degrees of freedom. However, evaluating the energy gradient not only remains a major computational bottleneck of the optimization procedure, but also suffers from frequent numerical instabilities. In this work, we adopt recent advances in implicit differentiation techniques to address these challenges in PEPS optimization. By reformulating the core step of the gradient computation in terms of a single characteristic equation for the contraction environment, we reduce the cost of the gradient computation and improve its scaling with the problem size. By choosing a suitable parametrization of this characteristic equation based on the intrinsic
symmetries of the contraction environment, we can directly remove instabilities from the global gradient computation that would otherwise arise from the derivatives of subroutines of the contraction
algorithm. Finally, we demonstrate how this approach drastically simplifies the practical implementation of stable gradient-based PEPS optimization.
Read the full abstract ▾
All authors Lander Burgelman, Anna Francuz, Paul Brehmer, Lukas Devos, Jutho Haegeman, Frank Verstraete, Bram Vanhecke
Instrumentation and Detectors
Comparative study and optimization of SDHCAL hadronic energy reconstruction methods
Tanguy Pasquier, Gérald Grenier and Imad Laktineh
We present a detailed study of hadronic shower energy reconstruction methods for the Semi-Digital Hadronic Calorimeter (SDHCAL) within the ILD detector concept, using the Particle Flow
Algorithm (PFA) APRIL. Using samples of single $K^0_L$ and dijet ($u,d,s$) events, we compare linear, quadratic, split, and
polynomial regression-based reconstruction formulas, focusing on their impact on linearity and resolution. The study also addresses angular corrections required in the barrel region due to non-perpendicular particle incidence. Results show that while all methods achieve good overall performance, the split method and the
polynomial regression provide the best compromise across different energy regimes, offering improved resolution at low energies without compromising linearity at higher energies. For dijets, sensitivity to PFA confusion dominates the resolution at high energies. These findings highlight the potential of future improvements, notably the integration of precise timing information from the T-SDHCAL into APRIL, to further reduce confusion and enhance hadronic energy reconstruction for next-generation
lepton colliders.
Read the full abstract ▾
Plasma Physics
An asymptotic-preserving five-moment two-species plasma model coupled to an external magnetohydrodynamic solver
Magnus Deisenhofer, Aleksandr Mustonen, Simon Lautenbach et al. (+1 more)
Accurately modeling collisionless space
plasmas requires capturing small-scale kinetic effects while keeping global-scale simulations computationally tractable. Traditional multiscale approaches often rely on localized magnetohydrodynamics (MHD)-particle-in-
cell (PIC) coupling or dynamic model hierarchies. In this work, we extend an established, adaptive multi-model hierarchy spanning from fully kinetic Vlasov descriptions to fluid models by introducing an asymptotic-preserving (AP) strategy that couples a two-species, five-moment fluid description with an ideal MHD solver. This coupling is the final critical step toward enabling efficient global simulations because the kinetic-scale physics in nonideal regions is entirely handled by finer models in the hierarchy. Kinetic descriptions natively solve Maxwell's equations and thus capture fast
plasma waves, oscillations, and light waves, which are absent in the MHD dynamics. To address this difference without sacrificing computational efficiency, our AP framework seamlessly projects these fast dynamics onto the slow MHD dynamics, ensuring rigorous consistency at the model interfaces. We detail the AP two-fluid formulation, the variable-coupling interface, and its integration into external frameworks. Finally, we demonstrate the validity and robustness of the fully coupled framework, from kinetics to ideal MHD, through
magnetic reconnection simulations.
Read the full abstract ▾
All authors Magnus Deisenhofer, Aleksandr Mustonen, Simon Lautenbach, Rainer Grauer
Atmospheric and Oceanic Physics · Cross-listed from astro-ph.EP
Atmospheric evolution through outgassing and escape on young molten rocky exoplanets
Emma Postolec, Tim Lichtenberg, Harrison Nicholls et al. (+2 more)
The earliest rocky
planet atmospheres are shaped by competition between initial volatile inventories and atmospheric escape. On young magma ocean
planets, outgassing competes with atmospheric escape, controlling volatile retention and atmospheric
evolution. We investigate how atmospheric escape and replenishment via outgassing during magma ocean crystallization shape rocky
planet atmospheres. We extend a coupled interior-atmosphere model to simulate rocky
planet evolution during the magma ocean era by incorporating an energy-limited atmospheric escape module. Comparing radiative-convective and prescribed-convective atmospheres, we quantify how atmospheric energy transport affects escape. We explore a wide range of orbital separations, escape efficiencies, oxidation states, and initial volatile inventories to identify regimes where sustained magma-ocean outgassing or escape dominates. We estimate atmospheric loss and compositions for young rocky
planets around Sun-like and M-
dwarf stars over geologic timescales. Atmospheric escape shortens magma ocean lifetimes by weakening greenhouse insulation. Radiative-convective atmospheres reduce solidification timescales compared to purely convective cases. Volatile dissolution into the magma ocean interacts with escape to chemically fractionate the planetary volatile budget over time by retaining more soluble species. For Earth-mass
planets, atmospheres survive if loss rates remain moderate. Mantle redox state remains a key control on retained atmospheric composition: high oxygen fugacity (fO2) yields heavier, H2O- and CO2-rich atmospheres, while low fO2 produces light, H2- or CO-dominated atmospheres, consistent with previous studies. Orbital separation, initial volatile inventory, and
stellar type produce diverse evolutionary pathways, from bare rocky
planets to magma oceans with thick atmospheres, ranging from H2- to SO2-dominated.
Read the full abstract ▾
All authors Emma Postolec, Tim Lichtenberg, Harrison Nicholls, Laurent Soucasse, Floris van der Tak
Optics
Hybrid Symmetry Breaking for Chiral Quasi-Bound States in the Continuum
Yongtu Zou, Zhiyao Ma, Guangwei Hu et al. (+3 more)
Chiral optical modes provide a fundamental platform for
spin selective light matter interactions and underpin emerging applications ranging from
chiral emission to polarization-controlled photonic devices. They are typically achieved by tailoring specific structural asymmetries to directly induce circularly polarized radiation. Here, we introduce hybrid
symmetry breaking as a general route for generating and controlling
chiral quasi-bound states in the continuum (qBICs). By combining multiple orthogonal
symmetry perturbations, optical chirality emerges in otherwise achiral photonic structures and evolves continuously from linear to circular polarization. A parity based analysis reveals that the
chiral qBICs originate from the
symmetry-controlled
evolution of parity allowed radiative channels. We demonstrate the universality of the approach across multiple BIC platforms, achieve deterministic control of the polarization state across nearly the entire Poincare sphere, and further establish dynamic chirality reconfiguration in a fixed structure through a phase-change material. More broadly, our results demonstrate that optical chirality can emerge from
symmetry engineering, providing a general framework for the design of
chiral photonic states.
Read the full abstract ▾
All authors Yongtu Zou, Zhiyao Ma, Guangwei Hu, Haoran Ren, Stefan A. Maier, Changxu Liu
Chemical Physics · Cross-listed from astro-ph.GA
Isomer-specific excitation of formic acid in collisions with helium atoms
Karina Sogomonyan, Anzhela Veselinova-Marinova, François Lique et al. (+1 more)
An accurate estimation of the molecular abundances of isomers in the interstellar medium (ISM) is necessary to unravel the underlying chemistry and physics. After the recent detections of both isomers of formic acid ($cis-$ and $trans-$HCOOH) in dense dark cold clouds, their accurate molecular line modeling became of interest. The conditions of these environments do not necessarily follow the local thermodynamic
equilibrium, thus taking into account the competition between the radiative and collisional processes is required. This involves the knowledge of the rotational excitation data for collisions with the most abundant interstellar species \textemdash He and H$_2$. In this paper, the first potential energy surfaces (PES) for the interaction of the two rotamers of formic acid with He atoms are computed using the explicitly correlated coupled-cluster theory [CCSD(T)-F12]. The obtained PESs demonstrate qualitative similarities and high anisotropy. The global minima are found with $V=-53.0$ cm$^{-1}$ and $V=-46.0$ cm$^{-1}$ for $cis-$HCOOH and $trans-$HCOOH respectively. Collisional excitation cross sections calculated for total energies up to 100 cm$^{-1}$ demonstrate similar propensity rules for both isomers. Quantitative differences of the cross sections associated with the two rotamers are also discussed.
Read the full abstract ▾
All authors Karina Sogomonyan, Anzhela Veselinova-Marinova, François Lique, Jérôme Loreau
Atomic Physics · Cross-listed from cond-mat.quant-gas
Parallel analog quantum simulation in homogeneous quantum gases
Diego Hernández Rajkov, Alberto Terenzi, Marcia Frómeta Fernández et al. (+4 more)
Analog
quantum simulation offers a powerful way to study strongly correlated
quantum systems that are beyond the reach of classical computation. In this context, ultracold atomic gases have been demonstrated to be an exceptionally versatile and well-controlled platform for implementing various
quantum Hamiltonians. In this work, we extend this level of control to a multiplexed configuration in which distinct
quantum-simulation units are independently controlled and engineered starting from a single atomic cloud. We demonstrate multiplexed operation in two representative settings. First, by shaping box-trap potentials and separately controlling the evaporative cooling trajectories, we prepare subsystems at various temperatures across the superfluid transition of the
unitary Fermi gas. Second, we demonstrate parallel
quantum simulation of the Josephson
Hamiltonian across distinct Josephson-junction
quantum simulation units with individually tunable parameters, including local phase control to initialize the dynamics. Our scheme provides a versatile route toward systematic studies of dynamics and transport
Hamiltonians in strongly correlated ultracold matter. Moreover, it is readily extendable to a wide range of atomic species, geometries, and dimensionalities.
Read the full abstract ▾
All authors Diego Hernández Rajkov, Alberto Terenzi, Marcia Frómeta Fernández, Nicola Grani, Massimo Inguscio, Giulia Del Pace, Giacomo Roati
Optics
Spatially multiplexed concentric discrete optical vortices: Complex topological structures and unconventional rotational dynamics
Aditya Narayana Jena and Vishwa Pal
Precise control over the rotational dynamics of structured lights has become a defining objective in contemporary photonics. It plays a central role in governing the functional distribution of optical energy. Particularly, orbital angular momentum driven intensity rotation and azimuthal energy flow in
vortex beams have emerged as crucial degrees of freedom in light-matter interactions. Leveraging this foundation, we establish a discrete optical
vortex (DOV) platform comprising concentric rings of phase-locked
lasers that enable precise control over
vortex-beam rotation. By engineering the spatial distribution of topological charges (TCs) across the concentric rings of DOVs, we realize shape-invariant asymmetric
vortex beams with controllable reversal of intensity rotation, without altering the sign of constituent TCs. This result establishes a new framework for controlling energy flow in
vortex beams, beyond the conventional paradigm that links
vortex rotation solely to the sign of the TC. Such controllable rotational dynamics opens new avenues for programmable beam steering, advanced optical micromanipulation, information multiplexing, and adaptive structured-light systems.
Read the full abstract ▾
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Self-organized defect clustering and concentration-dependent vacancy diffusion in MoS$_2$
Aaron Flötotto, Benjamin Spetzler, Martin Ziegler et al. (+2 more)
Sulfur vacancy migration has a crucial impact on electronic transport and the functional behavior of MoS$_2$-based devices such as memristors and memtransistors. According to recent atomistic simulations, vacancy migration proceeds via cooperative, vacancy-assisted sulfur jumps, implying strongly correlated defect dynamics. Here, we investigate the collective behavior of sulfur-vacancy clusters in MoS$_2$ using kinetic Monte-Carlo simulations with transition rates derived from machine learning interatomic potential molecular dynamics simulations. We identify three transport regimes: At low concentrations, vacancies are immobile or confined within small clusters, whereas at high concentrations, classical diffusive transport with a constant
diffusion coefficient is observed, and vacancies aggregate into anisotropically extended clusters. A well defined intermediate regime is characterized by clusters merging into a connected, fluctuating network with a concentration-dependent
diffusion coefficient. This regime is characterized by a broad distribution of cluster sizes. The strong dependence of the vacancy
diffusion coefficient on the average defect concentration provides new insights into the origin of memristive behavior observed in MoS$_2$.
Read the full abstract ▾
All authors Aaron Flötotto, Benjamin Spetzler, Martin Ziegler, Erich Runge, Christian Dreßler
Fluid Dynamics
Harnessing Machine Learning for Hybrid Constitutive Modelling of Viscoelastic Fluid Flows in Computational Rheology
J.L. Cummings, C. Fernandes, F. Dong et al. (+2 more)
Recent advances in data-driven modelling have highlighted the potential of hybrid approaches which combine Tensor Basis Neural Networks (TBNN) with Universal Differential Equations (UDE) to discover frame-invariant, non-linear viscoelastic constitutive models. These hybrid models enable the creation of digital twins for complex viscoelastic fluids, offering direct transferability to computational fluid dynamics simulations. In this work, we introduce a reduced dimensional tensor basis formulation that enhances both the physical consistency of the learned representations with respect to the training data and the numerical stability of subsequent simulations. The UDE architecture is embedded into an open-source finite volume solver in which the constitutive response is generated dynamically at runtime based on local fluid flow conditions. Training on synthetic
datasets generated using a range of well established viscoelastic models in oscillatory shear flows alone, the performance of the resulting UDEs is evaluated under extrapolation to unseen conditions and flow-types. These include deploying the UDEs in viscometric extensional flows as well as 2D and 3D
benchmark flows, such as the 4:1 sudden contraction and cross-slot, providing a quantitative analysis of their capabilities, limitations and failure modes. The proposed reduced-basis framework enables data-efficient discovery of frame-invariant constitutive models that generalise beyond their training regime, capturing key flow features such as the onset and growth of flow-induced elastic instabilities in strong extensional flows even though trained solely on shear data. Quantitative accuracy decreases as extrapolation increases, but incorporating first normal stress difference information further improves quantitative accuracy and extends predictive fidelity to higher Deborah numbers.
Read the full abstract ▾
All authors J.L. Cummings, C. Fernandes, F. Dong, M.A. Alves, M.S.N. Oliveira
History and Philosophy of Physics
Coloring Black Holes: Epistemic and Aesthetic Choices in Astronomical Imaging
Rodrigo Ochigame, Emilie Skulberg and Jeroen van Dongen
In 2019, the first image of a black hole's shadow based on observation was released by the Event Horizon
Telescope Collaboration (EHT). This paper shows that despite the EHT's emphasis on a single image as its final result, there were countless plausible ways of rendering the data, among which researchers could not easily choose. To obtain a single image from the extremely noisy and sparse data, it was necessary to select one of multiple plausible approaches, or to average the results from different approaches, at each stage of data processing. We examine the epistemic and aesthetic choices involved at various stages, and explore what the images would have looked like if the EHT had made different choices. We suggest that the most valuable evidence produced by the EHT comes not from the single image it ultimately advertised as its central result, but from the demonstration of the limited variability that emerged from the specific choices made.
Read the full abstract ▾
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Spot Profile Analysis Low Energy Electron Diffraction of Plasma-Enhanced Chemical Vapor Deposition Grown Epitaxial Few-Layer Graphene on Sapphire
Niels Ganser, Marko A. Kriegel, Umut Kaya et al. (+6 more)
We demonstrate the use of high-resolution spot-profile analysis low-energy electron diffraction to determine the mean grain size of
plasma-enhanced chemical vapor deposition grown few-layer
graphene on sapphire (Al$_2$O$_3$). The diffraction patterns exhibit broadened
graphene spots, pronounced diffuse scattering, and azimuthally extended features, indicating finite crystallite size and rotational disorder. By analyzing the finite-size broadening of the specular (00) spot with an Airy-type diffraction profile, we determine a mean grain diameter of 3.7$\,$nm for the as-grown
graphene layer. Post-growth annealing under ultrahigh-
vacuum conditions increases the mean grain size to about 5.7$\,$nm and 6.8$\,$nm, respectively. These results establish SPA-LEED as a sensitive reciprocal-space method for quantifying the structural coherence of directly grown
graphene on insulating substrates.
Read the full abstract ▾
All authors Niels Ganser, Marko A. Kriegel, Umut Kaya, Jixi Zhang, Rodney D. L. Smith, Marika Schleberger, Wolfgang Mertin, Gerd Bacher, Michael Horn-von Hoegen
Instrumentation and Detectors
Intrinsic Spatial Position Resolution of P-type Point-Contact Germanium Detector
R.M.J. Li, S.K. Liu, S.T. Lin et al. (+8 more)
The p-type point-contact germanium detectors have emerged as the ideal detection technology for rare-event experiments such as direct dark matter searches and neutrinoless double beta decay, and have been verified to be capable of single-site spatial position resolution. Accurately characterizing the position-dependent pulse shape responses of the detector is a crucial prerequisite for deepening background understanding and achieving background reduction. Relying on an optimized cross-scanning localization method and a full-chain physical framework, this study extracted the pulse shape responses in critical regions of the CDEX detector, quantitatively evaluated its intrinsic spatial position resolution for the first time, and ultimately achieved the position tracing of real environmental backgrounds using the constructed pulse shape database. This study completely establishes a physical analysis closed-loop for spatial position resolution, providing critical theoretical and technical support for background analysis in future ton-scale arrays.
Read the full abstract ▾
All authors R.M.J. Li, S.K. Liu, S.T. Lin, Q.Y. Li, L.T. Yang, Q. Yue, Q. Wang, H.Y. Li, X.Y. Peng, H.Y. Xing, J.J. Zhu
Biological Physics · Cross-listed from nlin.AO
Stochastic ultimatum game: Spite-driven resource feedback fosters fairness
Arunava Patra, Prosanta Mandal and Sagar Chakraborty
Resource scarcity can fundamentally encourage antisocial behaviour, whereas resource abundance can promote fair behaviour. Experimental evidence indeed suggests that scarcity induces spiteful behaviour, while repeated interactions enhance
fairness. However, existing studies of game–environment feedback systems are largely confined to the
evolution of cooperation and they overlook the interplay between resources, spite, and
fairness. To address this lacuna, we develop a
stochastic ultimatum game framework in which an offerer and an accepter repeatedly interact to negotiate exploitation of a self-renewable resource under the ownership of the offerer. Successful agreements deplete the resource, whereas unsuccessful agreements inhibit exploitation and facilitate replenishment. The mutation–selection driven two-species
stochastic evolutionary dynamics reveal that the emergence of spite and
fairness strongly depends on the resource growth rate.
Fairness predominantly prevails for resources with high growth rates. Intriguingly, low resource growth rates give rise to a resource feedback loop driven by spite: spiteful behaviour dominates in the depleted state, facilitating transition of the resource state to replete state which, in turn, promotes
fairness through repeated interactions.
Read the full abstract ▾
Optics
Non-Hermitian Interaction between Light and Photonic Time Crystal Beyond the Floquet Quasinormal Mode Approximation
Yuhang Li, Yu Zhuang, Zilong Bao et al. (+4 more)
We report non-Hermitian mode couplings in a photonic time
crystal induced by the light within its momentum bandgap. When the relative phase between the light and the photonic time
crystal compensates for the detuning, we observe a periodic suppression of exponentially growing Floquet modes. In contrast, the optical response in this regime cannot be reproduced by the conventional Floquet expansion of the Green's function, revealing that the light induces effective mode couplings beyond the quasinormal mode approximation. We further investigate the parity-time phase transition through the exceptional point and quantitatively explain the suppression dynamics based on the phase, detuning, and modulation amplitude. The nontrivial interaction with light and the controllable non-Hermiticity indicate the great potential of photonic time
crystals in temporally modulated nanophotonics.
Read the full abstract ▾
All authors Yuhang Li, Yu Zhuang, Zilong Bao, Jingwen Cui, Junda Wang, Xiulai Xu, Chenjiang Qian
Computational Physics · Cross-listed from cond-mat.str-el
Optimization dynamics of Transformer backflow neural quantum states for the two-dimensional Hubbard model
Zong-Yu Liao, Jia-Qi Wang, Rong-Qiang He et al. (+1 more)
Building on the multi-determinant
Transformer backflow neural
quantum state (NQS) ansatz and the associated multi-stage training workflow for the doped two-dimensional Hubbard model, we investigate how the optimization dynamics of the NQS depend on several key optimization and architectural hyperparameters. The workflow consists of neural-network backflow (NNB) initialization, supervised
Transformer pre-training, and main energy optimization using the Moment-Adaptive ReConfiguration Heuristic (MARCH) within variational Monte Carlo. Using the doped $4\times4$ periodic Hubbard model at $U=8$ as a baseline, we examine how the update-norm threshold,
Transformer width, number of determinant channels, and Monte Carlo batch size affect convergence. We find that a moderate update constraint improves the efficiency of MARCH optimization, larger
Transformer width and more determinant channels improve the expressive capacity of the ansatz, and larger Monte Carlo batches reduce sampling noise in the update direction. We further test the same workflow at half filling, weaker interaction strength, open boundary conditions, and on a larger $8\times8$ doped
lattice. These results identify practical optimization trends for
Transformer backflow NQSs and highlight the balance between ansatz expressivity, MARCH update stability, and Monte Carlo sampling quality.
Read the full abstract ▾
All authors Zong-Yu Liao, Jia-Qi Wang, Rong-Qiang He, Zhong-Yi Lu
Medical Physics
One-for-All Adaptive Radiotherapy Planning Agent: A Foundation Framework for Daily CBCT-guided Radiotherapy
Shaoyan Pan, Kirk Jon Luca, Yuan Gao et al. (+8 more)
In this work, we introduce the One-for-All Adaptive Radiotherapy Planning
Agent, a unified foundation-model-based system that performs complete, treatment-specific online adaptive planning directly from daily cone-beam CT in under two minutes. The
agent first autonomously predicts all essential planning components, including synthetic CT generation,
multimodal alignment, and tumor/organ
segmentation. It then intelligently leverages these outputs to execute the final clinical plan design, providing a comprehensive, automated solution for daily treatment. We also demonstrate that the
agent enables clinicians to define planning with intent and intervene at critical decision points, ensuring a "human-in-the-loop" framework that generates acceptable plans before final approval. Evaluated on multiple
datasets spanning head-and-neck, lung, abdominal, and prostate cancers with both
photon and
proton therapy, the proposed framework achieves clinically acceptable accuracy and plan quality comparable to clinically generated treatment plans, with target dose errors (D98) generally within 2.0 Gy of the reference plan. The strong performance of the One-for-All
agent highlights the promise of a unified foundation-model approach and opens opportunities for fast, scalable, and fully automated online adaptive radiotherapy across diverse clinical scenarios.
Read the full abstract ▾
All authors Shaoyan Pan, Kirk Jon Luca, Yuan Gao, Shansong Wang, Mingzhe Hu, Ryan Sanford, Mojtaba Safari, Justin Roper, Zhen Tian, Tonghe Wang, Xiaofeng Yang
Instrumentation and Detectors
A flexible DAQ system for the Timepix4 ASIC in the 4DPHOTON project
N. V. Biesuz, J. Alozy, R. Bolzonella et al. (+6 more)
This paper presents the design and implementation of a flexible data acquisition system13 developed for the Timepix4 ASIC. The system is based on a modular14 FPGA-centric architecture combining high-speed serial readout, Ethernet-based data transport,15 and deterministic multi-board synchronization. The hardware platform includes a scalable stack16 composed of commercial FPGA carrier boards, FMC-based interface electronics, detector-specific17 chipboards, and a dedicated Trigger Logic Unit for synchronized operation.18 The firmware architecture separates control and data paths, enabling independent configuration19 and high-throughput acquisition through UDP over 10 GbE links. The design supports zero-back-20 pressure operation toward the ASIC and allows adaptation of the readout bandwidth to different21 experimental conditions. Synchronization between multiple DAQ systems is achieved through22 a common clock and trigger distribution network, experimentally demonstrated with sub-100 ps23 precision.24 The system has been developed to support detector characterization, laboratory measurements,25 and beam-test campaigns for the 4DPHOTON detector concept. Hardware organization, firmware26 architecture, synchronization strategy, and performance measurements are presented.
Read the full abstract ▾
All authors N. V. Biesuz, J. Alozy, R. Bolzonella, V. Cavallini, A. Cotta Ramusino, M. Fiorini, E. Franzoso, X. Llopart Cudie, A. Saputi
Optics · Cross-listed from astro-ph.IM
Millimetre-scale spectrographs for next-generation photonic instrumentation
Emily Ronson, Robert J. Harris, Ariadna Calcines Rosario et al. (+1 more)
We present a set of ultra-compact spectrographs fabricated using two-
photon polymerisation, each under 1 mm in length and printed directly onto an optical fiber. This fully integrated,
alignment-free architecture enables extremely low-mass instrumentation with broad potential across astrophotonics, space systems, drone-based sensing, and
quantum optics. Two transmissive configurations are presented; they combine beam-expansion optics, dispersive elements, and stray-light suppression within monolithic printed structures optimised for J- and H-band operation. Coarse gratings provide resolving powers of approximately R = 30. Experimental characterisation confirms the feasibility of fiber-coupled, fully printed spectrographs and demonstrates their promise as deployable components for next-generation integrated photonic instrumentation.
Read the full abstract ▾
All authors Emily Ronson, Robert J. Harris, Ariadna Calcines Rosario, Viktoria Kutnohorsky
Biological Physics · Cross-listed from cond-mat.soft
Density-driven reentrant polymer transitions via saturable bridging crowders
Monmee Phukan, Hitesh Garg and Satyavani Vemparala
Reentrant coil-globule-coil transitions, in which a
polymer collapses and then reexpands as a single parameter is varied, have been observed across diverse soft matter systems, yet the minimal ingredients required to produce them remain unclear. Using molecular dynamics simulations of coarse-grained
polymers interacting with a single species of attractive crowder, we show that crowder volume fraction $\phi_c$ alone is sufficient to drive a complete reentrant transition. At low $\phi_c$, crowders bridge distant monomers and drive cooperative collapse; at high $\phi_c$, saturation of monomer binding sites suppresses bridging connectivity and produces reentrant expansion. This density-driven transition is absent with purely repulsive crowders, which produce only monotonic compaction while preserving self-avoiding walk (SAW) chain statistics. In contrast, bridging breaks SAW universality: the rescaled size distributions no longer collapse onto a universal curve, and the conformational distributions trace the full coil-globule-coil trajectory as $\phi_c$ is varied. For charged
polymers with explicit counterions, electrostatics amplifies rather than suppresses reentrance: bridging crowders displace counterions from the chain, and upon saturation the unscreened backbone charges drive expansion well beyond the original chain size. Saturable
geometric bridging thus emerges as a minimal mechanism linking reentrant phenomena across neutral and charged
polymers in crowded environments.
Read the full abstract ▾
Geophysics
A Unified Conceptual Framework for Gravitational Instabilities: From Latent System State to Failure
Jérome Faillettaz
Gravitational instabilities are among the most widespread natural hazards and are expected to become increasingly significant under ongoing environmental change. Despite substantial advances in process understanding, monitoring, and modeling, predicting the timing of failure remains a fundamental challenge because instability emerges from complex interactions operating across multiple spatial and temporal scales. Existing approaches often focus on specific processes, forcing mechanisms, or observational signatures, resulting in a fragmented view of how systems evolve toward failure. This article propose a unified conceptual framework in which gravitational instabilities are interpreted as the progressive
evolution of a latent system state controlled by damage accumulation, stress redistribution and external forcing to catastrophic failure. Within this perspective, failure emerges from the continuous interplay between internal system dynamics and external forcing, while predictability depends on our ability to infer the evolving state of the system from incomplete and indirect observations. The framework provides a common structure linking physical processes, observable manifestations, monitoring strategies, modeling approaches, and
forecasting methods across a wide range of gravitational hazards. By integrating concepts from geomechanics, fracture mechanics, statistical physics, and data-driven sciences, the proposed framework shifts the focus from the search for universal precursors toward the reconstruction of evolving system states and their proximity to instability. It offers a unifying perspective for understanding failure processes and developing more robust approaches to hazard assessment and early warning.
Read the full abstract ▾
Computational Physics · Cross-listed from cond-mat.mtrl-sci
SevenNet-Polar for MultiTask Prediction of Energy, Forces, Stress, and Born Effective Charges: Development and Application to ZrO$_2$, Li$_3$PO$_4$, and Perovskites
Anh Khoa Augustin Lu, Shungo Arai, Yutack Park et al. (+3 more)
Accurate prediction of the Born effective charge (BEC) tensor is crucial for modeling materials under electric fields but remains computationally expensive. To bridge this gap, we present SevenNet-Polar, an equivariant graph neural network framework based on the SevenNet architecture for fast and accurate BEC predictions. Our BEC-only predictors can achieve an RMSE as low as 0.0043 e on ZrO$_2$, Li$_3$PO$_4$, and perovskites, despite the presence of high-temperature (up to 2,000 K) and defect-laden training data. Our all-in-one multitask models for predicting energy, forces, stress, and BEC in ZrO$_2$ and Li$_3$PO$_4$ achieve high accuracy with an RMSE of 1.0 meV/atom for energy, 12 meV/angstrom for forces, 0.05 GPa for stress, and 0.0029 e for BEC. BEC accuracy is not degraded by multitask training. Scaling analysis reveals distinct exponents for diagonal and off-diagonal BEC components, both of which exhibit less favorable scaling than energy, force and stress errors. SevenNet-Polar generalizes robustly when tested on scenarios containing structural environments absent from the training set, such as along nudged elastic band (NEB) trajectories or grain boundaries in ZrO$_2$. Accelerated by FlashTP, SevenNet-Polar enables simulations containing up to 1.5 million atoms on multi-GPU supercomputers and up to approximately 15,000 atoms on a single consumer-grade GPU. This makes charge-aware molecular dynamics simulations under electric fields more accessible.
Read the full abstract ▾
All authors Anh Khoa Augustin Lu, Shungo Arai, Yutack Park, Seungwu Han, Tsuyoshi Miyazaki, Satoshi Watanabe
Physics and Society
RACiMo: Red Ambiental Ciudadana de Monitoreo: A Student-Centred Citizen Science Network for Environmental Monitoring, Data Literacy, and Climate Awareness in Colombia
L.V. Flórez, G. Sánchez-Ariza, N. Mantilla-Molina et al. (+12 more)
This paper traces the
evolution of Red Ambiental Ciudadana de Monitoreo (RACiMo), a citizen-science and environmental-education initiative developed by Universidad Industrial de Santander in Colombia. RACiMo has evolved through successive editions from a school-based open-hardware programme into a regional environmental monitoring network that integrates meteorological and air-quality data, open-data practices, and student-centred research. The project's central objective is to train citizens, especially secondary-school students, teachers, and university mentors, to record, curate, analyse, interpret, and communicate
climate and air-quality data relevant to their local contexts. RACiMo has involved approximately 515 students from urban, metropolitan, rural, and páramo communities in Santander, Colombia. It has progressed from Arduino-Raspberry Pi stations assembled through a Do-It-With-Others approach to low-maintenance commercial instruments and a multi-municipality network of professional weather and air-quality stations. Its pedagogy has shifted from learning by building sensors to learning by analysing real environmental
datasets through Python, Jupyter notebooks, visualisation tools, and student-led research projects. The current RACiMo-Orquídeas implementation expands the network across five municipalities, emphasises local environmental issues such as freight traffic and industrial activity, and provides public access to data through repositories and interactive tools. The paper discusses the trade-offs between openness, educational value, reliability, data quality, sustainability, and scalability. It argues that citizen environmental monitoring can strengthen
climate awareness and adaptation when local communities are trained not only to collect data, but also to understand and use it critically.
Read the full abstract ▾
All authors L.V. Flórez, G. Sánchez-Ariza, N. Mantilla-Molina, J. Pisco-Guabave, A. Martínez-Méndez, A. Serrano-Mendoza, Luis A. Núñez, H. Asorey, L.M. Becerra, J. Grisales-Casadiegos, A. Núñez-Castiñeyra, J. Peña-Rodríguez, J. Salamanca-Coy, C. Sarmiento-Cano, D. Sierra-Porta