History and Philosophy of Physics
We Have Never Been Sophisticated
Clara Bradley and James Owen Weatherall
Many philosophers of physics maintain that a physical theory that exhibits (certain kinds of)
symmetries is flawed, on the grounds that such theories posit "excess structure". In an influential paper, Dewar [2019, "Sophistication about
Symmetries", Brit. J. Phil. Sci. 70: 485-521] introduces a distinction between "reduction" and "sophistication" as alternative ways of removing excess structure. In this paper we re-examine the distinction as Dewar draws it, and we argue that there is no physically or philosophically important distinction between what Dewar calls "reduction" and what he calls "internal sophistication". We then argue that there are multiple notions of "reduction" in the literature that ought to be distinguished, both in motivation and in outcome.
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Instrumentation and Detectors
Edge Machine Learning for Cluster Counting in Next-Generation Drift Chambers
Deniz Yilmaz, Liangyu Wu, Julia Gonski et al. (+2 more)
Drift chambers have long been central to
collider tracking, but future machines like a
Higgs factory motivate higher granularity and cluster counting for particle ID, posing new data processing challenges. Machine learning (ML) at the "edge", or in
cell-level readout, can dramatically reduce the off-detector data rate for high-granularity drift chambers by performing cluster counting at-source. We present machine learning
algorithms for cluster counting in real-time readout of future drift chambers. These
algorithms outperform traditional derivative-based techniques based on achievable pion-kaon separation. When synthesized to FPGA resources, they can achieve latencies consistent with real-time operation in a future
Higgs factory scenario, thus advancing both R&D for future
collider detectors as well as hardware-based ML for edge applications in high energy physics.
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All authors Deniz Yilmaz, Liangyu Wu, Julia Gonski, Dylan Rankin, Christian Herwig
Biological Physics
Interspecific information use facilitates species coexistence in ecosystems
Wei Tao, Ju Kang, Wenxiu Yang et al. (+2 more)
Explaining how competing species coexist remains a central question in ecology. The well-known competitive exclusion principle (CEP) states that two species competing for the same resource cannot stably coexist, and more generally, that the number of consumer species is bounded by the number of resource species at steady state. However, the remarkable species diversity observed in natural ecosystems, exemplified by the paradox of the plankton, challenges this principle. Here, we show that interspecific social information use among predators provides a mechanism that fundamentally relaxes the constraints of competitive exclusion. A model of predation dynamics that incorporates interspecific information use naturally explains coexistence beyond the limits imposed by CEP. Our model quantitatively reproduces two classical experiments that contradicts the CEP and captures coexistence patterns documented in natural ecosystems, offering a general mechanism for the maintenance of biodiversity in ecological communities.
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All authors Wei Tao, Ju Kang, Wenxiu Yang, Yiyuan Niu, Xin Wang
Physics Education · Cross-listed from cs.CL
Mastering Olympiad-Level Physics with Artificial Intelligence
Dong-Shan Jian, Xiang Li, Chen-Xu Yan et al. (+10 more)
Olympiad-level physics problem-solving significantly challenges both humans and artificial intelligence (AI), as it requires integrating appropriate modeling, application of physical principles, and precise calculation within long
reasoning processes. In this paper, we introduce LOCA (LOgical Chain Augmentation), an AI
agent framework designed for complex physics
reasoning. LOCA decomposes long
reasoning into serialized atomic and verifiable steps, refining the solution through an augment-review loop. We evaluate LOCA on the 2025 Chinese Physics Olympiad (CPhO) theory examination, a rigorous testbed renowned for its depth and complexity. The framework achieves a near-perfect score of 313 out of 320 points, significantly surpassing the top human competitor and other baseline methods. Furthermore, LOCA attains a near-perfect score of 28.6 out of 30 on the IPhO 2025 examination, demonstrating its strong generalizability across different contexts. Our work points toward the development of trustworthy AI partners in both research and education.
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All authors Dong-Shan Jian, Xiang Li, Chen-Xu Yan, Hui-Wen Zheng, Zhi-Zhang Bian, You-Le Fang, Ren-Xi He, Jing-Tian Zhang, Ce Meng, Ling-Shi Meng, Bing-Rui Gong, Sheng-Qi Zhang, Yan-Qing Ma
Fluid Dynamics
Self-similar scaling of variable-density Rayleigh-Taylor turbulence
Chian Yeh Goh, Daniel Brito Matehuala and Guillaume Blanquart
The dynamics of self-similar Rayleigh-Taylor (RT) mixing layers are investigated across a broad range of Atwood and Reynolds numbers using the statistically stationary Rayleigh-Taylor (SRT) flow configuration - a computational framework that enables simulation of self-similar RT flows at reduced cost compared to conventional temporally growing mixing layers. Normalizations are developed for all dominant non-transport terms in the continuity, mixed mass, and turbulent kinetic energy budgets in terms of the input parameters: the mixing layer height $h$, gravitational acceleration $g$, and fluid densities $\rho_H$ and $\rho_L$. Most normalized quantities collapse well across the parameter space. In some cases, variations in the Atwood number $A$ (or equivalently, the density ratio $R$) lead to consistent integral magnitudes but spatially shifted profiles. These shifts are primarily related to a division by density and are similarly observed in the analytical solution of the one-dimensional variable-density
diffusion problem. The analysis introduces a reference density for the mixed mass, examines trends in Favre-averaged statistics, and derives a scaling law for the growth rate of the mixing layer. For height definitions encompassing the full extent of the layer, the conventional growth parameter, $\alpha = \dot{h}^2/4Agh$, varies with Atwood number. Our analysis leads to an alternative formulation using an effective Atwood number, $A^*= (\ln R)/2$, that is consistent with the scaling proposed by Belen'kii & Fradkin (Trudy FIAN, vol. 29, 1965, pp. 207-238). The corresponding growth parameter, $\alpha^*=\dot{h}^2/4A^*gh$, remains nearly constant across all Atwood numbers considered, offering a unified scaling for variable-density RT flows.
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Computational Physics
Parallel and GPU accelerated code for phase-field and reaction-diffusion simulations
Steven A. Silber and Mikko Karttunen
We present SymPhas 2.0, a major update of the compile-time symbolic
algebra simulation framework SymPhas for phase-field and reaction-
diffusion models. This release introduces significant expansions and enhancements that enable the definition of a phase-field model directly from the free-energy functional via compile-time evaluated functional differentiation. It also introduces directional derivatives, symbolic summation, tensor-valued expressions, and compile-time derived finite difference stencils of arbitrary order and accuracy. Furthermore, the code has been parallelized for CPUs with MPI, and GPU computing has been added using CUDA (Compute Unified Device Architecture). For the latter, symbolic expressions are compiled into optimized CUDA kernels, allowing large-scale simulations to execute entirely on the GPU. For large systems ($32,768^2$ in 2D and $1,024^3$ in 3D with double precision), speedups up to $\sim \!\!1,000 \times$ were obtained compared to the first version of SymPhas using multi-threaded CPU execution on a single system. These developments establish SymPhas 2.0 as a flexible and scalable framework for efficient implementation of phase-field and reaction-
diffusion models on GPU-based high-performance computing platforms.
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Optics · Cross-listed from quant-ph
Frequency Spectra of Isolated Laser Pulse Envelopes
L. H. Ford and Brian Fu
This paper will deal with isolated
laser pulses, those which last for a finite time interval and whose envelope function is strictly zero outside of this interval. We numerically calculate the
Fourier transform of this function and study its asymptotic behavior at high frequencies. This work is motivated by recent results on the probability distributions of quadratic operators in second quantized systems. An example is the density of a material which is subject to zero point fluctuations in the
phonon vacuum state. These distributions can decrease very slowly, leading to a relatively high probability for large fluctuations. If the operator is measured by a
laser pulse, the rate of decrease of the distribution mirrors the rate of decrease of the pulse envelope
Fourier transform. We describe a model for the creation of isolated pulses in which this
Fourier transform falls as an exponential of a fractional power of frequency and find examples where this fraction is in the range 0.1 to 0.2. The probability distribution for large fluctuation has the same functional form and implies a significant probability for fluctuations very large compared to the variance.
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Atomic Physics · Cross-listed from astro-ph.SR
Collisional and magnetic effects on the polarization of the solar oxygen infrared triplet
Moncef Derouich and Saleh Qutub
Context: The scattering polarization of the infrared (IR) triplet of neutral oxygen (O\,i) near 777\,nm provides a powerful diagnostic of
solar atmospheric conditions. However, interpreting such polarization requires a rigorous treatment of isotropic depolarizing collisions between O\,i atoms and neutral hydrogen. Aims: We aim to investigate the combined effects of collisional and
magnetic depolarization in shaping the
alignment of O\,i levels (and thus the polarization of the O\,i IR triplet). Methods: We compute, for the first time, a comprehensive set of collisional depolarization and polarization transfer rates for the relevant O\,i energy levels. These rates are incorporated into a multi-level atomic model, and the statistical
equilibrium equations (SEE) are solved to quantify the impact of collisions and
magnetic fields on atomic
alignment. Results: Our calculations indicate that elastic collisions with neutral hydrogen, together with the Hanle effect of turbulent
magnetic fields stronger than about 20 G, efficiently suppress the bulk of the atomic
alignment in deep photospheric conditions where hydrogen densities exceed $n_{\mathrm{H}} \sim 10^{16}$ cm$^{-3}$. In the chromosphere, however, the lower hydrogen density weakens collisional depolarization, allowing polarization to persist. Conclusions: Our results are consistent with a chromospheric origin for the linear polarization signals of the O I IR triplet. Future studies should combine accurate non-LTE radiative transfer with reliable collisional rates in order to achieve fully consistent modeling.
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Optics
Superluminal Spacetime Crystals Induced by Anomalous Velocity Modulation
Filipa R. Prudêncio and Mário G. Silveirinha
Time-modulated media offer powerful opportunities for controlling light, yet extending such concepts to optical frequencies has remained challenging. Here we propose a different route to photonic spacetime
crystals based on modulation of the anomalous velocity in low-
symmetry conductors, particularly Weyl semimetals. We show that when driven by a strong optical pump, the anomalous velocity of Bloch electrons induces an ultrafast spacetime modulation that propagates with a superluminal phase velocity relative to the dielectric background. This self-induced modulation enables unidirectional light transport below the optical gap and, near the epsilon-near-zero point, gives rise to collective parametric resonance and stimulated emission of volume plasmons. These findings identify Weyl semimetals as a promising platform for realizing optical spacetime
crystals and open a pathway toward active and nonreciprocal photonic systems governed by
quantum geometric effects.
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Fluid Dynamics · Cross-listed from math.NA
Learning parameter-dependent shear viscosity from data, with application to sea and land ice
Gonzalo G. de Diego and Georg Stadler
Complex physical systems which exhibit fluid-like behavior are often modeled as non-Newtonian fluids. A crucial element of a non-Newtonian model is the rheology, which relates inner stresses with strain-rates. We propose a framework for inferring rheological models from data that represents the fluid's effective viscosity with a neural network. By writing the rheological law in terms of tensor invariants and tailoring the network's properties, the inferred model satisfies key physical and mathematical properties, such as isotropic frame-indifference and existence of a convex potential of dissipation. Within this framework, we propose two approaches to learning a fluid's rheology: 1) a standard regression that fits the rheological model to stress data and 2) a PDE-constrained optimization method that infers rheological models from velocity data. For the latter approach, we combine finite element and machine learning libraries. We demonstrate the accuracy and robustness of our method on land and sea ice rheologies which also depend on external parameters. For land ice, we infer the temperature-dependent Glen's law and, for sea ice, the concentration-dependent shear component of the viscous-plastic model. For these two models, we explore the effects of large data errors. Finally, we infer an unknown concentration-dependent model that reproduces Lagrangian ice floe simulation data. Our method discovers a rheology that generalizes well outside of the training
dataset and exhibits both shear-thickening and thinning behaviors depending on the concentrations.
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Optics
Wafer-scale conformal metasurface optics
Louis Martin-Monier, Sehui Chang, Johannes Froech et al. (+11 more)
Curved and conformal optics offer significant advantages by unlocking additional
geometric degrees of freedom for optical design. These capabilities enable enhanced optical performance and are essential for meeting non-optical constraints, such as those imposed by ergonomics, aerodynamics, or wearability. However, existing fabrication techniques such as direct electron or
laser beam writing on curved substrates, and soft-stamp-based transfer or nanoimprint lithography suffer from limitations in scalability, yield, geometry control, and
alignment accuracy. Here, we present a scalable fabrication strategy for curved and conformal metasurface optics leveraging thermoforming, an industry-standard, high-throughput manufacturing process widely used for shaping thermoplastics. Our approach uniquely enables wafer-scale production of highly curved metasurface optics, achieving sub-millimeter radii of
curvature and micron-level
alignment precision. To guide the design and fabrication process, we developed a thermorheological model that accurately predicts and compensates for the large strains induced during thermoforming. This allows for precise control of metasurface geometry and preservation of optical function, yielding devices with diffraction-limited performance. As a demonstration, we implemented an artificial compound eye comprising freeform micro-metalens arrays. Compared to traditional micro-optical counterparts, the device exhibits an expanded field of view, reduced aberrations, and improved uniformity, highlighting the potential of thermoformed metasurfaces for next-generation optical systems.
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All authors Louis Martin-Monier, Sehui Chang, Johannes Froech, Zhaoyi Li, Luigi Ranno, Khoi Phuong Dao, Akira Ueno, Jia Xu Brian Sia, Hanyu Zheng, Padraic Burns, Tian Gu, Young Min Song, Arka Majumdar, Juejun Hu
Biological Physics
Completion of partial structures using Patterson maps with the CrysFormer machine learning model
Tom Pan, Evan Dramko, Mitchell D. Miller et al. (+2 more)
Protein structure determination has long been one of the primary challenges of structural biology, to which deep machine learning (ML)-based approaches have increasingly been applied. However, these ML models generally do not incorporate the experimental measurements directly, such as X-ray crystallographic diffraction data. To this end, we explore an approach that more tightly couples these traditional crystallographic and recent ML-based methods, by training a hybrid 3-d
vision transformer and convolutional network on inputs from both domains. We make use of two distinct input constructs / Patterson maps, which are directly obtainable from crystallographic data, and “partial structure” template maps derived from predicted structures deposited in the AlphaFold
Protein Structure Database with subsequently omitted residues. With these, we predict electron density maps that are then post-processed into atomic models through standard crystallographic refinement processes. Introducing an initial
dataset of small
protein fragments taken from
Protein Data Bank entries and placing them in hypothetical
crystal settings, we demonstrate that our method is effective at both improving the phases of the crystallographic structure factors and completing the regions missing from partial structure templates, as well as improving the agreement of the electron density maps with the ground truth atomic structures.
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All authors Tom Pan, Evan Dramko, Mitchell D. Miller, Anastasios Kyrillidis, George N. Phillips Jr
Plasma Physics
Self-organisation through layering of $\beta$-plane like turbulence in plasmas and geophysical fluids
P. L. Guillon, G. Dif-Pradalier, Y. Sarazin et al. (+2 more)
Staircase formation and layering is studied in simplified, potential vorticity conserving models of
plasmas and geophysical fluids, by investigating turbulent self-organisation and nonlinear saturation with different mechanisms of free energy production – forcing or linear instability – and with standard or modified zonal flow responses. To this end, staircase formation in both the standard and modified Charney-Hasegawa-Mima equations with
stochastic forcing, along with two different simple instability driven models – one from a
plasma and from a geophysical context – are studied and compared. In these studies, it is observed that $\beta$-plane
turbulence that does not distinguish between zonal and non-zonal perturbations (i.e., standard zonal response) gradually forms large-scale,
elliptic zonal structures that merge progressively, regardless of whether it is driven by forcing (though it should be slow enough to allow wave couplings) or by the baroclinic instability, using for example a two-layer model. Conversely, the
plasma system, with its modified zonal response, can rapidly form straight, stationary jets of well-defined size, again regardless of the way it is driven: by
stochastic forcing or by the dissipative drift instability. Furthermore, the instability-driven
plasma system exhibits a phase transition between a zonal flow dominated state and an eddy dominated state. In both states, saturation is possible without large-scale friction.
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All authors P. L. Guillon, G. Dif-Pradalier, Y. Sarazin, D. W. Hughes, Ö. D. Gürcan
Applied Physics
Bandwidth of Linear Classically Damped Systems with Application to Experimental Model Aircraft
Benjamin J. Chang, Keegan J. Moore, Lawrence A. Bergman et al. (+2 more)
Bandwidth is a widely known concept and tool used in structural dynamics to measure an oscillator's capacity to dissipate energy over time, for example when used in half-power damping estimation of structural modes. Root Mean Square (RMS) Bandwidth is a generalization of bandwidth that overcomes some of the limitations encountered with conventional bandwidth, including the prerequisite of linearity, single-mode response, and light damping. However, its mathematical form does not reveal much about the physics behind it. In this paper, we extend RMS Bandwidth to multiple degree-of-freedom, linear, time-invariant, classically damped systems by deriving an Analytical Root Mean Square (ARMS) Bandwidth in terms of a system's modal parameters and initial modal energy distribution. We demonstrate that ARMS Bandwidth reliably and accurately computes a single measure for a practical structure's dissipative capacity. Also, a purely data-driven methodology for assessing the modal energy distribution is developed. We apply ARMS Bandwidth to single and multiple degree-of-freedom systems and an experimental model aircraft to demonstrate its broad applicability. Future work will address the effects of non-classical damping distribution, time-varying parameters, and nonlinearities.
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All authors Benjamin J. Chang, Keegan J. Moore, Lawrence A. Bergman, Alexander F. Vakakis, Walter A. Silva
Instrumentation and Detectors
Development of the CEPC analog hadron calorimeter prototype
Yukun Shi, Anshun Zhou, Hao Liu et al. (+16 more)
The Circular Electron Positron
Collider (CEPC) is a next-generation electron$-$positron
collider proposed for the precise measurement of the properties of the
Higgs boson. To emphasize
boson separation and jet reconstruction, the baseline design of the CEPC detector was guided by the particle flow
algorithm (PFA) concept. As one of the calorimeter options, the analogue
hadron calorimeter (AHCAL) was proposed. The CEPC AHCAL comprises a 40-layer sandwich structure using steel plates as absorbers and scintillator tiles coupled with silicon photomultipliers (SiPM) as sensitive units. To validate the feasibility of the AHCAL option, a series of studies were conducted to develop a prototype. This AHCAL prototype underwent an electronic test and a
cosmic ray test to assess its performance and ensure it was ready for three beam tests performed in 2022 and 2023. The test beam data is currently under analysis, and the results are expected to deepen our understanding of
hadron showers, validate the concept of Particle Flow
Algorithm (PFA), and ultimately refine the design of the CEPC detector.
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All authors Yukun Shi, Anshun Zhou, Hao Liu, Jiechen Jiang, Yanyun Duan, Yunlong Zhang, Zhongtao Shen, Jianbei Liu, Boxiang Yu, Shu Li, Haijun Yang, Yong Liu, Liang Li, Zhen Wang, Siyuan Song, Dejing Du, Jiaxuan Wang, Junsong Zhang, Quan Ji
Applied Physics · Cross-listed from cs.CE
Phase field modelling of cracking and capacity fade in core-shell cathode particles for lithium-ion batteries
Y. Tu, B. Wu and E. Martínez-Pañeda
Core-shell electrode particles are a promising morphology control strategy for high-performance lithium-ion batteries. However, experimental observations reveal that these structures remain prone to mechanical failure, with shell fractures and core-shell debonding occurring after a single charge. In this work, we present a novel, comprehensive computational framework to predict and gain insight into the failure of core-shell morphologies and the associated degradation in battery performance. The fully coupled chemo-mechano-damage model presented captures the interplay between mechanical damage and electrochemical behaviours, enabling the quantification of particle cracking and capacity fade. Both bulk material fracture and interface debonding are captured by utilising the phase field method. We quantify the severity of particle cracking and capacity loss through case studies on a representative core-shell system (NMC811@NMC532). The results bring valuable insights into cracking patterns, underlying mechanisms, and their impact on capacity loss. Surface cracks are found to initiate when a significantly higher lithium concentration accumulates in the core compared to the shell. Interfacial debonding is shown to arise from localised hoop stresses near the core-shell interface, due to greater shell expansion. This debonding develops rapidly, impedes lithium-ion transport, and can lead to more than 10% capacity loss after a single discharge. Furthermore, larger particles may experience crack branching driven by extensive tensile zones, potentially fragmenting the entire particle. The framework developed can not only bring new insight into the degradation mechanisms of core-shell particles but also be used to design electrode materials with improved performance and extended lifetime.
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Optics
Phase noise properties of supercontinuum generation in all-normal dispersion fibers
Matis Marcadier, Nicolas Forget, Yoann Pertot et al. (+1 more)
The spectral coherence properties of supercontinuum generation in polarization-maintaining all-normal dispersion fibers are investigated.
Stochastic phase noise induced by energy fluctuations, along with spectrally-resolved intensity-to-phase transfer coefficients, are quantitatively analyzed, confirming the high coherence of the generated supercontinuum. Our results show that the nonlinear process is fundamentally deterministic with ultra-low spectral phase noise, yet exhibits significant intensity-to-phase coupling.
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All authors Matis Marcadier, Nicolas Forget, Yoann Pertot, Aurelie Jullien
Optics
Alex J. Vernon and Konstantin Y. Bliokh
Geometric phases play an enormous role in optics and are generally associated with the
evolution of light's polarization state on the Poincaré sphere, or its
spin on the sphere of
spin directions. Here we put forward a new kind of optical
geometric phase that appears exclusively in nonparaxial light, resulting from cyclic changes to the relative amplitude and phase between the electric and
magnetic fields. This phase is naturally represented on a recently introduced `electric-
magnetic' sphere.
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Applied Physics · Cross-listed from cond-mat.mes-hall
k-Selective Electrical-to-Magnon Transduction with Realistic Field-distributed Nanoantennas
Andreas Höfinger, Andrey A. Voronov, David Schmoll et al. (+9 more)
The excitation and detection of propagating
spin waves with lithographed nanoantennas underpin both classical magnonic
circuits and emerging
quantum technologies. Here, we establish a framework for all-electrical propagating
spin-wave spectroscopy (AEPSWS) that links realistic electromagnetic drive fields to micromagnetic dynamics. Using finite-element (FE) simulations, we compute the full vector near-field of electrical impedance-matched, tapered coplanar and stripline
antennas and import this distribution into finite-difference (FD) micromagnetic solvers. This approach captures the
antenna-limited wave-vector spectrum and the component-selective driving fields (perpendicular to the static magnetisation) that simplified uniform-field models cannot. From this coupling, we derive how realistic current return paths and tapering shapes, k-weighting functions, for Damon-Eshbach surface
spin waves in yttrium-iron-garnet (YIG) films are, for millimetre-scale matched CPWs and linear tapers down to nanometre-scale
antennas. Validation against experimental AEPSWS on a $48\,nm$ YIG film shows quantitative agreement in dispersion ridges, group velocities, and spectral peak positions, establishing that the
antenna acts as a tunable k-space filter. These results provide actionable design rules for on-chip magnonic transducers, with immediate relevance for low-power operation regimes and prospective applications in
quantum magnonics.
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All authors Andreas Höfinger, Andrey A. Voronov, David Schmoll, Sabri Koraltan, Florian Bruckner, Claas Abert, Dieter Suess, Morris Lindner, Timmy Reimann, Carsten Dubs, Andrii V. Chumak, Sebastian Knauer
Physics and Society
Regret, Uncertainty, and Bounded Rationality in Norm-Driven Decisions
Christos Charalambous
This study introduces an
agent-based model to study how regret, uncertainty, and social norms interact to shape vaccination behavior during epidemics. The model integrates three behavioral mechanisms, anticipated regret, evolving norms, and uncertainty-dependent trust, within a unified learning framework. Grounded in psychology and behavioral economics, it captures how individuals make probabilistic choices influenced by material payoffs, fear, trust, and social approval. Simulations of the Susceptible-Infected-Recovered process show that collective outcomes are best when
agents display an intermediate level of rationality; they deliberate enough to respond to risk but remain flexible enough to adapt, avoiding the instability of both random and overly rigid decision-making. Regret exerts a dual influence; moderate levels encourage adaptive self-correction, while excessive regret or greed destabilize choices. Uncertainty has a similarly non-linear effect; moderate ambiguity promotes caution, but too much uncertainty disrupts coordination. Social norms restore cooperation by compensating for incomplete information. Personal norms guide behavior when individuals have reliable information and feel confident in their judgments. Injunctive norms-signals of others' approval-become more influential under uncertainty, while descriptive norms, which arise from observing others' actions, provide informational cues that help people decide what to do when direct knowledge is limited. Overall, the model provides a psychologically grounded, computationally explicit account of how
emotion, cognition, and social norms govern preventive behavior during epidemics.
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Biological Physics · Cross-listed from cond-mat.stat-mech
Stochastic Thermodynamics of Cooperative Biomolecular Machines: Fluctuation Relations and Hidden Detailed Balance Breaking
D. Evan Piephoff and Jianshu Cao
We examine a biomolecular machine involving a driven, observable process coupled to a hidden process in a kinetically cooperative manner. A
stochastic thermodynamics framework is employed to analyze a fluctuation
theorem for the first-passage time of the observable process under nonequilibrium steady-state conditions. Based on a generic kinetic model, we demonstrate that, along first-passage trajectories,
entropy production remains constant when the changes in
stochastic entropy and free energy of the machine are balanced, which corresponds to zero net hidden flux through the initial state
manifold. Under this condition, which we define quite generally, this first-passage time fluctuation
theorem can be established, with its violation serving as an experimentally detectable signature of hidden detailed balance breaking (which we subsequently characterize). In addition, using an enzymatic model, we show that the violation of our first-passage time fluctuation
theorem can be thought of as a consequence of the breakdown of local detailed balance in the steps linking coarse-grained states that correspond to the initial and intermediate state
manifolds. In the absence of hidden current, the fluctuation
theorem is restored, and a mesoscopic local detailed balance condition can be established, which has implications for the thermodynamic analysis of driven, coarse-grained systems. This work sheds significant light on the unique connections between
stochastic thermodynamic quantities and kinetic measurements in complex cooperative networks.
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Instrumentation and Detectors
Time resolution of the ALICE Time-Of-Flight detector with the first Run 3 pp collisions at ${\bf \sqrt{\textit{s}} = 13.6}$ TeV
ALICE Collaboration
Particle identification (PID) is a fundamental aspect of the ALICE detector system, central to its heavy-ion and
proton-
proton physics programs. Among the different PID strategies, ALICE uses the Time-Of-Flight (TOF) detector to identify particles at intermediate momenta ($0.5 < p_{\rm T} < 4$ GeV/$c$). The ALICE TOF detector performed successfully during the first ten years of LHC operations. During the Long Shutdown 2, many ALICE sub-detectors, including TOF, were upgraded to fully leverage the targeted 50 kHz interaction rate of Pb$-$Pb collisions, which required the implementation of a continuous readout scheme. The TOF detector electronics were upgraded and refurbished, while processing
algorithms for data quality control, reconstruction, calibration, and analysis were rewritten. This paper presents the upgraded TOF detector operation and calibration procedures and its performance in terms of timing resolution, a key factor for particle separation in ALICE analyses. Using 2022 pp collision data at $\sqrt{s} = 13.6$ TeV from Run 3, the time resolution of the detector was estimated with two independent methods, both yielding consistent results, better than 80 ps. Despite the excellent performance already achieved, further improvements are expected after additional detector commissioning and refined calibration procedures, thus enhancing the ALICE PID capabilities for Run 3 and beyond.
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Chemical Physics
Analytical Nuclear Gradients for the Multiconfigurational Self-Consistent Field Method Coupled with the Polarizable Fluctuating Charges Model
Francesco Mazza, Marco Trinari, Chiara Sepali et al. (+1 more)
The multiscale model combining the multiconfigurational self-consistent field (MCSCF) method with the fully atomistic polarizable Fluctuating Charges (FQ) force field (J. Chem. Theory Comput. 2024, 20, 9954-9967) is here extended to the calculation of analytical
nuclear gradients. The gradients are derived from first principles, implemented in the OpenMolcas package, and validated against numerical references. The resulting MCSCF/FQ
nuclear gradients are employed to simulate vibronic absorption spectra of aromatic molecules in aqueous solution, namely benzene and phenol. By integrating this approach with molecular dynamics simulations, both solute conformational flexibility and the dynamical aspects of solvation are properly captured. The computed spectra reproduce experimental profiles and relative band intensities with remarkable accuracy, demonstrating the capability of the MCSCF/FQ model to simultaneously describe the multireference character of the solute and its interaction with the solvent environment.
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All authors Francesco Mazza, Marco Trinari, Chiara Sepali, Chiara Cappelli
Chemical Physics · Cross-listed from cond-mat.mes-hall
Long-range propagating paramagnon-polaritons in organic free radicals
Sebastian Knauer, Roman Verba, Rostyslav O. Serha et al. (+5 more)
Materials are commonly distinguished by their
magnetic response into diamagnetic, paramagnetic, and magnetically ordered (ferro-, ferri-, and
antiferromagnetic) phases. Diamagnets and paramagnets lack spontaneous long-range order, whereas ordered magnets develop such order below their Curie or Néel temperature and support single
spin-wave excitations (
magnons).
Magnons have found applications in
radio-frequency technologies and computation, magneto-optics, and foundational
quantum experiments. Above the Curie/Néel temperature, long-range order is lost and the material transitions to a paramagnetic phase, with localised
spin alignment in small patches, producing paramagnons with only short-range propagation. Here we show that long-range coherence is preserved in the organic free radical 2,2,6,6-tetramethylpiperidin-1-oxyl above the Néel temperature using all-electrical propagating
spin-wave spectroscopy in external
magnetic fields. We observe coherently excited low-energy paramagnon-polaritons up to $\mathbf{23\,\mathrm{GHz}}$ , propagating over $\mathbf{8\,\mathrm{mm}}$ at supersonic group velocities exceeding $\mathbf{100\,\mathrm{km\,s^{-1}}}$. Using free radicals as
magnon carriers integrates organic materials with spintronics and opens the way to organic electronics, dense information storage, and
quantum technologies.
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All authors Sebastian Knauer, Roman Verba, Rostyslav O. Serha, Denys Slobodianiuk, David Schmoll, Andreas Ney, Sergej Demokritov, Andrii Chumak
Space Physics
Electron Heat Flux and Whistler Instability in the Earth's Magnetosheath
Ida Svenningsson, Emiliya Yordanova, Yuri V. Khotyaintsev et al. (+4 more)
Despite heat flux's role in regulating energy conversion in collisionless
plasmas, its properties and
evolution in the magnetosheath downstream of the Earth's bow shock are scarcely explored. We use MMS in situ measurements to quantify and characterize the electron heat flux in the magnetosheath. We find that the heat flux is shaped by the magnetosheath
magnetic field as it drapes around the magnetosphere. While it is affected by
solar wind upstream conditions and increases with
magnetic field strength, it is not substantially changed by local magnetosheath processes. Also, the heat flux is limited by whistler instability thresholds.
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All authors Ida Svenningsson, Emiliya Yordanova, Yuri V. Khotyaintsev, Mats André, Giulia Cozzani, Alexandros Chasapis, Steven J. Schwartz
Optics
Low-Energy Free-Electron Nonclassical Lasing
Mai Zhang, Yu Wang, Chang-Ling Zou et al. (+4 more)
Harnessing a beam of slow free electrons in artificial photonic structures offers a powerful, tunable platform for generating nonclassical light without the need for heavy physical equipment. Here we present a theory of nonclassical lasing, demonstrating how incoherent electrons in photonic
crystal cavities can coherently emit
photons through collective dynamics. When
photon emission rate exceeds cavity losses, nonclassical lasing with sub-Poissonian
photon statistics emerges, driven by multi-
photon Rabi oscillations. At specific coupling strengths,
quantum state trapping effect emerges, producing high-fidelity Fock states at room temperature (e.g. nearly 90%-fidelity of four
photon Fock state). Notably, the frequency of the emitted
photons can be readily tuned via the velocity of the injected electrons to match cavity modes. This approach supports photonic integration and offers a scalable, energy-efficient platform for room-temperature
quantum light sources and advanced studies in
quantum electrodynamics.
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All authors Mai Zhang, Yu Wang, Chang-Ling Zou, Lei Ying, Qiongyi He, Guang-Can Guo, Chun-Hua Dong
Geophysics · Cross-listed from astro-ph.EP
Fundamentals of interior modelling and challenges in the interpretation of observed rocky exoplanets
Philipp Baumeister, Francesca Miozzi, Claire Marie Guimond et al. (+7 more)
Most our knowledge about rocky
exoplanets is based on their measure of mass and radius. These two parameters are routinely measured and are used to categorise different populations of observed
exoplanets. They are also tightly linked to the
planet's properties, in particular those of the interior. As such they offer the unique opportunity to interpret the observations and potentially infer the
planet's chemistry and structure. Required for the interpretation are models of planetary interiors, calculated a priori, constrained using other available data, and based on the physiochemical properties of mineralogical phases. This article offers an overview of the current knowledge about
exoplanet interiors, the fundamental aspects and tools for interior modelling and how to improve the contraints on the models, along with a discussion on the sources of uncertainty. The origin and fate of volatiles, and their role in planetary
evolution is discussed. The chemistry and structure of planetary interiors have a pivotal role in the thermal
evolution of
planets and the development of large scale properties that might become observables with future space missions and ground-based surveys. As such, having reliable and well constrained interior models is of the utmost importance for the advancement of the field.
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All authors Philipp Baumeister, Francesca Miozzi, Claire Marie Guimond, Marie-Luise Steinmeyer, Caroline Dorn, Shun-Ichiro Karato, Emeline Bolmont, Alexandre Revol, Alexander Thamm, Lena Noack
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Effect of Concentration Fluctuations on Material Properties of Disordered Alloys
Han-Pu Liang, Chuan-Nan Li, Xin-Ru Tang et al. (+4 more)
Alloying compound AX with another compound BX is widely used to tune material properties. For disordered
alloys, due to the lack of periodicity, it has been challenging to calculate and study their material properties. Special quasi-random structure (SQS) method has been developed and widely used to treat this issue by matching averaged atomic correlation functions to those of ideal random
alloys, enabling accurate predictions of macroscopic material properties such as total energy and volume. However, in AxB1-x
alloys, statistically allowed local concentration fluctuations can give rise to defect-like minority configurations, such as bulk-like AX or BX regions in the extreme, which could strongly affect calculation of some of the material properties such as
semiconductor bandgap, if it is not defined properly, leading to significant discrepancies between theory and experiment. In this work, taking the bandgap as an example, we demonstrate that the calculated
alloy bandgap can be significantly underestimated in standard SQS calculations when the SQS
cell size is increased to improve the structural model and the bandgap is defined conventionally as the energy difference between the lowest unoccupied state and the highest occupied state, because the rare event motifs can lead to wavefunction localization and become the dominant factor in determining the "bandgap", contrary to experiment. To be consistent with experiment, we show that the bandgap of the
alloy should be extracted from the majority configurations using a density-of-states fitting (DOSF) method. This DOSF approach resolves the long-standing issue of calculating electronic structure of disordered
semiconductor alloys. Similar approaches should also be developed to treat material properties that depends on localized
alloy wavefunctions.
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All authors Han-Pu Liang, Chuan-Nan Li, Xin-Ru Tang, Xun Xu, Chen Qiu, Qiu-Shi Huang, Su-Huai Wei
Fluid Dynamics
Freezing dynamics of the ferrofluid droplet in a uniform magnetic field using the lattice Boltzmann flux solver
Jinxiang Zhou, Liming Yang, Yaping Wang et al. (+2 more)
In this study, an enthalpy-based
lattice Boltzmann flux solver is developed to simulate the freezing dynamics of a ferrofluid droplet under a uniform
magnetic field. The accuracy and robustness of the solver are first validated through three
benchmark tests: conductive freezing, static droplet freezing, and ferrofluid droplet deformation. The solver is then employed to investigate the influence of a uniform
magnetic field on the freezing behavior of ferrofluid droplets, with particular emphasis on the overall freezing process, heat transfer characteristics, and freezing duration. The results reveal that the uniform
magnetic field affects the freezing dynamics primarily by altering the droplet morphology. Under a vertically oriented
magnetic field, the droplet elongates along the field direction, which increases the thermal resistance and consequently prolongs the freezing time. Conversely, a horizontally uniform
magnetic field flattens the droplet, reducing the thermal resistance and thus shortening the freezing time. These findings provide new physical insight into
magnetic-field-induced modulation of the freezing process in ferrofluid systems.
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All authors Jinxiang Zhou, Liming Yang, Yaping Wang, Jie Wu, Xiaodong Niu
Optics
Systematic dispersion engineering of crystalline microresonators for broadband and coherent frequency comb generation
Liu Yang, Ryomei Takabayashi, Hiroki Moriguchi et al. (+9 more)
Ultraprecision machining offers a powerful route to dispersion control in crystalline microresonators, allowing the design of waveguide geometries for tailoring the spectrum of microresonator frequency combs. By precisely designing the geometry, both group-velocity and higher-order dispersions can be engineered across a broad wavelength range. However, despite their promising features, such advantages have remained largely unexplored due to fabrication challenges. Here, we demonstrate that resonators shaped by ultrapecision machining exhibit high precision and strongly suppressed spatial mode interactions, facilitating the generation of smooth dissipative Kerr
soliton combs and broadband frequency combs beyond the telecommunication C-band. These results underscore the effectiveness of precision geometry control for realizing coherent and broadband microcombs on crystalline photonic platforms.
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All authors Liu Yang, Ryomei Takabayashi, Hiroki Moriguchi, Hikaru Kodama, Kazuma Miura, Koshiro Wada, Kai Yamaguchi, Tatsuki Murakami, Hajime Kumazaki, Yasuhiro Kakinuma, Takasumi Tanabe, Shun Fujii