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Physics Physics

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Saturday 14 February

Chemical Physics

Efficient Simulation of Non-Markovian Path Integrals via Imaginary Time Evolution of an Effective Hamiltonian

Xiaoyu Yang, Limin Liu, Wencheng Zhao et al. (+2 more)

Accurately simulating the non-Markovian dynamics of open quantum systems remains a significant challenge. While the recently proposed time-evolving matrix product operator (TEMPO) algorithm based on path integrals successfully circumvents the exponential scaling associated with memory length, its reliance on layer-by-layer tensor contractions and compressions leads to steep scaling with respect to the system Hilbert space dimension. In this work, we introduce the effective Hamiltonian-based TEMPO (EH-TEMPO) algorithm, which reformulates the calculation of the Feynman-Vernon influence functional as an imaginary time evolution governed by an effective Hamiltonian. We demonstrate that this effective Hamiltonian admits a highly compact matrix product operator representation, enabling substantial compression with negligible loss of accuracy. Combining a one-shot global evolution with a backward retrieval approach, EH-TEMPO significantly reduces algorithmic complexity and is naturally suited for GPU acceleration. We benchmark the method by simulating the energy transfer dynamics in the 7-site Fenna-Matthews-Olson complex model and 4-site perylene bisimide model. The results demonstrate that EH-TEMPO achieves numerically exact accuracy with superior efficiency, delivering speedups of up to 17.5$\times$ on GPU hardware compared to standard CPU implementations.
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All authors Xiaoyu Yang, Limin Liu, Wencheng Zhao, Jiajun Ren, Wei-Hai Fang

Physics and Society

The gold-rush effect: how innovation speeds up

Alessandro Bellina, Gabriele Di Bona, Giordano De Marzo et al. (+1 more)

Innovation records often exhibit "hockey-stick" patterns of abrupt, near-singular growth at the collective level. However, this macroscopic explosiveness stands in stark contrast to individual discovery, which remains bounded by cognitive and temporal constraints and follows slow, sublinear accumulation laws. Here, we resolve this micro-macro discrepancy by introducing a minimal multi-scale model that identifies the growth of the explorer population as the primary driver of aggregate acceleration. Building on the Theory of the Adjacent Possible and the Urn Model with Triggering (UMT), we demonstrate that as discoveries expand the space of possibilities, they attract new explorers through a self-reinforcing branching process. This expansion induces a nonlinear mapping between intrinsic time (individual discovery events) and natural time (calendar years), effectively reparameterizing steady individual trajectories into accelerating system-level dynamics. We validate the framework using large-scale patent (EPO) and scientific publication (OpenAlex) datasets, showing that the model accurately reproduces stable per-capita productivity alongside exponential aggregate growth. By providing a quantitative link between individual behavior and collective takeoffs, this work offers a unified foundation for understanding the statistical structure and temporal evolution of innovation ecosystems.
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All authors Alessandro Bellina, Gabriele Di Bona, Giordano De Marzo, Vittorio Loreto

Accelerator Physics

Demonstration of High-Gain Harmonic Lasing in a Terahertz Free-Electron Laser

Yin Kang, Cheng Yu, Yue Wang et al. (+26 more)

Compact Free-Electron Lasers (FELs) offering broad, continuous spectral tunability are traditionally constrained by fixed-parameter magnetic structures and the necessity for high-energy electron beams. High-gain Harmonic Lasing (HL) has long been proposed as a solution to overcome these limitations; however, a robust experimental verification of this principle has remained absent. Here, we report the first experimental demonstration of high-gain HL. By employing a frequency-tunable electron beam density modulation to dominate the fundamental instability, we achieved sustained FEL amplification at the 3rd and 5th harmonics of the wiggler. The HL mode generated output power comparable to conventional fundamental operation with enhanced stability and narrower spectral bandwidth. Notably, we demonstrate that HL extends the spectral coverage by a factor of two under fixed facility constraints, achieving pulse energies up to 540 {\mu}J. These results establish high-gain HL as a versatile mechanism for advancing compact, wavelength-flexible FEL facilities.
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All authors Yin Kang, Cheng Yu, Yue Wang, Weiyi Yin, Zhangfeng Gao, Hanghua Xu, Hang Luo, Jian Chen, Taihe Lan, Xiaoqing Liu, Jinguo Wang, Huan Zhao, Fei Gao, Liping Sun, YanYan Zhu, Yongmei Wen, Chengcheng Xiao, Yongfang Liu, Yixuan Liu, Xingtao Wang, Jiaqiang Xu, Zheng Qi, Tao Liu, Bin Li, Kaiqing Zhang, Zhen Wang, Chao Feng, Bo Liu, Zhentang Zhao

Optics

Translationally deformed topological charge nanolaser with an ultrasmall mode volume

Shengqun Guo, Feng Tian, Yuhua Liao et al. (+2 more)

Developing vortex nanolasers is highly desirable for on-chip multidimensional large-capacity information processing. Topological optical modes hold great promise for achieving coherent emission with diverse functionalities. However, the development of robust and ultracompact topological charge lasing operation remains insufficiently explored. Here, we theoretically propose a translationally deformed topological charge vortex nanocavity with a low mode volume of 0.32 $(\lambda/n)^3$, and experimentally demonstrate the corresponding lasing emission with a low lasing threshold of around 0.74 $\mu$W. The designed topological nanocavity, constructed by translationally deformed photonic crystals, supports an ultracompact optical mode carrying a topological charge characterized by polarization winding. The well-defined topological charge characteristics of the fabricated device are revealed in both near- and far-field polarization-resolved optical profiles. Our work opens a promising avenue for versatile topological photonic integration and gives new potential for exploring intriguing structured light-matter interactions under the topological photonics scenario.
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All authors Shengqun Guo, Feng Tian, Yuhua Liao, Bowen Han, Taojie Zhou

Optics · Cross-listed from quant-ph

Quantum dynamics of microwave photons in synthetic frequency dimension

Zheshu Xie, Luojia Wang, Jiawei Qiu et al. (+13 more)

Synthetic frequency dimension offers a powerful approach to simulate lattice models and control photon dynamics. However, extending this concept into the quantum regime, particularly at the single-photon level, has remained challenging in photonic platforms. Here, we demonstrate quantum-state initialization and detection of single-photon evolutions within a synthetic frequency lattice by integrating a superconducting qubit with a 16-meter aluminum coaxial cable. A tunable superconducting quantum interference device (SQUID)-based modulator is employed to synthesize lattice couplings and artificial gauge fields. We observe single-photon quantum random walks and Bloch oscillations, as well as nonadiabatic, unidirectional frequency conversion under rapid temporal modulation of the lattice Hamiltonian, together with band-structure measurements. The lattice connectivity can be readily reconfigured to construct higher-dimensional lattices using multiple drive tones. Our results establish superconducting quantum circuits as a versatile platform for programmable Hamiltonians and extensible synthetic lattices with flexible single-photon control.
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All authors Zheshu Xie, Luojia Wang, Jiawei Qiu, Libo Zhang, Yuxuan Zhou, Ziyu Tao, Wenhui Huang, Yongqi Liang, Jiajian Zhang, Yuanzhen Chen, Song Liu, Jingjing Niu, Yang Liu, Youpeng Zhong, Luqi Yuan, Dapeng Yu

Fluid Dynamics

Instability of microbial droplets growing on viscous substrates

Vicente Gomez Herrera and Scott Weady

We develop and analyze a model for a flat microbial droplet growing on the surface of a three-dimensional viscous fluid. The model describes growth-induced stresses at the fluid surface, density variations in the bulk due to nutrient consumption, and the resulting fluid flows that arise. We reformulate this free-boundary problem as a system of integro-differential equations defined solely on the microbial domain. From this formulation, we identify an axisymmetric solution corresponding to a radially expanding disk and analyze its morphological stability. We find that growth forces stabilize the axisymmetric solution while buoyancy forces destabilize it. We connect these findings to experimental observations.
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Optics

Broadband High-Speed Dual-Comb Spectroscopy Enabled by a Dynamic 1550 nm Bidirectional Dissipative Soliton Fiber Laser

Mingjun Wang, Zhangru Shi, Anshuang Wang et al. (+1 more)

We report a high-energy, bidirectional, dissipative soliton mode-locked fiber laser operating in the 1550 nm normal-dispersion regime. By leveraging intracavity dispersion management and a Lyot filtering mechanism, the laser achieves flat-top optical spectra with 10-dB bandwidths exceeding 20 nm in both directions. Single-pulse energies of 2.7 nJ and 1.5 nJ are achieved for the clockwise and counter-clockwise directions, respectively. Furthermore, the all-fiber configuration exhibits superior noise performance and inherent common-mode noise suppression. To facilitate broadband and high-speed dual-comb spectroscopy, we employ a dynamic repetition rate difference control technique via pump power modulation, enabling zero-crossing dynamic scanning. This approach achieves a spectral measurement bandwidth of approximately 16 nm at an acquisition rate of 500 Hz. Compared to static operation, this represents a nearly two-order-of-magnitude improvement in acquisition speed and achieves a fivefold measurement bandwidth beyond the Nyquist aliasing limit. Experimental results demonstrate that the system maintains robust coherence even under dynamic modulation. By implementing a phase-correction algorithm, a mutual coherence time of 0.5 s is successfully achieved, yielding a spectral resolution exceeding 7.2 GHz. This work fills a gap in high-energy dissipative soliton dual-comb sources at 1550 nm and provides an ideal solution for low-cost, high-sensitivity dual-comb spectroscopy requiring both broad bandwidth and high speed.
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All authors Mingjun Wang, Zhangru Shi, Anshuang Wang, Bowen Li

Optics

Precision Hamiltonian Encoding in Full-Aperture Spatial Photonic Ising Machines

P. S. Karavelas, D. Karanikolopoulos, L. Mouchliadis et al. (+11 more)

Spatial photonic Ising machines (SPIMs) offer compact, room-temperature hardware with inherently parallel, energy-efficient, single-shot optical evaluation of the Ising Hamiltonian. However, accurate operation has been fundamentally limited by optical aberrations and non-uniform illumination, which corrupt phase-based spin encoding and distort coupling representation, forcing operation to a restricted spatial light modulator (SLM) region. Here we introduce a high-precision full-aperture calibration scheme that overcomes these constraints. By implementing wavefront retrieval and correction with $<\lambda/40$ accuracy, we restore faithful phase encoding across the entire SLM area. Furthermore, we introduce an interaction-normalization method, which compensates for amplitude curvature and enables uniform coupling representation. Together, these advances establish a full-aperture SPIM architecture whose faithful Hamiltonian encoding is a prerequisite for photonic Ising computation.
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All authors P. S. Karavelas, D. Karanikolopoulos, L. Mouchliadis, A. K. Spiliotis, N. L. Pitanios, S. Gentilini, D. Veraldi, P. Charlesworth, D. Pierangeli, J. Sakellariou, N. G. Berloff, S. I. Tsintzos, C. Conti, P. G. Savvidis

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

Quantitative models for excess carrier diffusion and recombination in STEM-EBIC experiments on semiconductor nanostructures

Tobias Meyer, Christoph Flathmann, David A. Ehrlich et al. (+4 more)

The increased complexity and reduced size of (opto-)electronic devices demands for quantitative descriptions of excess carrier transport and recombination via various mechanisms. In addition, experimental methods capable of resolving carrier dynamics on the nanometer scale are required. In this paper, we present a quantitative model of a confined geometry including recombination at two surfaces, which is very generic for electron beam induced current measurements in a scanning transmission electron microscope - a method which offers atomic scale spatial resolution. The model is based on analytical considerations as well as finite element simulations and underlying assumptions are subjected to an in-depth discussion. Finally, the successfull application to experimental data obtained on the complex oxide SrTi0.995Nb0.005O3 demonstrates the practicality and robustness of the approach, which enables the precise determination of its bulk diffusion length of L = 10.2 +- 0.1 nm.
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All authors Tobias Meyer, Christoph Flathmann, David A. Ehrlich, Patrick Paap-Peretzki, Jonas Lindner, Christian Jooß, Michael Seibt

History and Philosophy of Physics

Making Symmetry Explicit: The Limits of Sophistication

Henrique Gomes

Symmetry is often treated in philosophy of physics as an interpretive problem. A particularly lively dispute concerns local symmetries: do they indicate surplus structure that ought to be expunged, or are they merely a harmless redundancy? One influential response favours the second option for certain theories – those dubbed internally sophisticated. And indeed, in much of physics practice, local symmetries are left implicit: one simply works "up to isomorphism” without pausing over invariance. But not always. In some settings, local symmetry and invariance become pressing practical concerns for physicists. Yet philosophical discussions of sophistication have paid little sustained attention to when, and why, this happens. Surveying textbook general relativity (GR) and gauge theory, I identify the settings in which diffeomorphism invariance or gauge invariance must be handled explicitly. (Here a setting is a choice of representational framework or background assumptions within which one formulates and uses the theory – for instance, linearisation, an initial-value formulation, or a Hamiltonian $3+1$ formalism.) I propose an operational criterion – background-relative sophistication (BRS) – and argue that it accounts well for the pattern: it marks just where symmetry can stay implicit and where it must be made explicit. Quantum and subsystem settings raise a further difficulty: there, certain tasks (superposition and gluing) force symmetry into view even for theories that are BRS.
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Optics

Surface defects in carbon-doped hexagonal boron nitride for negative-contrast direct laser writing

Dmitrii Litvinov, Virgil Gavriliuc, Magdalena Grzeszczyk et al. (+5 more)

Radiative defects in hexagonal boron nitride (hBN) are active in a broad spectral range from deep ultraviolet to near-infrared wavelengths. Representatives of these defects act as bright single photon sources, spin-1 systems, and multiproperty atomic-scale sensors. They are predominantly investigated in bulk hBN films, where defects are decoupled from surface and interfacial effects. Here, we demonstrate a novel class of surface defects optically active in the green/yellow visible spectral range, which exhibit photophysical properties distinct from their bulk counterparts. High-power resonant laser illumination quenched the emission from the ensemble of such defects, which was attributed to a light-driven structural reconfiguration. The quenched defects were found to recover their emissive capabilities via a thermal cycling process, revealing an activation energy of 24.5 meV for the structural transition. Alternatively, permanent quenching of the defects was triggered by surface chemistry, involving lithiation-enabled attachment of functional groups. These mechanisms were utilized to realize negative-contrast direct laser writing, designing arbitrary geometric emissive patterns on demand in a microscopic configuration. The surface-active radiative centers in hBN appear particularly attractive for exploring environmental sensitivity, surface science, and coupling to photonic structures or electronic devices by taking unique advantage of the two-dimensional characteristics of the host lattice.
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All authors Dmitrii Litvinov, Virgil Gavriliuc, Magdalena Grzeszczyk, Kristina Vaklinova, Kenji Watanabe, Takashi Taniguchi, Kostya S. Novoselov, Maciej Koperski

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

Unprecedented Multipoint Observation of Spatially Varying ICME Turbulence of Different Ages during October 2024 Extreme Solar Storm at 1 AU

Shibotosh Biswas, Ankush Bhaskar, SG Abitha et al. (+4 more)

Understanding turbulence in interplanetary coronal mass ejections (ICMEs) is fundamental to space plasma research and critical for assessing the impact of space weather on geospace. Turbulence governs energy cascade, plasma heating, magnetic reconnection, and solar wind magnetosphere coupling, thereby influencing both ICME evolution and geoeffectiveness. While previous event based and statistical studies have examined ICME turbulence and its radial evolution in great detail, no significant measurements of ICME magnetic turbulence at a single vantage point have been obtained from multiple observatories separated azimuthally. Here, we present the first multipoint analysis of magnetohydrodynamic (MHD) turbulence across ICME plasma regions, using four spacecraft at the Sun-Earth L1 point, separated by 80 RE (mesoscale) along the dawn-dusk direction. Using high-resolution magnetic field observations from ISRO's Aditya L1, NASA's Wind and ACE, and NOAA's DSCOVR, we analyze turbulence associated with the October 10, 2024, solar storm, which triggered the second strongest geomagnetic storm of solar cycle 25. Our results reveal significant variability and differing turbulence maturity across small separations, supported by analysis of field-aligned and perpendicular magnetic-field cascades, indicating strong anisotropies. Sheath turbulence is substantially modified by shock induced energy injection. Evidence of compressible turbulence and plasma energization at the flux rope interaction region indicates that internal processes, such as magnetic reconnection, strongly influence ICME plasma evolution, highlighting pronounced spatial variability in turbulence and plasma states observed by multiple L1 monitors near Earth and underscoring their potential role in space weather impacts.
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All authors Shibotosh Biswas, Ankush Bhaskar, SG Abitha, Omkar Dhamane, Sanchita Pal, Dibyendu Chakrabarty, Vipin K Yadav

Classical Physics

Description of 4 Spacecraft, Moving on Elliptic Kepler Orbits

Vladimir P. Zhukov, Nikolai K. Iakovlev, Alexander A. Bochkarev et al. (+4 more)

The four-spacecraft formation is essential for measurements of various physical fields. The use of this formation on substantially elliptical heliocentric Kepler orbits allows measuring gradients of gravitation field in Solar system. The accuracy of the measurements will be sufficient to confirm or to refute modified theories of gravity. In this paper a new approach for the description of this formation is presented. The analytical solutions of the linearized motion equations are obtained. The distinctive feature of the solutions is that they use Cartesian coordinates of one of the spacecraft, termed the chief. These solutions have a clear physical meaning. It is shown, that the volume of a tetrahedron formed by spacecraft is a polynomial of 3-rd degree of Cartesian coordinates of the chief. The polynomial's coefficients are functions of initial spacecraft coordinates and velocities and linearly depend on time. If all spacecraft have the same periods of rotation around the Sun, the volume is a polynomial of 2-nd degree of the chief coordinates with time-independent coefficients. In this case the volume can be zeroed from 0 to 4 times per the period. Suggested approach can significantly simplify planning missions for measurements of various interplanetary fields.
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All authors Vladimir P. Zhukov, Nikolai K. Iakovlev, Alexander A. Bochkarev, Nikita E. Logvinenko, Sergei M. Kurchev, Vlas A. Karavaikin, Ivan A. Radko

Fluid Dynamics

Resolving Cryogenic and Hypersonic Rarefied Flows via Deep Learning-Accelerated Lennard-Jones DSMC

Ahmad Shoja Sani, Ehsan Roohi and Stefan Stefanov

Integrating the physically realistic Lennard–Jones (LJ) potential into Direct Simulation Monte Carlo (DSMC) remains challenging because the long-range potential complicates collision-rate definition and makes repeated scattering-angle evaluation expensive. This study develops an LJ–DSMC framework built around two methodological advances and a transport-level validation of the resulting collision kernel. First, a generalized collision-selection treatment is formulated for Bird's DSMC algorithms (DSMC1, DSMC1S, and DS2V) through a Variable Effective Diameter (VED) model obtained from local Chapman–Enskog viscosity matching. This viscosity-consistent pair-selection model provides a finite DSMC collision-rate closure for the LJ potential and is validated in helium and argon normal shocks, cryogenic supersonic Couette flow, and hypersonic cylinder flows. The results show agreement with VHS in high-temperature repulsive regimes, but reveal clear LJ effects, including reduced shear stress and larger cryogenic wakes, when attractive forces become important. Second, the computational bottleneck of the accepted LJ binary-scattering step is removed by training a Deep Operator Network (DeepONet) to predict the LJ deflection angle from high-fidelity scattering data, replacing the numerical Matsumoto–Koura integral while preserving the standard elastic post-collision update. The surrogate gives a bulk mean wrapped-angle error of \(1.6\times10^{-3}\,\mathrm{rad}\) and a 99th-percentile error of \(9.9\times10^{-3}\,\mathrm{rad}\), accelerates the collision subroutine by 40%, and reduces total wall time by 36%. Finally, the same DeepONet–LJ scattering kernel is tested beyond viscosity-controlled flows through diffusion benchmarks.
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Applied Physics · Cross-listed from cond-mat.mes-hall

Josephson-like magnetic tunnel junction – transition from classical to quantum regime

V.V.Yurlov, P.N. Skirdkov, K.A. Zvezdin et al. (+1 more)

We theoretically propose and analyze a Josephson-like magnetic tunnel junction (MTJ) structure that exhibits quantum spin dynamics analogous to those in superconducting Josephson junctions. By exploiting the isomorphism between the equations of motion for low-dissipation MTJs with easy-plane anisotropy and the Josephson phase dynamics, we construct a theoretical framework for realizing spintronic qubits. Within this framework, we identify the physical parameters – such as anisotropy constants, Gilbert damping, spin current amplitude, and geometric factors – that govern the transition from classical to quantum behavior. We show that different types of spintronic qubits, including analogs of charge, flux, and transmon superconducting qubits, can be implemented depending on the hierarchy of energy scales. A Hamiltonian formalism is developed for each regime, enabling an analytical treatment of the two-level quantum dynamics and estimation of coherence times. In particular, we demonstrate that the spin current can be used not only to excite but also to stabilize the qubit states through dissipation control. These findings provide a route toward integrating spintronic qubits into CMOS-compatible architectures and lay the groundwork for a fully spintronic platform for quantum computation.
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All authors V.V.Yurlov, P.N. Skirdkov, K.A. Zvezdin, A.K. Zvezdin

Chemical Physics

fix pimd/langevin: An Efficient Implementation of Path Integral Molecular Dynamics in LAMMPS

Yifan Li, Axel Gomez, Kehan Cai et al. (+10 more)

Path integral molecular dynamics (PIMD), which maps a quantum particle onto a fictitious classical system of ring polymers and propagates the "beads" of this extended classical system using molecular dynamics, is widely used to capture nuclear quantum effects (NQEs) in molecular simulations. Accurate PIMD calculations typically require a large number of beads and are therefore computationally demanding. While software packages such as i-PI offer comprehensive PIMD functionality, the high efficiency of simulations driven by machine learning interatomic potentials, such as Deep Potential (DP), calls for more efficient PIMD implementations that fully exploit modern massively parallel supercomputers. Here we present fix pimd/langevin, an efficient PIMD implementation in LAMMPS that supports commonly used features and leverages the Message Passing Interface architecture of LAMMPS to achieve high computational efficiency. We demonstrate the usage and validate the correctness of our code using liquid water as a representative example, and provide a comprehensive overview of the supported features. Then we discuss several important technical aspects of the implementation. Using DP simulations of water as a benchmark, we show that our implementation achieves several-fold acceleration compared to i-PI. Finally, we report strong and weak scaling results that demonstrate the favorable parallel performance of our code.
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All authors Yifan Li, Axel Gomez, Kehan Cai, Chunyi Zhang, Li Fu, Weile Jia, Yotam M. Y. Feldman, Ofir Blumer, Jacob Higer, Barak Hirshberg, Shenzhen Xu, Axel Kohlmeyer, Roberto Car

Medical Physics

Biocompatibility of Additively Manufactured Fe-AZ31 Biodegradable Composites for Craniofacial Implant Applications

Xue Dong, Samuel Medina, Sai Pratyush Akula et al. (+5 more)

Metallic plating systems composed of titanium and its alloys remain the standard treatment for craniofacial bony fixation but may require secondary removal due to infection, implant migration, or discomfort. Thus, biodegradable metallic implants may eliminate complications and secondary procedures while maintaining structural integrity. Our previous work demonstrated the fabrication of immiscible Fe-AZ31 composites via additive manufacturing with improved degradation kinetics over pure Iron. This study aimed to evaluate the in vitro and in vivo biocompatibility of Fe-AZ31 composites for potential craniofacial fixation applications. Pure iron (Fe), Mg alloy (AZ31) and Fe-AZ31 samples were fabricated for extract-based cytotoxicity testing using HFF-1 fibroblasts, L929 fibroblasts and hFOB osteoblasts. Metal extracts were prepared at a 3 cm^2/mL surface-to-volume ratio in complete media at 37C and cell viability was measured by live/dead assay after 24 and 72h exposure. For in vivo evaluation, Fe-AZ31, Fe, and Ti plates were implanted subcutaneously in wild type mice for 6 weeks, 3 and 6 months. Implant degradation, histologic response, hematology, and serum biochemistry were assessed. Fe-AZ31 extracts demonstrated >70% cell viability across all cell types at both timepoints with normal cell morphology and adhesion, whereas AZ31 extracts caused marked cytotoxicity associated with pronounced alkalization (pH 10). In vivo, Fe-AZ31 implants exhibited gradual surface corrosion accompanied by mild, transient inflammation and minimal capsule formation over time. No systemic toxicity was observed. Hematology and serum biochemistry remained within physiological limits. Additively manufactured Fe-AZ31 composites demonstrate acceptable biocompatibility and favorable tissue responses, supporting their development as resorbable metallic fixation devices for craniofacial reconstruction.
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All authors Xue Dong, Samuel Medina, Sai Pratyush Akula, Abby Chopoorian Fuchsman, Matthew W. Liao, Sophia Salingaros, Atieh Moridi, Jason A. Spector

Friday 13 February

Instrumentation and Detectors

Nuclear Data Needs for Microcalorimetry and Non-destructive Assay

Geon-Bo Kim, Begona Aranguren-Barrado, Shamsuzzoha Basunia et al. (+5 more)

Cryogenic microcalorimeters are state-of-the-art radiation detectors using superconducting and quantum technologies. They can resolve complex X-ray and low-energy {\gamma}-ray spectra with ultra-high energy resolution of an order of 10 eV at 100 keV, enabling high-precision non-destructive assay (NDA) analysis of nuclear materials containing uranium, plutonium and other actinides. With significant technical advancements in microcalorimetry technology, microcalorimeters are now deployable to end-users such as the International Atomic Energy Agency (IAEA) for improved NDA. However, the accuracy of microcalorimetry analysis can be limited by nuclear data. There are several cases that the current nuclear data obtained by conventional radiation detector technologies is not sufficient to support microcalorimetry analysis. To address the growing need for improved nuclear data in microcalorimetry, the U.S. Department of Energy Office of International Nuclear Safeguards hosted a workshop on Microcalorimetry and Nuclear Data (MiND) in June 2023. Microcalorimetry experts and users, and nuclear structure evaluators and managers, and program sponsors attended the workshop with the main objective of identifying a roadmap for priority nuclear data, stakeholders, partnerships, and opportunities. This paper summarizes the outcome of the MiND workshop, including the priority list of nuclear data for microcalorimetry and a multi-laboratory measurement campaign to improve such nuclear data.
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All authors Geon-Bo Kim, Begona Aranguren-Barrado, Shamsuzzoha Basunia, Daniel Becker, Lee Bernstein, Mark Croce, Joel Ullom, Andrew Voyles

Computational Physics

Using Neural Networks to Accelerate TALYS-2.0 Nuclear Reaction Simulations

Wilson Lin, Catherine E Apgar, Lee A Bernstein et al. (+7 more)

Recent efforts to improve the predictability of TALYS-2.0 calculated charged-particle residual product cross sections have focused on adjusting parameters related to the optical model potential and pre-equilibrium process. Although adjusted TALYS-2.0 outputs show marked improvements in agreement with experimental data over the default parameters, the procedure is generally time-consuming due to the need for sequential TALYS-2.0 calculations. Since the models and model parameters must be defined and constrained prior to adjustment, we show in this work that an artificial neural network can serve as a surrogate model to successfully predict TALYS-2.0 outputs within this domain of input parameters. No practical differences were observed in the trained model's performance between uniform random, Latin hypercube and Sobol sequence sampling for generating the training datasets. Once validated, trained neural network models were used to adjust TALYS-2.0 nuclear model parameters, where a multi-parameter fitting procedure was not only feasible but optimal for this process. The neural network approach is >1000x faster at generating residual product cross sections than using TALYS-2.0 directly, and a high-fidelity surrogate model could be implemented with about 1500 TALYS-2.0 files to achieve adjusted cross sections comparable to the previous publication.
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All authors Wilson Lin, Catherine E Apgar, Lee A Bernstein, YunHsuan Lee, Alan B McIntosh, Dmitri G Medvedev, Ellen M OBrien, Christiaan E Vermeulen, Andrew S Voyles, Jonathan T Morrell

Instrumentation and Detectors

Experimental Characterization of Bulk Micromegas for Development of Active Target Time Projection Chamber for Nuclear Astrophysics Studies

Pralay Kumar Das, Nayana Majumdar and Supratik Mukhopadhyay

A Micromegas-based active target Time Projection Chamber, namely Saha Active Target TPC (SAT-TPC), is under development at Saha Institute of Nuclear Physics for its application in nuclear astrophysics experiment to measure the branching ratio of the direct and sequential decay of the Hoyle state of $^{12}$C. A bulk Micromegas was characterized to optimize its operating parameters and its performance for $\alpha$-particle tracking was investigated using gas mixtures Ar + CO$_{2}$ (90:10) and Ar + i-C$_4$H$_{10}$ (95:5) at atmospheric pressure using 5.9~keV X-ray and 5.48~MeV $\alpha$-particles from radioactive sources. A hydrodynamic transport model was used to simulate the charge-deposit profile of the $\alpha$-particle track on the Micromegas readout and compared to the experimental data to complement the experimental measurement as well as validate the numerical model. A good agreement was observed that confirmed the suitability of the choice of the bulk Micromegas in the development of the SAT-TPC prototype and the hydrodynamic modelling of the detector dynamics
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Computational Physics · Cross-listed from cs.NE

Enhancing Heat Sink Efficiency in MOSFETs using Physics Informed Neural Networks: A Systematic Study on Coolant Velocity Estimation

Aniruddha Bora, Isabel K. Alvarez, Julie Chalfant et al. (+1 more)

In this work, we present a methodology using Physics Informed Neural Networks (PINNs) to determine the required velocity of a coolant, given inlet and outlet temperatures for a given heat flux in a multilayered metal-oxide-semiconductor field-effect transistor (MOSFET). MOSFETs are integral components of Power Electronic Building Blocks (PEBBs) and experiences the majority of the thermal load. Effective cooling of MOSFETs is therefore essential to prevent overheating and potential burnout. Determining the required velocity for the purpose of effective cooling is of importance but is an ill-posed inverse problem and difficult to solve using traditional methods. MOSFET consists of multiple layers with different thermal conductivities, including aluminum, pyrolytic graphite sheets (PGS), and stainless steel pipes containing flowing water. We propose an algorithm that employs sequential training of the MOSFET layers in PINNs. Mathematically, the sequential training method decouples the optimization of each layer by treating the parameters of other layers as constants during its training phase. This reduces the dimensionality of the optimization landscape, making it easier to find the global minimum for each layer's parameters and avoid poor local minima. Convergence of the PINNs solution to the analytical solution is theoretically analyzed. Finally we show the prediction of our proposed methodology to be in good agreement with experimental results.
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All authors Aniruddha Bora, Isabel K. Alvarez, Julie Chalfant, Chryssostomos Chryssostomidis

Chemical Physics

UBio-MolFM: A Universal Molecular Foundation Model for Bio-Systems

Lin Huang, Arthur Jiang, XiaoLi Liu et al. (+8 more)

All-atom molecular simulation serves as a quintessential “computational microscope” for understanding the machinery of life, yet it remains fundamentally limited by the trade-off between quantum-mechanical (QM) accuracy and biological scale. We present UBio-MolFM, a universal foundation model framework specifically engineered to bridge this gap. UBio-MolFM introduces three synergistic innovations: (1) UBio-Mol26, a large bio-specific dataset constructed via a multi-fidelity “Two-Pronged Strategy” that combines systematic bottom-up enumeration with top-down sampling of native protein environments (up to 1,200 atoms); (2) E2Former-V2, a linear-scaling equivariant transformer that integrates Equivariant Axis-Aligned Sparsification (EAAS) and Long-Short Range (LSR) modeling to capture non-local physics with up to ~4x higher inference throughput in our large-system benchmarks; and (3) a Three-Stage Curriculum Learning protocol that transitions from energy initialization to energy-force consistency, with force-focused supervision to mitigate energy offsets. Rigorous benchmarking across microscopic forces and macroscopic observables – including liquid water structure, ionic solvation, and peptide folding – demonstrates that UBio-MolFM achieves ab initio-level fidelity on large, out-of-distribution biomolecular systems (up to ~1,500 atoms) and realistic MD observables. By reconciling scalability with quantum precision, UBio-MolFM provides a robust, ready-to-use tool for the next generation of computational biology.
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All authors Lin Huang, Arthur Jiang, XiaoLi Liu, Zion Wang, Jason Zhao, Chu Wang, HaoCheng Lu, ChengXiang Huang, JiaJun Cheng, YiYue Du, Jia Zhang

Physics and Society

Social Contagion and Bank Runs: An Agent-Based Model with LLM Depositors

Chris Ruano and Shreshth Rajan

Digital banking and online communication have made modern bank runs faster and more networked than the canonical queue-at-the-branch setting. While equilibrium models explain why strategic complementarities generate run risk, they offer limited guidance on how beliefs synchronize and propagate in real time. We develop a process-based agent-based model that makes the information and coordination layer explicit. Banks follow cash-first withdrawal processing with discounted fire-sale liquidation and an endogenous stress index. Depositors are heterogeneous in risk tolerance and in the weight placed on fundamentals versus social information, communicating on a heavy-tailed network calibrated to Twitter activity during March 2023. Depositor behavior is generated by a constrained large language model that maps each agent's information set into a discrete action and an optional post; we validate this policy against laboratory coordination evidence and theoretical benchmarks. Across 4,900 configurations and full LLM simulations, three findings emerge. Within-bank connectivity raises the likelihood and speed of withdrawal cascades holding fundamentals fixed. Cross-bank contagion exhibits a sharp phase transition near spillover rates of 0.10. Depositor overlap and network amplification interact nonlinearly, so channels weak in isolation become powerful in combination. In an SVB, First Republic, and regional bank scenario disciplined by crisis-era data, the model reproduces the observed ordering of failures and predicts substantially higher withdrawal rates among uninsured depositors. The results frame social correlation as a measurable amplifier of run risk alongside balance-sheet fundamentals.
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Physics and Society

Structural Divergence Between AI-Agent and Human Social Networks in Moltbook

Wenpin Hou and Zhicheng Ji

Large populations of AI agents are increasingly embedded in online environments, yet little is known about how their collective interaction patterns compare to human social systems. Here, we analyze the full interaction network of Moltbook, a platform where AI agents and humans coexist, and systematically compare its structure to well-characterized human communication networks. Although Moltbook follows the same node-edge scaling relationship observed in human systems, indicating comparable global growth constraints, its internal organization diverges markedly. The network exhibits extreme attention inequality, heavy-tailed and asymmetric degree distributions, suppressed reciprocity, and a global under-representation of connected triadic structures. Community analysis reveals a structured modular architecture with elevated modularity and comparatively lower community size inequality relative to degree-preserving null models. Together, these findings show that AI-agent societies can reproduce global structural regularities of human networks while exhibiting fundamentally different internal organizing principles, highlighting that key features of human social organization are not universal but depend on the nature of the interacting agents.
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Physics and Society

Cooperative Game Theory Model for Sustainable UN Financing: Addressing Global Public Goods Provision

Labib Shami and Teddy Lazebnik

This study introduces a novel cooperative game theory model designed to improve the United Nations' current funding mechanisms, which predominantly rely on voluntary contributions. By shifting from a Nash equilibrium framework, where member states act in self-interest, to a cooperative model, the proposed approach aligns each country's financial contributions with the benefits they derive from UN activities. The model ensures a more sustainable and equitable system by introducing personalized pricing based on derived utility. Using agent-based simulations, the research demonstrates that the suggested approach increases global utility, reduces free-rider issues, and creates a more efficient resource allocation system. The findings suggest that the proposed model can optimize UN funding, ensuring a more stable and effective framework for global public goods provision, while considering the varying economic capacities of member states. Further research is recommended to assess the political viability of the model.
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Space Physics

Leveling of MHD turbulence imbalance in shear flows

M. Kavtaradze, G. Mamatsashvili, G. Chagelishvili et al. (+1 more)

We investigate magnetohydrodynamic (MHD) turbulence in plane shear flows with a streamwise background magnetic field in the super-Alfvénic regime, i.e., when the flow velocity is larger than the local Alfvén speed. In this regime, turbulence is energetically supplied by large-scale shear of the flow via transient, or non-modal amplification of Alfvén waves, which are the building blocks of MHD turbulence, and streamwise-uniform, mostly nonmagnetic modes. We show that shear reduces turbulence imbalance, driving the system toward a balanced state – the energies of counter-propagating Alfvén waves become essentially equal, even for an initially perfectly imbalanced Alfvénic turbulence. This balancing occurs due to the shear-induced linear non-modal dynamics of Alfvén waves – their non-modal growth, resulting in over-reflection, and coupling between counter-propagating wave branches. Because of its linear origin, this process of balancing of MHD turbulence by shear is fundamentally different from the nonlinear processes operating in standard MHD turbulence in the absence of a mean shear flow. It can have direct implications for understanding the balanced/imbalanced nature of MHD turbulence in shear regions of the solar wind.
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All authors M. Kavtaradze, G. Mamatsashvili, G. Chagelishvili, E. Uchava

History and Philosophy of Physics · Cross-listed from eess.SP

Sub Specie Aeternitatis: Fourier Transforms from the Theory of Heat to Musical Signals

Victor Lazzarini

J. B. Fourier in his Théorie Analytique de la Chaleur of 1822 introduced, amongst other things, two ideas that have made a fundamental impact in fields as diverse as Mathematical Physics, Electrical Engineering, Computer Science, and Music. The first one of these, a method to find the coefficients for a trigonometric series describing an arbitrary function, was very early on picked up by G. Ohm and H. Helmholtz as the foundation for a theory of musical tones. The second one, which is described by Fourier's double integral, became the basis for treating certain kinds of infinity in discontinuous functions, as shown by A. De Morgan in his 1842 The Differential and Integral Calculus. Both make up the fundamental basis for what is now commonly known as the Fourier theorem. With the help of P. A. M. Dirac's insights into the nature of these infinities, we can have a compact description of the frequency spectrum of a function of time, or conversely of a waveform corresponding to a given function of frequency. This paper, using solely primary sources, takes us from the physics of heat propagation to the modern theory of musical signals. It concludes with some considerations on the inherent duality of time and frequency emerging from Fourier's theorem.
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Fluid Dynamics

Higher-order mean velocity profile in the convective atmospheric boundary layer

Chenning Tong, Davoud Pourabdollah, Kirill Barskov et al. (+1 more)

The higher-order mean velocity profile in the convective atmospheric boundary layer (CBL) is derived using the method of matched asymptotic expansions. The universal expansion coefficients are obtained using field measurement data. The profile accounts for the departures from the (leading-order) log law and local-free-convection scaling as well as the deviations from the Monin-Obukhov Similarity theory (MOST). Invoking MOST and the Multipoint Monin-Obukhov similarity theory, the perturbation equations are obtained from the Reynolds-stress, potential-temperature flux and potential temperature-variance budget equations and the mean momentum and mean potential temperature equations. The small parameters with the most impact in the equations are $(-z_i/L)^{-4/3}$, $(-z_i/L)^{-2/3}$ and $-h_0/L$, where $z_i$, $L$ and $h_0$ are the inversion height, the Obukhov length and the roughness height, respectively. Tong and Ding (J.~Fluid Mech. 2020) have identified the three-layer structure of the CBL In the present work, asymptotic matching between the outer and inner-outer layers also results in higher-order expansion terms. The expansion coefficients are obtained using measurement data from the recent M$^2$HATS field campaign. Comparisons between the expansions and the measurement show excellent agreement. The higher-order asymptotic expansions show that the convective logarithmic friction law derived by Tong and Ding (2020) is valid to at least the second order. The predicted friction law also agrees well with measurements. The higher-order mean velocity profile can provide improved accuracy over empirical profiles.
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All authors Chenning Tong, Davoud Pourabdollah, Kirill Barskov, Mengjie Ding

Fluid Dynamics

The Unsteady Taylor–Vortex Dynamo is Fast

Liam O'Connor, Daniel Lecoanet, Geoffrey M. Vasil et al. (+6 more)

Astrophysical and geophysical fluids commonly generate organized magnetic fields, despite having enormous magnetic Reynolds numbers $\rm{Rm}$ and abundant small-scale turbulence. Flow-induced dynamo action produces these fields, with the “kinematic dynamo problem” devoted to determining the rate at which a flow exponentially amplifies weak magnetic fields. However, previous studies on high-Rm kinematic dynamos have generated flows via imposed volumetric forcing or oscillatory boundary conditions. In this letter, we investigate a system with three important attributes: realistic flow conditions, fast dynamo action (operational for $\rm{Rm}\to\infty$), and a subharmonic spatio-temporal structure. We show that unsteady Taylor–vortex flow, a regime observed in laboratory experiments, gives rise to fast dynamos with time and length scales twice those of the flow at high $\rm{Rm}$. By numerically integrating a Floquet system driven by periodic oscillations of Taylor vortices, we solve the kinematic dynamo problem up to $\rm{Rm} = 3.2 \cdot 10^6$, calculating the dynamo's growth rate as a function of Rm and streamwise wavenumber. We find the onset of instability and compute Finite-Time Lyapunov Exponents, which identify the regions of Lagrangian chaos required for fast dynamo action. To our knowledge, unsteady Taylor–vortex flow produces the most physically motivated fast dynamo to date.
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All authors Liam O'Connor, Daniel Lecoanet, Geoffrey M. Vasil, Kyle C. Augustson, Florentin Daniel, Evan H. Anders, Keaton J. Burns, Jeffrey S. Oishi, Benjamin P. Brown

Physics and Society · Cross-listed from econ.GN

Endogenous Epistemic Weighting under Heterogeneous Information

Enrico Manfredi

Collective decision-making requires aggregating multiple noisy information channels about an unknown state of the world. Classical epistemic justifications of majority rule rely on homogeneity assumptions often violated when individual competences are heterogeneous. This paper studies endogenous epistemic weighting in binary collective decisions. It introduces the Epistemic Shared-Choice Mechanism (ESCM), a lightweight and auditable procedure that generates bounded, issue-specific voting weights from short informational assessments. Unlike likelihood-optimal rules, ESCM does not require ex ante knowledge of individual competences, but infers them endogenously while bounding individual influence. Using a central limit approximation under general regularity conditions, the paper establishes analytically that bounded competence-sensitive monotone weighting strictly increases the mean quality of the aggregate signal whenever competence is heterogeneous. Numerical comparisons under Beta-distributed and segmented mixture competence environments show that these mean gains are associated with higher signal-to-noise ratios and large-sample accuracy relative to unweighted majority rule.
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