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Physics Physics

physics Watch Physics

Monday 10 August

Chemical Physics

Decoding Transient X-ray Absorption Spectra of Acetylacetone With Multireference Algebraic Diagrammatic Construction Theory

Bennett W. Clark, Donna H. Odhiambo, Haden Dickerson et al. (+1 more)

Time-resolved X-ray absorption spectroscopy (TR-XAS) offers an element- and site-specific probe of coupled electronic and nuclear dynamics, but its interpretation requires methods that can treat multiconfigurational excited states across nonequilibrium nuclear ensembles. Here, we report time-resolved simulations of the acetylacetone (AcAc) transient X-ray absorption spectra by combining surface-hopping dynamics from complete active space second-order perturbation theory with multireference algebraic diagrammatic construction (MR-ADC). The simulated 20-200 fs spectra show a good agreement with experimental measurements and reveal that the TR-XAS response is governed by continuously evolving distributions of molecular geometries on the singlet potential energy surfaces (S2 and S1). In particular, absorption at 279.5-281.5 eV is enhanced for transient, nearly symmetric proton-sharing configurations, whereas the 284-286 eV profile reflects geometry-dependent C1s excitations modulated by proton transfer, bond alternation, and ring opening. For the long-time T_1 spectrum (7-10 ps), the principal features near 281.4 and 283.8 eV are assigned to central C 1s excitations into low-lying triplet pi-orbitals. Together, our simulations provide a more complete mechanistic picture of AcAc photorelaxation by directly linking ultrafast carbon K-edge signals to proton transfer, skeletal reorganization, internal conversion, and triplet formation.
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All authors Bennett W. Clark, Donna H. Odhiambo, Haden Dickerson, Alexander Yu. Sokolov

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

Sampling Free Energy Landscapes of Ionic Colloidal Crystal Systems using Machine-Learned Proxy Collective Variables

Michael S. Chen, Stefano Sacanna and Glen M. Hocky

Charged colloids coated with a polymer brush can be designed to preferentially self-assemble into different crystal structures by varying easy-to-tune experimental conditions. For a given set of conditions, we have observed in experiments and simulations a distribution of thermodynamically (meta)stable self-assembled crystal structures. Properly quantifying the free energy landscape of these colloidal systems is essential for rationally choosing conditions to preferentially target particular crystal structures. For some of the structures we have formed, standard crystalline order parameters are not able to differentiate between crystals or between crystals and amorphous aggregates. We show that local environment similarity descriptors are able to distinguish the relevant metastable states, but are too expensive for use in biased MD simulations. Here, we adopt an approach from machine-learned interaction potentials showing that SE(3)-equivariant transformer networks can serve as an efficient-to-evaluate machine-learned proxy. As a result, we can compute the relative free energies of accessible colloidal structures as a function of different experimentally-relevant physical knobs that can steer our system between two observed crystal types. As an example application, we then show how changing surface potentials of positive and negative colloids while maintaining the same attractive energy can shift which crystal structure is favored.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG

Deep Learning Imputation of Missing Radius of Maximum Winds (Rmax) Values in Tropical Cyclone Best-Track Data

Swastik Agrawal, Nishkal Hundia, Ziyue Liu et al. (+1 more)

Probabilistic coastal hazard assessments require accurate characterization of tropical cyclone (TC) parameters, yet datasets often contain missing records for the radius of maximum winds (Rmax), a key variable in Joint Probability Method analyses. This study evaluates data-driven approaches for Rmax imputation, including one-dimensional Convolutional Neural Networks (1DCNNs), Long Short-Term Memory (LSTM) networks, and conventional machine learning models. We examine physics-informed input augmentation, temporal modeling, and transfer learning using synthetic RAFT and STORM datasets for pre-training and observational IBTrACS data for fine-tuning. Including the radius of 34-knot winds (R34) substantially improves performance across all model types. Temporal models achieve higher average correlations than non-temporal models despite using approximately an order of magnitude fewer samples, indicating better preservation of relative Rmax variability across storms. This advantage is more pronounced when R34 is unavailable, suggesting temporal information can partially compensate for missing storm-size predictors. Transfer learning does not improve performance, likely because synthetic datasets have lower and less variable Rmax distributions than IBTrACS. These findings demonstrate the potential of temporal deep learning for reconstructing incomplete TC records and highlight the importance of physics-informed inputs, observational data availability, and distributional consistency in coastal hazard assessment.
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All authors Swastik Agrawal, Nishkal Hundia, Ziyue Liu, Michelle Bensi

Accelerator Physics

Thermal Design and Experimental Validation of a Water-Cooled Bimetallic Minichannel Beam Dump for High-Power Heavy-Ion Accelerators

J. Song, N. Bultmann, M. Reaume et al. (+6 more)

Efficient thermal management of beam-intercepting devices is essential for high-power heavy-ion accelerators,where intense and localized energy deposition can limit primary beam power and operational reliability. This work presents the thermal design and experimental validation of a water-cooled bimetallic minichannel beam dump developed for the Facility for Rare Isotope Beams (FRIB), a leading experimental nuclear physics facility. The design integrates three key thermal features: a tilted absorber geometry to reduce local heat flux, a CuCrZr/Al2219 bimetallic structure to enhance heat spreading while maintaining water-side compatibility, and 2-mm-wide minichannels to achieve high convective heat removal. A conjugate thermal model was developed to predict surface temperature, internal temperature gradients, bimetallic-interface temperature, coolant temperature rise, and thermal margin under representative beam-loading conditions. The prototype was validated in vacuum ($\approx$5$\times 10^{-4}$ torr) using a 17-keV electron beam. Surface temperatures were measured by infrared thermography, and internal temperatures were measured using embedded thermocouples. The calculated surface temperature distributions were generally consistent with the measurements within the experimental uncertainty of 4$\%$ in absolute temperature for central beam irradiation, while internal temperature measurements showed reasonable agreement within 15$\%$, mainly due to uncertainties in thermocouple placement and beam-position calibration. The validated model confirms that the minichannel beam dump can maintain absorber temperatures within the design limit under intermediate-power FRIB operating conditions. These results demonstrate the effectiveness of bimetallic minichannel cooling for compact, high-heat-flux beam dump systems in heavy-ion accelerator facilities.
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All authors J. Song, N. Bultmann, M. Reaume, M. Patil, R. Quispe-Abad, W. Franklin, S. I. Eom, E. Wakai, M. Vargas Vallejo

Optics

A fully integrated dispersion-managed femtosecond mode-locked laser

Xurong Li, Xuan Yang, Zheru Qiu et al. (+7 more)

Femtosecond lasers underpin applications ranging from material processing to corneal surgery, while their regular pulse trains form optical frequency combs that have revolutionized timekeeping, spectroscopy, and metrology. On-chip optical frequency combs, such as Kerr microcombs, have enabled high-repetition-rate applications in optical communications and microwave photonics. However, integrated chip-scale sources operating at low repetition rates (100 MHz to 1 GHz), crucial for high peak intensities, remain elusive, as existing devices typically operate well beyond 10 GHz. Here, we demonstrate a self-starting, photonic integrated mode-locked laser based on a dispersion-managed architecture that accesses this regime. The laser combines erbium-implanted silicon nitride gain waveguides, integrated chirped Bragg gratings, and a semiconductor saturable absorber mirror to generate optical pulses with repetition rates from 0.5 to 1.2 GHz, pulse durations as short as 300 fs, and mode-locking thresholds down to 27.3 mW. The output forms a passively stable optical frequency comb with a comb-line drift below 1% of the repetition rate, surpassing the stability of commercial fiber lasers by two orders of magnitude. Leveraging this ultra-low threshold, we achieve complete hybrid integration by co-packaging the laser with a telecom-grade 980-nm III-V pump diode chip inside a compact photonic module. The resulting electrical-in/optical-out module delivers turnkey, stable mode-locked pulses, providing a compact, low-power, and vibration-insensitive foundry-compatible platform for field-deployable optical metrology and precision sensing.
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All authors Xurong Li, Xuan Yang, Zheru Qiu, Jiale Sun, Xinru Ji, Jianqi Hu, Grigorii Likhachev, Yichi Zhang, Ulrich Kentsch, Tobias Kippenberg

Optics

Scalable laser micro- and nanostructuring of mould inserts for functional injection-moulded polymer surfaces

Petr Hauschwitz, Elena Čižmárová, Jiří Bobek et al. (+10 more)

Functional polymer surfaces with tailored wettability, antibacterial and adhesion properties are increasingly required in medical, packaging and consumer applications. Laser structuring of steel mould inserts followed by injection moulding offers a scalable manufacturing route, but conventional single-beam texturing has limited throughput. Here, we present a selective acceleration strategy that applies different laser techniques to micro- and nanostructuring. Deep microhole drilling was accelerated up to 20-fold by operating an ultrashort-pulse fibre laser at a repetition rate of 1 MHz in single-beam mode. For laser-induced periodic surface structures (LIPSS), line-beam shaping with a spatial light modulator increased productivity by 35-fold, reaching processing speeds above 100 cm$^2$ min$^{-1}$ while retaining sub-micrometre fidelity. Replication experiments with polypropylene (PP), PA66 and ABS confirmed successful transfer of micro- and nanostructures, with PP showing the highest fidelity. Vacuum-assisted injection moulding increased replicated feature height by 56–283 percent. All laser-textured PP surfaces showed higher static water contact angles than the untreated reference, reaching approximately $134^\circ$ in the Wenzel regime. Structured PA66 surfaces reduced bacterial retention by up to 99.8 percent for E. coli and approximately 90 percent for S. aureus. Laser texturing also increased the shear strength of PP joints bonded with a non-optimised adhesive by up to 30-fold. This approach provides a practical, coating-free route to functional polymer components and helps bridge the gap between laboratory laser texturing and industrial injection moulding.
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All authors Petr Hauschwitz, Elena Čižmárová, Jiří Bobek, Hana Pištěková, Vladimír Sedlařík, Milan Kocáb, Radka Bičišťová, Martin Procházka, Jan Brajer, Jiří Mužík, Martin Smrž, Michal Chyla, Tomáš Mocek

Medical Physics · Cross-listed from eess.IV

Lost in k-Space: An Open-Source MR-Physics Escape Room

Sabine Melanie Räuber, Marta Brigid Maggioni and Francesco Santini

Introduction. Operating an MR scanner for technical and clinical research requires multidisciplinary competencies beyond MR physics, including safety management and teamwork. Gamification, particularly educational escape rooms, have been associated with improved motivation, engagement and knowledge retention in health professional education. Materials and Methods. We developed an MR-physics-themed educational escape room for the 41st Annual Meeting of the ESMRMB. Designed for teams of four with a time limit of 25 minutes, the room reproduced the atmosphere of an MR control room. The five puzzles covered the Larmor equation, sequence composition, MR safety and acoustical identification of MR sequences. Custom ESP32 electronics allowed the puzzles to communicate in real time with each other and with the game master Results. The room ran without technical interruptions and was played by 39 teams (approximately 160 participants); 12 solved it (escape rate 31%), with a median solution time of 21 minutes and 53 seconds. Early-career researchers acted as game masters. Discussion. The escape rate aligns with comparable activities targeting scientific audiences. Difficulty can be tuned by adjusting puzzle obscurity, component availability, required prior knowledge and mental leaps. A modified version could usefully supplement mandatory MR safety training. Code, schematics, machining files and documentation are released as open source.
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Fluid Dynamics · Cross-listed from math.NA

A novel compact scheme for second-order fluxes applied to the Spectral Difference method

Guido Lodato and Niccolò Tonicello

The discretization of second-order (viscous) terms in Discontinuous Spectral Element Methods (DSEMs) typically relies on an auxiliary gradient variable, whose treatment at element interfaces affects the accuracy and stability of the scheme. The Bassi-Rebay (BR1) formulation is attractive for its simplicity and parameter-free character, but suffers from sub-optimal convergence at even polynomial orders and requires an extended five-element stencil. Inspired by Huynh's Flux Reconstruction formulation, we develop a compact, fully-centered scheme for second-order fluxes within the Spectral Difference (SD) method. The proposed approach modifies the reconstruction of the auxiliary gradient using interface-dependent, one-sided continuous fluxes, reducing the stencil from five to three elements while preserving the centered and parameter-free nature of BR1. The formulation is developed in one dimension and extended to multiple dimensions. Temporal eigenanalysis is used to characterize its dissipation and dispersion properties, including the effects of interior penalty terms. Numerical tests consider the linear diffusion equation, an under-resolved localized Dirac's delta, the nonlinear porous medium equation, and implicit large-eddy simulations of the three-dimensional Taylor-Green vortex at $\mathrm{Re}=1600$ and $5000$. The compact scheme restores the expected convergence order for all polynomial degrees, including even orders, and reduces spurious oscillations in under-resolved and nonlinear regimes. It also remains stable in turbulent cases where the standard formulation fails, owing to improved damping of high-wavenumber numerical modes. The proposed approach provides an attractive compact alternative to BR1 for second-order fluxes in the SD method.
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Optics

In-situ integrated nonlocal Huygens metasurfaces enable robust vortex beams from multimode fibers

Mingke Jin, Jieyu Zheng, Chaoyang Wang et al. (+4 more)

A fundamental hurdle for multimode fiber (MMF) integrated photonics is achieving robust and deterministic wavefront shaping against fiber perturbation, which induces random modal interference and scrambles the real-space output into speckle patterns. Existing wavefront shaping methods typically rely on pixelated phase or polarization pre-compensation, rendering them highly sensitive to fiber deformation. Here, we show that in-situ integration of a silicon nonlocal metasurface onto an MMF end facet enables direct conversion of arbitrary speckle patterns into optical vortex beams without pre-compensation. The metasurface supports overlapped Mie resonances and nonlocal bound states in the continuum (BICs), yielding high-transmission bands by satisfying the generalized nonlocal Huygens condition. Through momentum-space coupling between MMF modes and Huygens-BICs with topological polarization-vortex nature, the output maintains doughnut-shaped profiles under static and dynamic perturbations, demonstrating exceptional robustness against fiber deformation. This approach provides a compact, alignment-tolerant platform for robust structured light generation in MMFs for endoscopy, optical trapping and communications.
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All authors Mingke Jin, Jieyu Zheng, Chaoyang Wang, Yuhao Fang, Gongkai Zhang, Min Qiu, Jingyi Tian

Fluid Dynamics

Memory-Generated Transport Geometry: Curvature, Holonomy, and Irreversibility

Mounir Kassmi

Memory is traditionally incorporated into transport theory as a constitutive correction acting on an already prescribed kinematic structure. Here we develop a different framework in which finite memory itself generates the geometry of transport. By reconstructing deformation from causal transport histories, the instantaneous velocity gradient is replaced by a memory-dependent transport connection whose ordered evolution gives rise to noncommutativity, curvature, and holonomy in transport-history space. We show that finite memory generates a nonvanishing geometric contribution to transport even in time-periodic, irrotational flows, providing a purely kinematic mechanism for irreversible Lagrangian transport without invoking vorticity, constitutive nonlinearities, stochastic forcing, or explicit symmetry breaking. We introduce an intrinsic curvature invariant, independent of the transport representation that measures the accumulated geometric structure generated by transport history. The framework predicts universal scaling governed by the dimensionless parameter (\omega\tau_m), identifies a characteristic memory scale (tau_c) separating rapid geometric accumulation from asymptotic saturation, and reveals a monotonically decreasing memory susceptibility with globally concave accumulation dynamics. Numerical simulations confirm these predictions and show that geometric irreversibility emerges through progressive curvature accumulation rather than resonance-driven amplification. These results establish finite memory as a generator of an intrinsic geometric structure rather than merely a modifier of dynamical evolution, revealing causal history as the microscopic origin of curvature, holonomy, and irreversible transport across a broad class of non-Markovian systems.
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Fluid Dynamics

Exact solution for the motion of a rigid particle with $\boldsymbol{S_4}$ and $\boldsymbol{C_{2v}}$ symmetry settling under gravity in a viscous fluid

Piotr Zdybel and Maria L. Ekiel-Jeżewska

We provide an exact and complete solution for the dynamics of a rigid particle of uniform density with $C_{2v}$ and $S_4$ symmetry, settling under gravity in a viscous fluid at a Reynolds number much smaller than unity. The $S_4$ symmetry renders the problem exactly integrable, with all orbits labelled by a single conserved quantity $0\le C\le 1$. We show that, for $0<C<1$, there are two different time scales, which lead to quasi-periodic evolution, with a significant time-dependent horizontal displacement. We obtain the tilt $\theta$ and spin $\psi$ Euler angles as periodic Jacobi elliptic functions of time, and the azimuthal angle $\phi$ through an incomplete elliptic integral of the third kind with a complex characteristic, which splits $\phi$ into a uniform drift and a strictly periodic modulation. The orientation period and the drift rate (corresponding to a constant angular velocity around the gravity direction) follow in a closed form. The vertical centre-of-mass displacement is obtained in terms of periodic in time incomplete elliptic integrals, and the periodic orbit-averaged settling velocity reduces to a single ratio of complete elliptic integrals. The horizontal component of the motion in the laboratory frame of reference is obtained exactly and algebraically in terms of all three Euler angles, so it is quasi-periodic. The horizontal component of the centre-of-mass position traces rosette-like, in general open curves confined by two concentric `envelope' circles. We determine very simple exact expressions for radii of both envelopes and demonstrate that they tend to infinity for a family of shapes with the rotation-translation coupling decreasing to zero. We also explain the origin of cusps at the rosette-like trajectory and provide a commensurability condition selecting strictly periodic rosettes.
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Data Analysis and Statistics · Cross-listed from nlin.PS

Rogue Wave Statistics from a Sparse Coherent Structure Decomposition

Yuchen He, Amin Chabchoub and Zhan Wang

While conventional rogue wave statistical models rely on linear or weakly nonlinear descriptions of random seas, we demonstrate experimentally that moderately or strongly nonlinear wave fields can be represented by sparse ensembles of coherent soliton-like packets. These packets exhibit log-normal amplitude distributions together with uniformly distributed phases and peak emergence times. This sparse coherent structure framework naturally leads to an extreme value description in which the probability of exceedance is governed by the tail of the coherent-structure amplitude distribution. The prediction is validated against laboratory hydrodynamic experiments across a variety of unidirectional sea states, showing good agreement with the experimental observations and comparing favourably with conventional statistical prediction models while retaining analytical simplicity. Our results provide a direct physics-based link between sparse coherent structures and rogue wave probabilities, with broader implications for nonlinear wave physics in optics, cold gases, and plasmas.
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Atomic Physics

Resonant photoionization dynamics during optical trapping of lithium atoms

K. Foster, S. Majumdar and D. Fischer

Photoionization induced by trapping and auxiliary laser fields is an inherent feature of many laser-cooling and optical trapping experiments, yet its microscopic dynamics are rarely investigated directly. In this work, we employ a reaction microscope implementing an event-by-event photoionization time retrieval technique to extend momentum-resolved photoelectron spectroscopy to continuous-wave laser–atom interactions. We investigate low-intensity multicolor photoionization of laser-cooled lithium atoms confined in an all-optical trap. Complete three-dimensional electron momentum distributions and kinetic-energy spectra recorded for different laser wavelengths and polarization configurations identify resonant excitation of the $5p$ and $5f$ states and reveal an additional ionization channel following spontaneous decay from the $5f$ to the $4d$ state. A pronounced polarization dependence of the photoionization yield is explained by magnetic-sublevel selection rules and the coherent interference of different virtual excitation pathways. These results demonstrate that reaction microscopy combined with event-by-event time reconstruction provides a powerful approach for investigating microscopic electronic dynamics in laser-cooled atomic systems and offers new insight into photoionization processes occurring during optical trapping.
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Optics

Direct Laser Interference Patterning of Functional Metal Surfaces: From Written Geometry to Functional Interfaces

Petr Hauschwitz

Direct laser interference patterning (DLIP) generates periodic micro- and nanoscale structures with increasing precision and throughput, yet similar geometries can produce fundamentally different functional responses. This review examines why morphology alone cannot predict friction, wetting and ice adhesion, bacterial response, cell behaviour, optical performance or electrochemical and photovoltaic function. DLIP is treated as a model system in which the optically prescribed geometry can be distinguished from the interface realised during processing. The written period is separated from relief depth, aspect ratio, hierarchical topography, surface chemistry, ageing and process history. Functional response is interpreted as a two-stage process: geometry creates the opportunity for interaction with an external agent, while the realised interface determines how that interaction becomes measurable performance under a specific interfacial state. A curated, metals-centred evidence base spanning tribology, wetting and anti-icing, antibacterial and biomedical surfaces, optics, electrochemistry, energy devices and manufacturing shows that period-depth coordinates alone rarely predict function across domains. Geometry remains highly transferable in optical systems and controlled mechanical contacts, whereas biological, state-dependent and device-level functions also depend on surface state, operating conditions and system architecture. The framework reconciles conflicting observations and identifies which variables are transferable and which remain context-dependent. Predictive DLIP surface engineering therefore requires identification of the interacting agent, separation of written geometry from the realised interface, isolation of variables governing interfacial coupling and evaluation through direct, mechanism-specific endpoints.
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Instrumentation and Detectors

Optimization studies of silicon remoTES cryogenic calorimeters

G. Angloher, M.R. Bharadwaj, A. Boehmer et al. (+42 more)

The remoTES design, developed within the COSINUS experiment, enables a broader range of materials to be operated as cryogenic calorimeters read out with Transition Edge Sensors (TESs). In this configuration, the TES is fabricated onto a separate chip and thermally coupled to the absorber via a gold (Au) link. The remoTES concept has been successfully tested on various target materials. To further enhance detector performance and to fully exploit the advantages of the remote coupling design a series of optimization studies has been conducted using silicon (Si) absorbers as benchmark. This work presents an evaluation of several measurements aimed at reducing the thermal boundary resistance and enhancing signal transmission across Si remoTES interfaces, specifically from the absorber to the phonon collector and from the phonon collector to the TES. By testing a new Au link design and three distinct phonon collector configurations, Au, copper, and aluminum (Al)/Au, we achieved a baseline resolution of (21.5 +/- 0.3)eV using the Al/Au phonon collector.
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All authors G. Angloher, M.R. Bharadwaj, A. Boehmer, S. Braun, M.R. Cababie, I. Colantoni, I. Dafinei, N. Di Marco, C. Dittmar, F. Ferella, F. Ferroni, S. Fichtinger, A. Filipponi, M. Friedl, D. Fuchs, L. Gai, M. Gapp, M. Heikinheimo, K. Heim, K. Huitu, M. Kellermann, R. Maji, M. Mancuso, L. Pagnanini, F. Petricca, S. Pirro, F. Proebst, G. Profeta, A. Puiu, F. Reindl, K. Schaeffner, J. Schieck, P. Schreiner, C. Schwertner, P. Settembri, K. Shera, M. Stahlberg, A. Stendahl, M. Stukel, C. Tresca, S. Yue, V. Zema, Y. Zhu, L. Ziegele, N. Zimmermann

Data Analysis and Statistics · Cross-listed from hep-ph

The Living Guide of Machine Learning for Particle Physics

Claudius Krause, Ramon Winterhalder, Matthew Feickert et al. (+1 more)

We started the Living Review of Machine Learning for Particle Physics (HEP-ML Living Review) in 2020 as a community-maintained, near-comprehensive bibliography of machine learning in particle physics. The field was then growing faster than any single researcher could follow, finding the relevant papers was hard, and a structured, continuously updated reference paid off immediately. Since then the literature has grown by more than an order of magnitude, the methods reach far beyond the classification and generation tasks of the early years, and the community has built its own ecosystem of topic-specific reviews, benchmark papers, and software frameworks. The original model no longer serves this field well, and we can no longer sustain it. We therefore change direction. We freeze the Living Review as an archival reference covering the literature up to 1 June 2026, where it remains a stable record of the first phase of HEP-ML. A new resource, the HEP-ML Living Guide, replaces it. It does not list everything. It curates, it annotates, and it points readers to foundational and representative work, so that researchers can find their way into a mature and rapidly diversifying field. In this article we explain why we make this change and how the new resource works.
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All authors Claudius Krause, Ramon Winterhalder, Matthew Feickert, Benjamin Nachman

Applied Physics

The Tilting Mode: A New Degree of Freedom for Magneto-Mechanical Resonator Sensors

Nora Timm, Florian Hartwig, Jonas Faltinath et al. (+3 more)

Magneto-mechanical resonators (MMRs) are an emerging class of passive, wireless sensors. Their torsional oscillation mode has recently been established for sensing and tracking applications. In this work, we report the identification and characterization of a second mechanical mode, the tilting mode, that provides sensitivity along an axis inaccessible to the torsional mode, opening up a new degree of freedom for tracking and sensing with a single MMR sensor. We derive an analytical model predicting the tilting frequency as a function of the geometric and magnetic parameters of the resonator, compare the tilting mode frequency to that of the torsional mode, and obtain a characteristic frequency ratio between the torsional and the tilting mode in the small angle approximation. Experimental characterization using three-axis excitation and detection confirms the mode's existence and its directional selectivity. Notably, the three-axis frequency response shows no observable cross-coupling between the torsional and the tilting mode. We further show that the tilting mode frequency follows the predicted dependence on magnet distance, confirming the analytical model and the mode's applicability for sensing, analogous to that of the torsional mode.
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All authors Nora Timm, Florian Hartwig, Jonas Faltinath, Sarah Reiss, Pascal Stagge, Tobias Knopp

Applied Physics

200 mm Wafer-Scale Monolithic 3D Integration of Atomic Layer-Deposited Oxide Semiconductors

Chang Niu, Linjia Long, Luqi Zheng et al. (+9 more)

Monolithic 3D (M3D) integration offers a pathway to overcome the scaling limits of conventional silicon complementary metal-oxide-semiconductor (CMOS) technology by extending dense vertical stacking of multifunctional logic and memory devices. Here, we demonstrate wafer-scale M3D integration of three tiers of atomic-layer-deposited (ALD) indium oxide (InOx)-based devices (>100,000 fabricated), including ferroelectric, enhancement-mode, and depletion-mode field-effect transistors, on 200 mm silicon wafers. We achieve threshold voltage standard deviation as low as 0.04 V, average electron mobility up to 91.6 cm2V-1s-1, and fully functional cross-tier circuits. A four-tier 3D computing-in-memory (CIM) accelerator targeting large language model workloads is developed using a custom InOx process design kit, delivering 1.4x to 2.9x speedup and comparable energy-delay product improvements over 2D baselines. These results establish ALD InOx M3D integration as a scalable and CMOS-compatible platform for next-generation artificial intelligence hardware and advanced electronics.
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All authors Chang Niu, Linjia Long, Luqi Zheng, Shuting Du, Jian-Yu Lin, Kisoo Nam, Zehao Lin, Chang Liu, Juanjuan Lu, Haiyan Wang, Haitong Li, Peide D. Ye

Applied Physics

A Superposition-Based Framework for Rapid Estimation of Arbitrary Antenna-Array Patterns

Amir Dayan, Nabeel Ali Khan, Inchara Lakshminarayan et al. (+4 more)

Antenna array theory is a well-established field. However, a systematic approach for fast pattern estimation in arrays with arbitrary antenna locations and orientations has not yet been developed. In this paper, based on simulated (or measured) radiation patterns of a single element, we present a Superposition-Based Framework (SBF) for numerically computing array radiation patterns in which the positions and orientations of the antenna elements can be readily modified. To validate the framework, a compact dual-layer circularly polarized patch antenna at 5.02 GHz (ESA's Celeste frequency) is designed and used as an array element in an 8-element ring antenna. Using the proposed framework and the single-element far-field pattern, the array radiation pattern is computed in 13s (excluding single-element simulation time), which is at least 50 times faster than the corresponding full-wave simulation while maintaining comparable accuracy. Comparisons with CST simulations show a peak E-field error of less than 0.5% for the intended polarization. Full-wave simulations are memory- and energy-intensive, and hence, impractical for larger arrays. The proposed SBF requires low computational power, making it energy-efficient and sustainable.
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All authors Amir Dayan, Nabeel Ali Khan, Inchara Lakshminarayan, Wahyudin Syam, Noori BniLam, William Whittow, Aakash Bansal

Computational Physics · Cross-listed from cs.LG

Hierarchical rank-evolving representation for physics-informed neural networks

Ruoyang Su, Xi-Le Zhao, Kun Li et al. (+1 more)

Recently, tensor-based physics-informed neural networks (T-PINNs) have received increasing attention. However, existing T-PINNs still face a fundamental challenge: they mainly rely on pre-specified low-rank tensor decompositions with manually tuned ranks, which limits their ability to capture the underlying structures of multivariate solution functions and hinders their practical deployment. To address this challenge, we propose a hierarchical rank-evolving (abbreviated as HRE) representation for multivariate functions, which endows us to faithfully capture the underlying structure of the targeted multivariate function accompanying with automatic rank determination. Concretely, in the hierarchical design of HRE representation, the target multivariate function is decomposed as a small-scale inner tensor with a set of univariate functions along each mode, where a customized tensor network decomposition can be readily deployed to capture the underlying structure of the small-scale inner tensor. In HRE representation, the crucial hyperparameters, ranks, can be adaptively revealed during the decomposition, freeing us from manual rank tuning and making HRE practically applicable to real-world problems. Besides, we build the HRE-PINNs correspondingly. Extensive numerical experiments, including high-dimensional static problems (Helmholtz equation and Poisson equation), nonlinear time-dependent problems (Klein-Gordon equation), and complex fluid-dynamics problems (flow mixing equation and Navier-Stokes equation), demonstrate that HRE-PINNs consistently outperform existing state-of-the-art approaches in terms of accuracy.
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All authors Ruoyang Su, Xi-Le Zhao, Kun Li, Liang Li

Physics and Society

The impact of the path ensemble on path percolation

Yunhao Ding, Andreas Münch and Renaud Lambiotte

Traffic-induced failures, from packet loss in communication networks to congestion breakdown in transport systems, occur when flows progressively exhaust the edges they traverse. Path percolation models this process by removing edges along sampled origin-destination paths. Existing work assumes locally tree-like networks and deterministic shortest-path routing, leaving unclear how path degeneracy and routing stochasticity affect fragmentation in the clustered networks typical of real systems. We introduce a generalised path-percolation framework where paths are drawn from a temperature-controlled routing ensemble interpolating between geodesic and noisy transport. We argue based on box-covering renormalisation and our numerical experiments that, for any finite routing horizon $C$, the process coarse-grains to ordinary mean-field percolation. Routing details affect non-universal quantities, especially the percolation threshold $p_c$, through the entropy of the load distribution and the capacity of finite clusters to accommodate flow. Load entropy therefore acts as a robustness measure for networks under path-based failures. When the routing horizon is tuned to the mean-field correlation length, $C=N^{1/3}$, within a source-uniform ensemble, the system enters a crossover regime with scaling exponents distinct from shortest-path percolation with infinite budget. In this regime, path elongation becomes decoupled in time from structural fragmentation: the characteristic path length reaches a growing maximum, associated with routing temperature, asymptotically ahead of the collapse of the giant component. These results clarify how microscopic routing organisation shapes macroscopic resilience, and identify path elongation as a measurable precursor of failure in communication and transport infrastructure.
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Optics

Femtosecond Engineering of PolyMethylPentene(PMP) Nonlinearity via NA, Spin/orbital angular momentum (OAM), and In-Situ SC Diagnostics

Siyang Zheng, Guangyu Zhu, Walter Perrie et al. (+4 more)

While femtosecond vortex beams are widely studied for photonic fabrication, how OAM affects third-order susceptibility, energy deposition, and structural symmetry in transparent polymers remains unclear. To address this gap, we investigate femtosecond vortex beam interactions with polymethylpentene (PMP) to establish OAM control over beam shaping and energy deposition in laser micromachining. A 775 nm femtosecond laser is frequency-doubled to 387.5 nm and phase-shaped by a reflective liquid crystal-spatial light modulator, with OAM imprinted via computer-generated holograms and independently controlled spin via a quarter-wave plate. Theoretical modeling of the tensorial nonlinear polarization, combined with systematic experiments on low-NA filamentation, supercontinuum spectroscopy using an advanced spectrometer, and high-NA inscription with NA = 0.4 and 0.7, reveals that the same $\chi^{(3)}$ tensor components govern all regimes. The transition from perturbative to dissipative behavior is determined solely by whether the local intensity exceeds the plasma formation threshold. Through an analytical framework based on the isotropic material model, the key innovation lies in identifying that $\chi_{1122}$ governs the energy deposition and plasma threshold, whereas $\chi_{1221}$ mediates the transverse nonlinear current and helicity-dependent asymmetry, thereby converting phase topology into permanent chiral structures. This enables OAM-controlled structuring with sub-micrometer feature sizes (approximately 0.43 $\mu$m diameter and approximately 200 nm$^2$ area) and localized intensities reaching $10^{14}$–$10^{15}$ W/cm$^2$, providing an engineering framework for deterministic fabrication of chiral waveguides and photonic devices through precise control of topological charge and focusing conditions.
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All authors Siyang Zheng, Guangyu Zhu, Walter Perrie, Dongzhi Wang, Runzhen Zhou, Juan Ignacio Ahuir-Torre, Puxiang Lai

Accelerator Physics

An accelerator-based source of high-intensity quantum-entangled annihilation gamma photons

Riad Suleiman

We present the concept and development of a novel accelerator-based source of high-intensity quantum-entangled 511 keV gamma-ray pairs produced through positron-electron annihilation. The source leverages the unique capabilities of the proposed Jefferson Lab positron facility to generate polarized, high-current positron beams with a well-defined time structure. These beams enable the production of entangled annihilation photons at intensities far exceeding those available from conventional radioactive sources. The resulting gamma-ray pairs can be characterized using Compton polarimetry techniques, providing a powerful platform for precision studies of quantum entanglement. The combination of high intensity, controllable polarization, and precise timing also opens new opportunities in medical imaging, materials science, quantum information science, and spintronics. Compared with traditional radioactive sources, the proposed system offers orders-of-magnitude higher photon flux, tunable beam parameters, and unprecedented control of the annihilation process. We discuss the source design, methods for entanglement characterization, potential applications, and future development directions.
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Physics Education

QTris: a pedagogical board game to teach Quantum Mechanics

Alessandro Amabile, Maria Bondani, Immacolata De Simone et al. (+3 more)

In this paper we introduce the new version of QTris, a board game designed to teach and learn Quantum Mechanics within the framework of Quantum Information and Computation. The key idea behind the game is that every game sequence simulates a process on a system of qubits. Thus, QTris can be effectively integrated as a pedagogical tool to teach Quantum Mechanics at high-school level following a two-state approach. After arguing in support of this latter approach, we describe QTris' basic rules and some of its possible extensions, emphasizing how the game mechanics puts in clear light key quantum concepts such as incompatibility, probabilistic measurement and unitary transformation. Moreover, we report on the results of a QTris-based educational activity which involved about 150 high-school students and provided encouraging preliminary indications that QTris can be a useful pedagogical platform to promote an immediate understanding of some key concepts of Quantum Mechanics.
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All authors Alessandro Amabile, Maria Bondani, Immacolata De Simone, Michela Nazzaro, Michele Viscardi, Alioscia Hamma

Chemical Physics

Nonadiabatic Forward-Flux Sampling of Rare Molecular Gas-Phase Ammonia Photodissociation

Madlen Maria Reiner, Johannes C. B. Dietschreit, Leticia González et al. (+1 more)

Simulating rare events in photochemistry by brute-force surface hopping is computationally prohibitive: most propagated trajectories either remain nonreactive or follow dominant relaxation channels, while the reaction of interest may occur with very low probability. Path sampling methods have long addressed this problem for ground-state dynamics, but their extension to nonadiabatic processes has so far been limited to low-dimensional analytical models. Here, we demonstrate that our recently developed nonadiabatic forward-flux sampling (NAFFS) method can be applied to efficiently simulate rare-events in full-dimensional molecular systems. As a representative benchmark, we investigate the rare molecular photodissociation channel of gas-phase ammonia, NH$_3$ + h$\nu \rightarrow$ NH + H$_2$. NAFFS samples reactive trajectories with the correct statistical weight, reproduces the reaction rate constant obtained in previous brute-force dynamical studies, provides direct access to mechanistic information through an averaged committor analysis, and reduces the simulation time per transition trajectory by up to three orders of magnitude. These results establish NAFFS as an efficient and statistically rigorous framework for investigating rare nonadiabatic processes in realistic molecular systems.
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All authors Madlen Maria Reiner, Johannes C. B. Dietschreit, Leticia González, Christoph Dellago

Optics

Impact of Terminal Noise on Polarization Rotation Vector for Sensing Applications

Mohammad M. Hosseini, Miquel Masanas, Giuseppe Paris et al. (+4 more)

State-of-Polarization sensing with coherent transponders enables wide-area geophysical monitoring over existing submarine cables, but its performance is limited by polarization noise from both the fiber and terminal hardware. This work investigates how terminal noise affects polarization rotation estimates derived from receiver equalizer coefficients and how it can obscure stochastic polarization drift used for sensing. We analyze Jones-matrix time series from two deployed receivers in the Sparkle Mediterranean link MedNautilus (approximately 2000 km and 450 km) and compare them with a laboratory back-to-back reference. Power Spectral Density (PSD) analysis reveals a low-frequency random-walk regime and a high-frequency white-noise floor, separated by a link-dependent corner frequency. The rotation innovation variance increases with link length, while the longest field link also shows elevated white noise consistent with accumulated amplifier and terminal contributions. Additionally, harmonic spectral components are observed, indicating a transponder-related artifact that should be considered in practical sensing applications.
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All authors Mohammad M. Hosseini, Miquel Masanas, Giuseppe Paris, Antonio Mecozzi, Alberto Marullo, Danilo Decaroli, Antonio Napoli

Computational Physics

Coordinate-Residual Physics-Driven Neural Network for Inverse Scattering Imaging

Yutong Du, Zicheng Liu, Bo Qi et al. (+2 more)

Electromagnetic inverse scattering is a nonlinear and ill-posed computational imaging problem, where accurate reconstruction is challenging due to measurement limitations, noise, and high computational costs, especially for 3-D imaging. Although physics-driven neural networks (PDNNs) reduce the dependence on labeled training data, existing accelerated PDNN frameworks often rely on preliminary reconstruction-based region selection, which may introduce instability when the selected region is inaccurate. In this paper, a coordinate-residual physics-driven neural network (CRPDNN) is proposed for 3-D electromagnetic inverse scattering. CRPDNN represents the unknown complex contrast distribution using normalized spatial coordinates and a residual convolutional network, whose parameters are optimized by enforcing consistency between the measured and model-predicted scattered fields. Unlike existing subregion-accelerated PDNN approaches, CRPDNN does not require a preliminary reconstruction, thereby avoiding dependence on its accuracy. For the reported noise-free 3-D synthetic cases, CRPDNN achieves an average relative error of 2.10%, compared with 7.97% for CSI and 3.99% for $L_{2/3}$-FBE-WCIE, while providing approximately 5.5- and 12.1-fold speedups over the two baselines, respectively. Additional 2-D comparisons further demonstrate its stability and computational efficiency relative to existing PDNN frameworks. CRPDNN also maintains reliable reconstruction performance under noisy measurements, and the 3-D Fresnel experiments further indicate its potential for practical imaging applications.
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All authors Yutong Du, Zicheng Liu, Bo Qi, Yali Zong, Peixian Han

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Magnetotransport evolution and nonlinear Hall effect in altermagnetic MnTe

Wei Zhou, Zhifeng Xue, Yunxing Li et al. (+6 more)

Hexagonal MnTe is a prototypical semiconducting altermagnet whose properties are heavily influenced by intrinsic disorder, yet how the resulting diverse transport regimes shape its magnetotransport behavior remains to be clarified alongside the role of relativistic spin-orbit coupling (SOC). Here, we present a systematic study of the anisotropic magnetoresistance (AMR), planar Hall effect (PHE), and nonlinear transport in MnTe bulk single crystals. Below the Néel temperature (TN ~ 304 K), the emergence of high-order harmonics in AMR and PHE within the high-temperature metallic regime reveals the interplay of magnetic order, crystalline symmetry, and SOC. At relatively lower temperatures, the disappearance of higher-order symmetries coincides with a transport crossover into the hopping conduction regime, suggesting that carrier localization diminishes the transport sensitivity to the Fermi-surface topology. In addition, we detect distinct second-order nonlinear Hall signals, providing evidence for a macroscopic inversion-asymmetric response in altermagnetic MnTe. Extending the investigations into the localized regime provides key insights into the subtle role of disorder and SOC in macroscopic charge transport. Our work thus underscores the necessity of exploring magnetotransport across diverse conducting regimes to comprehensively understand altermagnetic properties.
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All authors Wei Zhou, Zhifeng Xue, Yunxing Li, Nannan Tang, Ye Tao, Dingyong Zhong, Jiawei Luo, Donghui Guo, Huichao Wang

Atmospheric and Oceanic Physics

Identifying the large-scale synoptic drivers contributing to the Kerala floods using multivariate feature-based analysis

Marion P. Mittermaier

Parts of Kerala were hit by devastating floods three years in a row. This sequence was historically without precedent. This paper uses a multivariate object-based approach to examine the global forecasts of the Met Office Unified Model for the 2018, 2019 and 2020 monsoon seasons to identify and understand the large-scale synoptic drivers that led to the floods. Identifying similarities between synoptic drivers behind these flooding events was a key objective, as was understanding whether one could enhance predictability by using a multivariate approach for post-processing forecast output, using variables other than just precipitation, which is often inherently less predictable on its own. To this end event identification focused on the analyses first, and then on a day 5 forecast. The study found that the multivariate version of the Method for Object-based Diagnostic Evaluation (MvMODE) was able to successfully identify sequences of days in all three seasons corresponding to the event dates, which in combination, had flood-producing potential. This was achieved in both the analyses and in the 5-day forecasts, proving that a) the events share common synoptic drivers and b) there is inherent predictability which can be tapped into. The 5-day forecasts matched the analysed objects on each occasion, proving that the underlying large-scale drivers may be predictable into the medium-range. Based on the results, the paper proposes a conceptual synoptic pattern evolution which can help identify such events in future. The synoptic pattern has some similarities to atmospheric rivers in the mid-latitudes.
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Computational Physics · Cross-listed from math.NA

High-order fully discrete multi-entropy-stable and bound-preserving schemes for relativistic Euler equations

Linfeng Xu and Kailiang Wu

A discrete entropy inequality is the principal nonlinear stability estimate available for systems of conservation laws, and evaluating it presupposes a physically admissible state. So far, however, the two have been secured separately. Entropy-stable schemes are almost always semi-discrete, are built around one selected entropy pair, and take for granted the positivity of density and pressure that makes the entropy well defined in the first place, whereas bound-preserving limiters keep the solution admissible but deliver no entropy estimate. For the special relativistic Euler equations, the two cannot be separated at all, since the conservative-to-primitive map is implicit, and an inadmissible state therefore has no entropy to correct. Here we construct high-order discontinuous Galerkin and finite volume schemes that, to our knowledge, for the first time, are entropy stable in the fully discrete sense for an arbitrary prescribed finite family of convex entropy pairs, a property we call multi-entropy stability, and are provably admissible wherever an entropy is evaluated. All of this is achieved by a single cellwise projection, and neither conservation nor the design order is lost. The construction rests on relativistic causality, which bounds every characteristic speed by the speed of light. Consequently, the numerical viscosity can be fixed once for all states and all equations of state, and one two-point building block then serves the whole entropy family. Since only the convexity of the admissible set and this speed bound are used, the same route remains open for related systems. Finally, in computations with four equations of state, the schemes retain high-order accuracy close to vacuum, produce no inadmissible state in strong shocks, near-vacuum shock–vortex interaction or jets with Lorentz factor above $70$, and confirm the monotone decay of every enforced discrete entropy.
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