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Physics Physics

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Tuesday 21 April

Optics

Multi-slit time-reversed Young interference: source-space grating laws, quadratic-phase effects, and Talbot-like revivals

Jianming Wen

We develop a compact theory of time-reversed Young (TRY) interference beyond the symmetric two-slit geometry by considering equally spaced three-slit, finite $N$-slit, and infinite periodic slit arrays. In the TRY configuration, a point emitter illuminates the aperture, a position-fixed detector records the signal, and the response is reconstructed in source space by correlating the detector record with the source-coordinate label. We show that the three-slit case already reveals the essential new physics beyond two slits: a quadratic Fresnel phase survives, modifies the reconstructed interference law, and lifts the nominal dark fringes in the generic case. For a general equally spaced $N$-slit array, we identify the exact reconstructed response and show that the familiar textbook grating factor is recovered only when the quadratic phase is negligible, compensated, or reduced to a common phase across the array. In that ideal limit, the reconstructed peaks are source-space analogues of classical grating orders rather than outgoing diffraction beams. For an infinite periodic TRY array, we further show that the same discrete quadratic phase generates full and fractional Talbot-like revivals in source space, governed by a reciprocal-distance condition rather than the conventional Talbot propagation law. These results show that the symmetric two-slit TRY geometry is exceptional, while multi-slit TRY systems naturally combine source-space discrimination with sensitivity to aperture-wide phase structure and periodic-array revival physics.
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Optics

Electrically-injected room-temperature waveguide polariton laser

Hassen Souissi, Valentin Develay, Maksym Gromovyi et al. (+14 more)

Exciton-polariton lasers are coherent light sources which do not require the population inversion (transparency) condition to be fulfilled. They have been conceptualized at the end of the XXth century but until now they operate almost exclusively under optical injection, which severely limits the widespread integration of the polariton-based devices implemented so far. Here we tackle this issue by reporting an electrically-pumped exciton-polariton laser based on GaN and operating at room temperature in a mode-locked regime. The laser architecture is close to the geometry of commercial ridge-waveguide GaN lasers, but based on a bulk GaN active region instead of quantum wells. Unique features of polariton lasers are demonstrated, in particular the breakdown of the transparency condition, which enables our polariton lasers to operate even when only a small fraction (20%) of the cavity length is injected. Moreover, the large polaritonic gain allows for the operation of a short cavity length (60$\mu m$) compared to commercial lasers. From the very same sample, we also achieve polariton lasing under optical injection, confirming that the doped layers necessary for electrical injection do not prevent strong-coupling nor polariton lasing. Our results open a new perspective for polariton-based devices.
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All authors Hassen Souissi, Valentin Develay, Maksym Gromovyi, Edmond Cambril, Christelle Brimont, Laetitia Doyennette, Guillaume Malpuech, Dmitry Solnyshkov, Blandine Alloing, Sebastien Chenot, Mohamed Al-Khalfioui, Eric Frayssinet, Jean-Yves Duboz, Mingyang Zhang, Jesus-Zuniga Perez, Sophie Bouchoule, Thierry Guillet

Atmospheric and Oceanic Physics

Connecting the forward problem to the inverse problem in uncertainty quantification of Earth system models using fast emulators

Ethan YoungIn Shin, Baris Kale and Michael F. Howland

Quantifying and reducing uncertainty in Earth system model parameterizations is essential to improving their reliability in decision-making. Forward uncertainty propagation is used to derive parameter sensitivity but requires physically plausible parameter distributions first be learned from observations. Bayesian inference offers a principled approach but can become ill-posed when observations weakly constrain parameters–a condition difficult to know prior to inference. Addressing this gap, we show that parameter sensitivity results from forward uncertainty quantification can guide a non-iterative strategy for identifying observations informative to Bayesian calibration. We explore both forward and inverse uncertainty quantification for parameterizations of atmospheric turbulence in the Weather Research and Forecasting (WRF) model. To overcome the computational bottleneck of $\mathcal{O}(10^5)$ model evaluations required for both analyses, we leverage Gaussian process emulators trained on several hundred WRF simulations. Using these emulators, we conduct a global sensitivity analysis across observation space, investigating how parameter contributions to output variance depend on quantity of interest, atmospheric stability, time-averaging length, and spatial location. We then introduce nondimensional diagnostic measures that systematically identify regions where a parameter's contribution to output variance exceeds observational noise and its independent effect exceeds interaction effects. We demonstrate that observations from these regions serve as a strong proxy for accurate Bayesian calibration and reduced posterior uncertainty. Through emulator-aided Bayesian inversion with synthetic observations, we show how parameter uncertainty can be systematically reduced by leveraging sensitivity information.
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Chemical Physics

Causality in Liquid Water as a Hallmark of Emergent Glassy Dynamics

Leon Huet, Vittorio Del Tatto, Debarshi Banerjee et al. (+2 more)

In molecular liquids such as water, time-delayed influences between microscopic or mesoscopic variables are typically probed using time-correlation functions, which are symmetric under detailed balance and therefore blind to dynamical asymmetries. Here, we characterize water's dynamics using a causal inference metric that captures asymmetric couplings between collective variables. Analyzing equilibrium molecular dynamics simulations at ambient conditions and in the high-density liquid (HDL) regime of supercooled water, we uncover pronounced asymmetries in the couplings between orientational and translational degrees of freedom across multiple time and length scales. At room temperature, rotational modes exert a modest directional influence on translational dynamics. In contrast, in the supercooled HDL regime, translational motions emerge as the primary drivers of the dynamics, suggesting facilitation-like relaxation mechanisms characteristic of glassy systems. These results reveal a qualitative reorganization of dynamical couplings across thermodynamic conditions, implying that molecular liquids at thermal equilibrium can exhibit an emergent directionality in their fluctuation couplings. As a consequence, our analysis reveals that external perturbations acting on specific degrees of freedom can induce a stronger arrow of time in the causal relations between translational and orientational modes.
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All authors Leon Huet, Vittorio Del Tatto, Debarshi Banerjee, Alessandro Laio, Ali A. Hassanali

Chemical Physics · Cross-listed from quant-ph

Advancing Practical Quantum Embedding Simulations via Operator Commutativity Based State Preparation for Complex Chemical Systems

Dibyendu Mondal, Ashish Kumar Patra and Rahul Maitra

Determining the exponentially scaled ground state wavefunction and the associated molecular properties remains one of the central challenges in quantum chemistry. Hybrid quantum-classical algorithms implemented on quantum computers offer a promising route toward addressing this problem. However, despite several successful demonstrations on small molecular systems, accurate simulations of large and chemically realistic molecules remain difficult due to the limited capability of noisy intermediate scale quantum (NISQ) hardware. To bypass the limitations of NISQ devices, while simultaneously retaining the accuracy of the ground state energy estimations, we propose a dynamic ansatz construction strategy based on operator commutativity and energy driven screening within density matrix embedding theory (DMET) framework. The partitioning of the full system allows us to dynamically construct the ansatz over individual embedded subsystems, allowing each embedding problem be solved individually to a desired accuracy. The embedding Hamiltonian is updated in a self-consistent manner with dynamically formulated wavefunction, and their coupled optimization leads to accurate and efficient description of the overall system. To assess the performance of this approach, we apply it to several molecular systems and chemical processes with up to 144 qubits. These simulations require at most 20 qubits at a time and demonstrate improved accuracy and significantly reduced quantum gate requirements compared with conventional ansatze. We further investigate the impact of various fragmentation strategies and demonstrate the adaptability of our approach at each step of the DMET self-consistency cycle that leads to significantly improved accuracy for strongly correlated system.
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Fluid Dynamics

A neural operator framework for data-driven discovery of stability and receptivity in physical systems

Chengyun Wang, Liwei Chen and Nils Thuerey

Understanding how complex systems respond to perturbations, such as whether they will remain stable or what their most sensitive patterns are, is a fundamental challenge across science and engineering. Traditional stability and receptivity (resolvent) analyses are powerful but rely on known equations and linearization, limiting their use in nonlinear or poorly modeled systems. Here, we introduce a data-driven framework that automatically identifies stability properties and optimal forcing responses from observation data alone, without requiring governing equations. By training a neural network as a dynamics emulator and using automatic differentiation to extract its Jacobian, we can compute eigenmodes and resolvent modes directly from data. We demonstrate the method on both canonical chaotic models and high-dimensional fluid flows, successfully identifying dominant instability modes and input-output structures even in strongly nonlinear regimes. By leveraging a neural network-based emulator, we readily obtain a nonlinear representation of system dynamics while additionally retrieving intricate dynamical patterns that were previously difficult to resolve. This equation-free methodology establishes a broadly applicable tool for analyzing complex, high-dimensional datasets, with immediate relevance to grand challenges in fields such as climate science, neuroscience, and fluid engineering.
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Fluid Dynamics

A Statistical Field Theory for Isotropic Turbulence

Ahmed Farooq

This article establishes a first-principles statistical field theory of fully developed isotropic turbulence. Applying an exact Helmholtz decomposition to the local angular momentum field ($\Lvec = \rvec \times \uvec$) reveals a segregation into two orthogonally distinct topological phases: a longitudinal condensate of macroscopic coherent structures ($\PhiL$) and a volume-filling, transverse thermal bath ($\AL$). Constructing a Hamiltonian and evaluating the partition function of these decoupled fields demonstrates that their ergodic exploration of phase space is topologically quantized, mandating a strict $1:2$ equipartition of degrees of freedom. Inverting this topological projection back to the velocity domain isolates the radial velocity field ($\uvec_r$) (which strictly resides in the null space of the $\Lvec$ framework) revealing a recursive partitioning scheme across the cascade into a precise $1/3 : 2/9 : 4/9$ fractional hierarchy. This geometric constraint forces the turbulent steady state into a rigorous canonical equilibrium governed by the equalization of phase chemical potentials ($\mu_\Phi = \mu_A$). The radial component acts as a non-equilibrium mechanical piston, continuously injecting energy into the tangential modes to sustain the canonical equilibrium – a mechanism that mathematically formalizes the classical phenomenology of vortex stretching. Spectral evaluations from direct numerical simulation strongly corroborate this thermodynamic framework, establishing the universality of the partition ratios $1:2$ and $1/3 : 2/9 : 4/9$ as a fundamental signature of three-dimensional isotropic turbulence.
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Optics · Cross-listed from cond-mat.mes-hall

Photonic Chirality for Braiding and Readout of Non-Abelian Anyons

Netzer Moriya

We propose a cavity-based scheme that uses photonic chirality to control braiding and read out non-Abelian anyons in a fractional quantum Hall platform. Counter-propagating cavity modes interfere with a classical reference tone to create a rotating pinning landscape whose direction is set by photon circulation, so that opposite photonic branches drive opposite anyon loops. This realizes a branch-conditioned braid operation and maps the resulting braid response onto cavity intermode coherence. We derive the rotating pinning term and the readout relation at the effective-theory level, identify an operating window set by subgap driving, adiabatic transport, localization, and cavity coherence, and provide phenomenological diagnostics of transport locking. In the minimal four-anyon Ising realization, the leading signal reduces to a calibrated phase; more generally, the same readout structure becomes state dependent when the relative braid operator is non-scalar. The scheme provides a cavity route to braid-sensitive readout of non-Abelian anyons without relying on fragile electronic interference fringes.
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Fluid Dynamics

Acoustofluidic Suppression of Rayleigh Taylor Instability and Fluid Mixing: Stabilization of Stratified Fluids in a Minichannel

Venkatesh Seenuvasan Revathi, Jeyapradhap Thirisangu and Karthick Subramani

Rayleigh-Taylor Instability (RTI) typically arises when a dense fluid is superimposed on a lighter fluid, where the desta- bilizing gravitational force acting on miscible fluids drives chaotic mixing. We theoretically present an acoustofluidic method utilizing standing bulk acoustic waves (BAW) to counteract RTI and suppress the mixing of fluids. To success- fully achieve this suppression, we demonstrate that two concurrent conditions are to be satisfied: the acoustic energy density (Eac) of the standing waves must exceed its critical threshold (Ecr), and the orientation of the acoustic waves must be perpendicular to the fluid-fluid interface. This acoustofluidic mechanism reduces the mixing index (MI) by up to an order of magnitude compared to the mixing induced solely by gravity. By analyzing the interplay between acoustic and gravitational forces, this study provides a comprehensive understanding of acoustically modulated mixing dynamics in minichannels.
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Physics and Society

Dynamical heterogeneity reverses structural suppression of cooperation

Xiaochen Wang

Heterogeneity in individual characteristics and behaviour is a fundamental property of complex dynamical systems. While previous studies on evolutionary dynamics of strategies evolution in various systems have predominantly focused on the structural heterogeneity, dynamical heterogeneity in individuals' strategy update has been largely neglected. Here, we introduce a novel dynamical update mechanism based on individuals' decision-making information, comprising personal and social components. This update rule allows each individual to vary in the weight of personal information and the amount of social information, capturing the general scenario of dynamically heterogeneous populations. We find that cooperation, as a collective prosocial outcome, is significantly enhanced when highly connected individuals on interaction network rely more heavily on personal information and access more social information. This effect is notably absent in homogeneous networks, thereby overturning the prevailing consensus that structural heterogeneity inherently suppresses cooperation. This theoretical prediction is further validated by empirical evidence from GitHub collaboration networks. Furthermore, individuals preferentially linking to those who are well-informed and possess greater personal information further promotes collective cooperation. We additionally reveal that cooperators gain a decisive advantage when relying more on personal information compared to defectors, whereas social information affects cooperators and defectors equivalently. Our findings offer profound insights into how dynamical heterogeneity fundamentally shapes the evolution of collective cooperation in complex systems.
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Chemical Physics · Cross-listed from cond-mat.mes-hall

Towards Application of Nanodiamonds for in-situ Monitoring of Radicals in Liquid Phase Chemical Reactions

Emma Herbst, Sebastian Westrich, Alena Erlenbach et al. (+3 more)

In many chemical reactions, short-lived radical intermediates play a crucial role, while detecting such short-lived species in-situ remains challenging. The optically readable electronic spin of nitrogen-vacancy (NV) centers in diamond is a nanoscale sensor for such radical species: its longitudinal spin relaxation time (T$_{1}$) reacts to magnetic fluctuations from the unpaired electrons of radical species in its local environment. In this setting, we demonstrate the successful in-situ detection of the nitroxide radical 2,2,6,6-Tetramethylpiperidinyloxyl (TEMPO) using NV center-based T$_1$ relaxometry after depositing nanodiamonds onto the inner wall of a glass cuvette. A significant concentration-dependent shortening of the relaxation time was observed, from 197\:\textmu s $\pm$ 21\:\textmu s without radical to 66\:\textmu s $\pm$ 30\:\textmu s at a concentration of 1\:M TEMPO. At the same time, the nanodiamonds remain firmly attached to the cuvette even after the solution under investigation has been exchanged. The detection is sensitive in the nanomolar (nM) range and the determined signal-to-noise ratio is between 1.6 and 3.
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All authors Emma Herbst, Sebastian Westrich, Alena Erlenbach, Jonas Gutsche, Maria Wächtler, Elke Neu

Optics

Directional Scattering-Induced Optical Forces on a Mie Particle near a Metal Interface

Semyon Borodulin, Natalia Kostina and Mihail Petrov

Optical manipulation of Mie-resonant dielectric nanoparticles is strongly influenced by their enhanced scattering and multipolar response, which fundamentally modifiesthe balance of optical forces. In this work, we study the optical forces acting on a resonant dielectric nanoparticle placed near a metal interface, where scattering occurs into both free-space and surface plasmon-polariton (SPP) channels. We show that the interference of electric and magnetic dipole moments leads to highly directional scattering in these channels, and the direction and magnitude of the scattering-induced force are directly linked to the angular directivity of the corresponding radiation channels. We show that in a cross-beam configuration, where the radiation-pressure contribution is suppressed, the optical force can be changed for almost 2{\pi} in a wide range of particle sizes that provides a route toward optical sorting of resonant nanoparticles.
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Optics

Fast projections of two-dimensional light patterns using acousto-optical deflectors

Robbert Decruyenaere, Clara Tanghe, Senne Van Wellen et al. (+1 more)

Precise and flexible control of structured light fields is essential for applications ranging from optical trapping and quantum simulation to microscopy and materials processing. Acousto-optical deflectors (AODs) are widely used in these settings due to their high speed, large damage threshold, and ability to generate steerable optical tweezers. Multi-tone driving offers a powerful alternative to slow sequential scanning, enabling the projection of complex patterns with high accuracy as rapid acoustic modulation averages out inter-spot interference. In two dimensions, however, intermodulation between tones in orthogonal AODs can reintroduce coherent artifacts. We present a fast, feedback-free AOD projection scheme based on an incommensurately staggered frequency lattice that intrinsically suppresses such artifacts. For separable two-dimensional target patterns, our method removes the need for scanning entirely, enabling substantially faster and highly accurate projections. We further extend the approach to non-separable images using a minimal scanning strategy that maintains rather high projection speeds. These results demonstrate that appropriately engineered multi-tone AOD driving offers an efficient and robust route to high-speed, high-fidelity generation of arbitrary intensity patterns.
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All authors Robbert Decruyenaere, Clara Tanghe, Senne Van Wellen, Karel Van Acoleyen

Classical Physics · Cross-listed from cs.RO

Forward Dynamics of Variable Topology Mechanisms - The Case of Constraint Activation

Andreas Mueller

Many mechanical systems exhibit changes in their kinematic topology altering the mobility. Ideal contact is the best known cause, but also stiction and controlled locking of parts of a mechanism lead to topology changes. The latter is becoming an important issue in human-machine interaction. Anticipating the dynamic behavior of variable topology mechanisms requires solving a non-smooth dynamic problem. The core challenge is a physically meaningful transition condition at the topology switching events. Such a condition is presented in this paper. Two versions are reported, one using projected motion equations in terms of redundant coordinates, and another one using the Voronets equations in terms of minimal coordinates. Their computational properties are discussed. Results are shown for joint locking of a planar 3R mechanisms and a 6DOF industrial manipulator.
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Medical Physics

Optimized encoding point distributions for efficient single-point imaging

Fabian Bschorr, Pia Gebhard, Tobias Speidel et al. (+1 more)

Purpose: Quasi-random Sobol-based sampling schemes exhibit deterministic structural artifacts when aggressively undersampled, particularly at low encoding densities required for accelerated 2D SPI/CSI. To address these limitations, two advanced undersampling strategies are investigated to mitigate deterministic behavior, improving image quality for time-constrained applications such as hyperpolarized MRI. Methods: An optimized Sobol sequence-derived point distribution with Heaviside-type density gradient center oversampling served as the initial sampling pattern. Undersampling was performed using two point-reduction algorithms: radius-adaptive stochastic undersampling (RAST), which applies a geometric, radius-dependent minimum-distance criterion, and Bayesian Information Gain Optimization (BINGO), that removes points based on their information gain to the reconstructed image. Phantom experiments were conducted on a 3 T clinical MRI system using up to 16-fold undersampling. Image quality was quantified using a performance score derived from RMSE, SSIM, and HFEN. Results: Both RAST and BINGO outperformed deterministic undersampling across all metrics. RAST achieved highest and most robust performance, with improvements up to 238% in the averaged metric score, while BINGO yielded improvements of 133% across matrix resolutions. Conclusion: The proposed strategies effectively reduce the number of encoding points in low-discrepancy 2D SPI point distributions while maintaining image quality under strong acceleration. RAST provides superior metric performance, whereas BINGO offers broad applicability, including suitability for non-linear encoding fields. These approaches support rapid acquisition workflows required for real-time and hyperpolarized applications.
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All authors Fabian Bschorr, Pia Gebhard, Tobias Speidel, Volker Rasche

Atomic Physics

Bound-state QED test above the Schwinger limit with kaonic fluorine

F. Clozza, S. Manti, F. Sgaramella et al. (+35 more)

Kaonic atoms, formed when a negatively charged kaon replaces an electron in an atomic orbit, provide access to bound-state quantum electrodynamics (BSQED) in electromagnetic fields far stronger than in ordinary atoms. Here, we report an experimental test of BSQED in a regime where the mean Coulomb field exceeds the Schwinger limit. Using high-precision x-ray spectroscopy of kaonic fluorine with the SIDDHARTA-2 experiment at DA$\Phi$NE, corresponding to an integrated luminosity of 22.4 pb$^{-1}$, we observe transitions involving the 4f and 3d levels, probing field-to-Schwinger-limit ratios of 1.11 and 3.70, respectively. The measured transition energies agree with state-of-the-art Dirac-Fock calculations. In particular, the 5g-4f transition showing a residual of 5.8 $\pm$ 4.7 (stat.) $\pm$ 5.5 (syst.) eV and a $\sim$ 9$\sigma$ sensitivity to QED contributions. These results provide a direct test of BSQED in the strong-field regime of QED above the Schwinger limit, opening a new avenue for precision studies in extreme electromagnetic fields.
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All authors F. Clozza, S. Manti, F. Sgaramella, L. Abbene, F. Artibani, M. Bazzi, G. Borghi, D. Bosnar, M. Bragadireanu, A. Buttacavoli, M. Carminati, A. Clozza, L. De Paolis, R. Del Grande, K. Dulski, C. Fiorini, I. Friščić, C. Guaraldo, M. A. Iliescu, P. Indelicato, M. Iwasaki, A. Khreptak, J. Marton, P. Moskal, H. Ohnishi, K. Piscicchia, F. Principato, A. Scordo, M. Silarski, D. Sirghi, F. Sirghi, M. Skurzok, J. Sommerfeldt, A. Spallone, K. Toho, O. Vazquez Doce, J. Zmeskal, C. Curceanu

Instrumentation and Detectors

Drift Correction of Scan Images by Snapshot Referencing

Zac Thollar, Kanto Maeda, Tetsuya Kubota et al. (+3 more)

Reliable quantitative analysis in scanning (transmission) electron microscopy (S(T)EM) is often hindered by image drift during long-duration spectral mapping for elemental analysis or for various material functions. We here present snapshot-referencing (SSR) drift correction, a retrospective approach to eliminate spatial distortion based on the temporal nature of the scanning process. A continuous drift vector for every pixel is calculated for a normalized time-field of the scan pattern (e.g., serpentine or raster) utilizing a high-signal, fast-scan "snapshot" as a drift-free reference to guide the correction of simultaneously acquired analytical maps. To describe the drift, we employed Bezier basis functions to model smooth thermal or mechanical drifts and piece-wise linear basis for high-frequency "spiky" shifts such as those caused by charging. We demonstrate the efficacy of this approach on experimental cathodoluminescence (CL) datasets, showing that it effectively restores spatial integrity to hyperspectral data cubes without the need for specialized hardware. This flexible, software-based solution is broadly applicable to any probe-based analytical technique where a fast imaging signal can be recorded alongside slow spectroscopic data.
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All authors Zac Thollar, Kanto Maeda, Tetsuya Kubota, Taka-aki Yano, Qiwen Tan, Takumi Sannomiya

Applied Physics

Articulatory movements influence electromagnetic wave transmission through the vocal tract

Remi Blandin, Martin Laabs, Rudolf von Bunau et al. (+6 more)

This study experimentally validates a numerical model of electromagnetic propagation through the human head during the pronunciation of different vowels, with the goal of improving our understanding of the underlying physical phenomena. A realistic finite element model was created from magnetic resonance images acquired while pronouncing the vowels /a/, /i/, and /u/. The model was validated against scattering matrix measurements obtained from two subjects whose geometries were modeled. Despite several potential sources of discrepancy, the simulations and measurements showed good qualitative agreement, confirming the validity of the approach. Similar transmission coefficient patterns were observed across subjects for the same vowels. Within the investigated frequency range of (1-6~GHz), the electric field exhibited a Mie scattering pattern. Local minima and maxima in the transmission coefficient, characterizing different articulatory configurations, were correlated with local variations in the electric field amplitude. The transmission coefficient's shape results from an interplay between resonance patterns and antenna placement, while the degree of mouth opening influences the shape of scattering modes. Although technically challenging, this numerical approach proved effective for studying electromagnetic propagation in the human head. The resulting robust numerical model and improved understanding of the underlying physics are expected to facilitate the development of radio-frequency-based silent speech interfaces.
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All authors Remi Blandin, Martin Laabs, Rudolf von Bunau, Bryn Lloyd, Silvia Farcito, Denys Nikolayev, Gabriela Hossu, Peter Birkholz, Dirk Plettemeier

Geophysics · Cross-listed from astro-ph.EP

Physical Analysis of Bennu Samples Reveals Regolith Production by Collisional Disruption on Near-Earth Asteroids

R.-L. Ballouz, A.J. Ryan, R.J. Macke et al. (+26 more)

Owing to the extremely low gravity of small near-Earth asteroids (NEAs), it has been assumed that impact-generated rock fragments escape into space and thus do not contribute to the accumulation of regolith. However, centimeter-sized stones returned from the small NEA Bennu by NASA's OSIRIS-REx mission exhibit impact craters up to a few millimeters wide, implying that impact fragments and impact-processed rocks are retained despite the microgravity environment. To understand how, we combined detailed physical analysis of Bennu samples, laboratory experiments of impacts into simulant rocks, and 3D numerical simulations of disruptive impacts into boulders. We find that the majority (85% by mass) of impact fragments eject toward and penetrate the asteroid's weak, porous surface, leading to their retention. In addition, crater depth-to-diameter ratios (d/D) suggest that the Bennu samples (median crater d/D = 0.36 $\pm$ 0.1) are structurally representative of the asteroid's large boulders (median crater d/D = 0.33 $\pm$ 0.08, measured previously). Our analyses indicate that most of Bennu's surface rocks (those with diameters $\lesssim$ 20 m) could be products of in situ collisional disruption. This impact-driven mechanism of regolith production likely occurs on other small NEAs with highly porous surfaces.
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All authors R.-L. Ballouz, A.J. Ryan, R.J. Macke, O.S. Barnouin, M. Lê, J. Moreno, S. Eckley, L. Hanton, A. Hildebrand, V. Toy-Edens, R.M. Meier, M. Berkson, E. Asphaug, S. Cambioni, C.G. Hoover, K. Jardine, E.R. Jawin, N. Lunning, J.L. Molaro, M. Pajola, K. Righter, K.T. Ramesh, F. Tusberti, K.J. Walsh, C.W.V. Wolner, D.N. DellaGiustina, H.C. Connolly, Jr., D.S. Lauretta

Atmospheric and Oceanic Physics

Improvements to the post-processing of weather forecasts using machine learning and feature selection

Kazuma Iwase and Tomoyuki Takenawa

This study aims to develop and improve machine learning-based post-processing models for precipitation, temperature, and wind speed predictions using the Mesoscale Model (MSM) dataset provided by the Japan Meteorological Agency (JMA) for 18 locations across Japan, including plains, mountainous regions, and islands. By incorporating meteorological variables from grid points surrounding the target locations as input features and applying feature selection based on correlation analysis, we found that, in our experimental setting, the LightGBM-based models achieved lower RMSE than the specific neural-network baselines tested in this study, including a reproduced CNN baseline, and also generally achieved lower RMSE than both the raw MSM forecasts and the JMA post-processing product, MSM Guidance (MSMG), across many locations and forecast lead times. Because precipitation has a highly skewed distribution with many zero cases, we additionally examined Tweedie-based loss functions and event-weighted training strategies for precipitation forecasting. These improved event-oriented performance relative to the original LightGBM model, especially at higher rainfall thresholds, although the gains were site dependent and overall performance remained slightly below MSMG.
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Fluid Dynamics

Experimental Demonstration of SDRL Controller for TS Wave Suppression with DBD Actuator

Babak Mohammadikalakoo, Sergio Garcia Villasol, Gabriele Salomone et al. (+2 more)

An experimental wind-tunnel implementation of a model-free single-step deep reinforcement learning (SDRL) controller is presented for TS wave suppression in a flat plate boundary layer. The controller is deployed in a feedforward layout. The arrangement comprises an upstream reference microphone, a downstream error microphone, and a DBD plasma actuator located between them. The controller updates its policy online from the measured error signal and, in real time, adjusts the coefficients of a finite-impulse-response (FIR) filter that maps the reference signal to the actuation command. TS waves are artificially introduced by a second, upstream-located DBD trigger actuator identical in specification to the control actuator. The trigger actuator is driven with single-frequency, multi-frequency, or broadband white-noise inputs depending on the control cases. Experiments were carried out in an anechoic wind tunnel facility using flush-mounted pressure microphones for sensing and controller feedback, together with two-component planar particle image velocimetry~(PIV) for flow-field verification. The controller performance is assessed via second-order statistics of the error signal and the spectral attenuation of the TS wave content. Across all tested scenarios, the SDRL-based controller consistently reduces the downstream disturbance level and exhibits robustness to moderate variations in freestream velocity and in the incoming TS wave disturbance spectrum. These results provide an experimental step toward adaptable, data-driven TS wave suppression with compact sensing and actuation, supporting practical strategies for boundary layer transition delay.
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All authors Babak Mohammadikalakoo, Sergio Garcia Villasol, Gabriele Salomone, Marios Kotsonis, Nguyen Anh Khoa Doan

Chemical Physics · Cross-listed from quant-ph

An Oracle-Free Quantum Algorithm for Nonadiabatic Quantum Molecular Dynamics

Joshua Courtney

Quantum computation is an attractive front for many problems that are intractable for computers today. One such problem is nonadiabatic quantum molecular dynamics, where quantized internal states coupling to parameterized modes result in a Hamiltonian resistant to oracle-based models and spectral decomposition. This dissertation applies diabatic Hamiltonian operators directly to the computational basis as first-quantized split-operator propagators, validated with dynamic observables including absorption and recurrence spectra, scattering cross-sections, population dynamics, and quantum scars. Circuits are derived and specified, with focused circuit optimization in multi-mode and multi-channel extensions, including multivariate potential energy terms and graph theoretic optimization from molecular symmetry. Resource estimation shows circuit depth advantage against QROM-loading architectures on a fault-tolerant scale, and a quantitative comparison against quantum signal processing variants confirms that a Trotter-based architecture retains a scalable T-gate advantage. Expanding beyond electronic states demonstrates that duality between finite basis and discrete variable representations permits congruent structural decompositions into quantum circuits, expanding the use of multi-channel dynamics far beyond chemistry.
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Atomic Physics

Background-free calibrated electric-field imaging with Rydberg-state fluorescence and Autler-Townes splitting

Gabriel Ko, Wiktor Krokosz, Mateusz Mazelanik et al. (+2 more)

We demonstrate a spatially resolved method for imaging millimeter-wave (mmWave) electric fields using Rydberg-state fluorescence in a warm atomic vapor. By utilizing a multi-photon ladder excitation scheme, we leverage a specific decay channel that remains dark in the absence of the mmWave field, resulting in high-contrast imaging with effectively zero background. Absolute calibration of the local electric field is achieved by reconstructing the Autler-Townes splitting of the Rydberg resonance across the imaging volume. To ensure robust field extraction across a wide dynamic range–including regimes where spectral features are not fully resolved–we employ a steady-state analysis based on the Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) master equation. We apply this technique to visualize standing-wave interference patterns within a vapor cell and demonstrate the ability to engineer local field distributions using structured dielectric reflectors. This approach provides a versatile and self-calibrating platform for the diagnostic imaging of high-frequency electromagnetic fields and the characterization of mmWave-optical interfaces.
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All authors Gabriel Ko, Wiktor Krokosz, Mateusz Mazelanik, Wojciech Wasilewski, Michał Parniak

Physics and Society

Node-weighted recurrence analysis for path dynamics on networks

A. Schmaus, N. Marwan and N. Molkenthin

Trajectories of units moving on networks are relevant for nonlinear dynamical systems as diverse as polymers, ocean drifters, and human mobility. Although RQA is a well-researched tool with applications in many areas, it has rarely been used for spatial trajectories on networks. Here, we explore the use of RQA for paths on networks. We find that path dynamics on networks display recurrence patterns that are not often described in other applications of recurrence analysis. In particular, the combination of diagonal lines and perpendicular diagonal lines, indicates backtracking paths. We find that recurrence analysis for path dynamics on networks can be helpful to a) better understand the network structure if dynamic and recurrence plots are known, b) better understand the dynamics if network and recurrence plots are known, and c) understand the interaction between path dynamics and the underlying network.
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Medical Physics

Corneal deformation mapping and FE-based strain analysis via digital image correlation: biomechanical changes after CXL and laser refractive surgery

Benedetta Fantaci, Alejandro Frechilla, Matteo Frigelli et al. (+3 more)

Accurate assessment of corneal mechanical properties is critical for understanding ocular biomechanics, predicting refractive surgery outcomes, and optimizing cross-linking (CXL) treatments. Conventional uniaxial tensile test is limited by non-physiological boundary conditions and simplified stress distributions. Inflation testing more closely reproduces the in vivo stress state but has traditionally lacked full-field deformation mapping. In this work, we present an integrated experimental-computational protocol combining inflation testing of freshly enucleated porcine eyes with high-resolution three-dimensional digital image correlation (3D-DIC). Fifteen corneas were analyzed across three cohorts: (i) de-epithelialized controls, (ii) CXL-treated (standard Dresden protocol), and (iii) anterior stromal ablation via femtosecond laser. Samples were subjected to controlled intraocular pressure (IOP) elevations up to 40 mmHg. The 3D-DIC approach provided dense, pointwise displacement and strain maps across the anterior surface, successfully quantifying the localized stiffening effects of CXL and the increased compliance induced by stromal ablation. These full-field kinematic data were integrated into a membrane-theory finite element framework to resolve principal in-plane strains, that were used for subsequent inverse modeling to derive anisotropic hyperelastic parameters of porcine corneal tissue. Overall, the method establishes an end-to-end route from physiologic loading to full-field strain mapping and constitutive parameter identification, enabling quantitative evaluation of treatment-induced biomechanical changes in the cornea.
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All authors Benedetta Fantaci, Alejandro Frechilla, Matteo Frigelli, Philippe Büchler, Sabine Kling, Begoña Calvo

Chemical Physics

Tailoring Attosecond Charge Migration in Native Molecular Ions

Evan Munaro-Langloÿs, Franck Lépine and Victor Despré

Attosecond chemistry involves developing strategies to manipulate electronic coherent waves in molecules, which can influence the outcome of photoinduced reactions. While recent progress in this field calls for investigations of increasingly complex isolated or embedded systems, theoretical predictions on attosecond charge migration have remained limited to native neutral species. Since molecules in nature often carry a native charge, there is potential biological and chemical interest in determining whether attosecond charge migration is affected by an additional charge. In this study, we employ high-level correlated methods to study purely electronic dynamics induced by hole-mixing in molecular ions. Our results, obtained for a series of neutral, protonated and deprotonated molecules, reveal that the likelihood of observing attosecond electron dynamics can either be degraded or improved by the presence of an initial charge, and that the existence of the dynamics is correlated with the strength of electron correlation. These findings will stimulate further experimental and theoretical investigations into this unexplored field of attosecond dynamics in molecular ions.
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Optics

Propagation-based classification of linear magnetoelectric response in dielectrics

Eduardo Bittencourt, Elliton O.S.R. Brandão, Érico Goulart et al. (+1 more)

We study electromagnetic wave propagation in homogeneous dielectrics endowed with a linear magnetoelectric (ME) response in the geometric-optics regime. Assuming isotropic permittivity and permeability while keeping a generic $3\times 3$ ME matrix $\alpha_{ij}$, we derive the eikonal (Fresnel) eigenvalue problem for the polarization vector and obtain a compact quartic dispersion relation for the normalized phase speed $r=v/v_d$, where $v_d=(\mu\varepsilon)^{-1/2}$ is the phase speed of the underlying dielectric. We then classify the propagation effects of $\alpha_{ij}$ by decomposing it into trace, symmetric-traceless, and antisymmetric sectors. We show that (i) the pure-trace sector is propagation-silent at leading geometric-optics order; (ii) the antisymmetric sector yields a factorized quartic and produces two branches with closed-form phase speeds, including regimes where $|v|>v_d$; and (iii) the symmetric-traceless sector encodes the richest directional dependence through algebraic invariants that control the Fresnel wave surface and polarization mixing. Finally, we discuss how the predicted phase-speed shifts can be accessed by phase-sensitive transmission and resonant techniques, and we outline numerical workflows to validate the analytic dispersion and map polarization signatures in bulk and finite geometries.
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All authors Eduardo Bittencourt, Elliton O.S.R. Brandão, Érico Goulart, Danilo H. Spadoti

Optics

A divergent-beam surface plasmon resonance architecture for multiplexed malaria biosensing

Amos. S. Kiyumbi and Jordan. H. Hossea

We present a numerical study of a divergent-beam Kretschmann surface plasmon resonance (SPR) platform for multiplexed malaria biosensing. A Powell-lens-generated angular fan enables camera-based angular interrogation of spatially separated regions of interest on a single Au film, thereby removing the need for mechanical scanning. The framework combines transfer-matrix modelling of the prism/Au multilayer with an effective-adlayer description of biomolecular binding at the biofunctional interface. As a representative dual-biomarker case, we consider plasmodium lactate dehydrogenase (pLDH) and histidine-rich protein 2 (HRP-2). Benchmarking of the N-SF11/Au (45 nm) baseline against published water/glycerol data reproduces the characteristic resonance positions and yields a bulk angular sensitivity of $73.2181 \,^\circ \text{RIU}^{-1}$. With representative aptamer-like and antibody-like recognition layers, the relevant sensing states remain within $54^\circ$ to $57^\circ$ and produce distinct, detector-resolvable responses. Combining the optical model with effective-medium and Langmuir binding descriptions gives model-based detection limits of approximately $5.5\,\text{ng mL}^{-1}$ for HRP-2 and $5.8\times 10^{-2}\,\text{ng mL}^{-1}$ for pLDH. These results support divergent-beam SPR as a viable architecture for quantitative multiplexed malaria biosensing.
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Plasma Physics

Deep-Learning based surrogate models for plasma exhaust simulations – SOLPS-NN

Stefan Dasbach, Sebastijan Brezinsek, Yunfeng Liang et al. (+2 more)

Accurate models of the scrape-off layer are required for the design and operation of tokamak fusion reactors. Scrape-off layer simulations are computationally expensive, difficult to operate and suffer from numerical instabilities. A potential remedy comes in using machine learning models trained on simulations for fast and easy to use predictions. We present a such candidate surrogate model - named SOLPS-NN - to provide recommendations for the methods to construct it. Based on a large dataset of several thousand SOLPS-ITER simulations with reduced neutral fidelity, a variation of machine learning models with differing architectures and scopes are tested. The evaluation shows that simple fully connected neural networks are a suitable architecture. It is demonstrated that the whole spatial domain can be predicted at once, but that it is easier to achieve high accuracy by employing independent models for different observables. The presented surrogate model with reduced neutral fidelity is sufficient to predict access to detachment with trends similar to experiments. A small dataset of higher fidelity ITER baseline SOLPS-ITER simulations is used to (re-)train surrogate models. The smaller extent of the ITER dataset allows for achieving much more accurate predictions. Transfer learning from the previous surrogate model works but has no direct benefits over training a new model from scratch. Future efforts should focus on discovering the potential and the methods for models utilizing simulations with mixtures of fidelity.
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All authors Stefan Dasbach, Sebastijan Brezinsek, Yunfeng Liang, Dirk Reiser, Sven Wiesen