Fluid Dynamics
Higher order moments of scalar within a plume in a turbulent boundary layer
Miaoyan Pang, Krishna M Talluru and Kapil Chauhan
This study examines the statistical nature of instantaneous scalar concentration in an elevated point-source plume (neutral or buoyant) dispersing within a turbulent boundary layer. Using high-frequency long-duration experimental measurements, we extensively validate the gamma distribution as the appropriate probability density function of concentration, particularly at large scalar magnitudes. The two-parameter gamma distribution is shown to capture the PDF at all locations across the plume. The classical similarity of the mean and root-mean-square (RMS) concentration, often expressed through a Gaussian form, is recovered through similarity of the scale and shape parameters of the gamma distribution. In addition, statistics of extreme events, such as the 99th percentile of the instantaneous concentration signal, are also well predicted, and their observed invariance near the plume centreline is reasoned. Further, similarity is observed for the third- and higher-order central moments and standardised central moments from the experimental data. The framework of the gamma distribution is also analytically extended to higher-order statistics. The experimental data are in good agreement with the predicted central moments up to the eighth order. The results emphasise the importance of achieving statistical convergence for the intermittent concentration signal, directly influenced by finite sampling times in a measurement. A secondary result is obtained for the ratio of plume half-widths based on the mean and the RMS concentration to be $1/\sqrt{2}$, consistent with experimental observations. The results establish the gamma distribution as a consistent and unified model for all scalar concentration statistics in elevated point source plumes within a turbulent boundary layer.
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Computational Physics · Cross-listed from cs.CE
CM-GAI: Continuum Mechanistic Generative Artificial Intelligence Theory for Data Dynamics
Shan Tang, Ziwei Cao, Zhenling Yang et al. (+4 more)
Generative artificial intelligence (GAI) plays a fundamental role in high-impact AI-based systems such as SORA and AlphaFold. Currently, GAI shows limited capability in the specialized domains due to data scarcity. In this paper, we develop a continuum mechanics-based theoretical framework to generalize the optimal transport theory from pure mathematics, which can be used to describe the dynamics of data, realizing the generative tasks with a small amount of data. The developed theory is used to solve three typical problem involved in many mechanical designs and engineering applications: at material level, how to generate the stress-strain response outside the range of experimental conditions based on experimentally measured stress-strain data; at structure level, how to generate the temperature-dependent stress fields under the thermal loading; at system level, how to generate the plastic strain fields under transient dynamic loading. Our results show the proposed theory can complete the generation successfully, showing its potential to solve many difficult problems involved in engineering applications, not limited to mechanics problems, such as image generation. The present work shows that mechanics can provide new tools for computer science. The limitation of the proposed theory is also discussed.
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All authors Shan Tang, Ziwei Cao, Zhenling Yang, Jiachen Guo, Yicheng Lu, Wing Kam Liu, Xu Guo
Instrumentation and Detectors
TIARA: a fast gamma-ray detector for range monitoring in Proton Therapy
A. André, M. Pinson, C. Hoarau et al. (+14 more)
We developed a novel gamma-ray detection system (TIARA) for range monitoring in Particle Therapy. The system employs Cherenkov-based gamma-ray detection modules arranged around the target or patient, operated in time coincidence with a fast plastic beam monitor (described in a separate paper). This work focuses on the design and comprehensive characterization of the gamma-ray detection module. It consists of a monolithic PbF$_2$
crystal (2 $\times$ 1.5 $\times$ 1.5 cm$^{3}$) coupled to a 2 $\times$ 2 SiPM
matrix from Hamamatsu. A series of beam tests at different clinical facilities (MEDICYC and ProteusOne in France, CNAO in Italy) enabled the determination of the detector time resolution under various conditions, with values ranging from 222 to 283 ps FWHM (Full Width Half Maximum). Monte Carlo simulations including the optical response of PbF$_2$ allowed for the determination of the detection efficiency as a function of particle type and energy. For the final TIARA prototype, which will be composed of 30 modules, an overall detection efficiency of 0.45% is expected. Comparison with experimental data confirmed that the modules are effectively insensitive to
neutrons, yielding an excellent signal-to-noise ratio (SNR), with an estimated SNR of 17 for a module placed at 25 cm from the 148 MeV
proton beam axis. These features translate into high range accuracy: while the performance varies with beam energy and irradiation conditions, a range accuracy of 3.3 mm at 2$\sigma$ significance level was achieved at low intensity with 63 MeV
protons at MEDICYC, for a small irradiation spot of $\mathbf{\sim}$10$\mathbf{^{7}}$
protons.
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All authors A. André, M. Pinson, C. Hoarau, Y. Boursier, M. Dupont, L. Gallin Martel, M.-L. Gallin Martel, A. Garnier, J. Hérault, J.-P. Hofverberg, P. Kavrigin, C. Morel, J.-F. Muraz, M. Pullia, S. Savazzi, D. Maneval, S. Marcatili
Physics and Society · Cross-listed from econ.GN
Manipulation in Prediction Markets: An Agent-based Modeling Experiment
Bridget Smart, Ebba Mark, Anne Bastian et al. (+1 more)
Prediction
markets mobilize financial incentives to forecast binary event outcomes through the aggregation of dispersed beliefs and heterogeneous information. Their growing popularity and demonstrated predictive accuracy in political elections have raised speculation and concern regarding their susceptibility to manipulation and the potential consequences for democratic processes. Using
agent-based simulations combined with an analytic characterization of price dynamics, we study how high-budget
agents can introduce price distortions in prediction
markets. We explore the persistence and stability of these distortions in the presence of herding or stubborn
agents, and analyze how
agent expertise affects
market-price variance. Firstly we propose an
agent-based model of a prediction
market in which bettors with heterogeneous expertise, noisy private information, variable learning rates and budgets observe the
evolution of public opinion on a binary election outcome to inform their betting strategies in the
market. The model exhibits stability across a broad parameter space, with complex
agent behaviors and price interactions producing self-regulatory price discovery. Second, using this simulation framework, we investigate the conditions under which a highly resourced minority, or ”whale”
agent, with a biased valuation can distort the
market price, and for how long. We find that biased whales can temporarily shift prices, with the magnitude and duration of distortion increasing when non-whale bettors exhibit herding behavior and slow learning. Our theoretical analysis corroborates these results, showing that whales can shift prices proportionally to their share of
market capital, with distortion duration depending on non-whale learning rates and herding intensity.
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All authors Bridget Smart, Ebba Mark, Anne Bastian, Josefina Waugh
Physics and Society
Resilient-to-Fragile Transition and Excess Volatility in Supply Chain Networks
David Martin, José Moran, Debabrata Panja et al. (+1 more)
We study a production network in which firms use non-substitutable (Leontief) inputs, hold precautionary inventories and face idiosyncratic productivity shocks, with adjustment occurring through quantities rather than prices. We show analytically and numerically that a critical boundary exists in the space of shock
volatility and inventory holdings: above this threshold, the economy absorbs shocks and fluctuates mildly while below it, cascading shortages make system-wide crises inevitable. Close to the threshold, aggregate output
volatility diverges through network-mediated amplification of purely idiosyncratic shocks, providing a concrete mechanism for the “small shocks, large business cycles” puzzle. Because inventories are costly, competitive pressure drives firms toward the fragility boundary: a resilience-efficiency trade-off emerges, putting the gains from lean supply chains at risk. Finally, we show that supplier diversification shifts the threshold and, depending on its abundance, can eliminate the fragile regime entirely.
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All authors David Martin, José Moran, Debabrata Panja, Jean-Philippe Bouchaud
Chemical Physics
SITH: A Quantum-Chemical Framework for Predicting Bond Destabilization in Stretched Molecules
Daniel Sucerquia, Mikaela Farrugia, Andreas Dreuw et al. (+1 more)
Mechanical forces can selectively destabilize chemical bonds of molecular systems, particularly in biological and synthetic
polymers. While experimental and theoretical methods have advanced our understanding of mechanochemical processes, predicting where energy concentrates within a molecule remains a significant challenge. To address this, we introduce SITH (Splitting Intramolecular Tension due to stretcHing), a novel method that decomposes the total electronic energy change of a stretched molecule into contributions from individual degrees of freedom – such as bond lengths, angles, and dihedrals – using numerical integration of the work-energy
theorem. Unlike previous approaches that rely on harmonic approximations, SITH provides high accuracy and robustness to study the distribution of energies of stretched molecules up to a first bond cleavage. Although SITH uses 3N-6 degrees of freedom for the energy decomposition, we show that it can work even for ring structures like prolines. We apply SITH to a
dataset of tripeptides and demonstrate that glycine and proline exhibit significantly different energy distributions in their Ca-C backbone bonds under tension: glycine stores more energy, making it more prone to rupture, while proline has the opposite behaviour. These findings reveal intrinsic differences in mechanochemical susceptibility across amino acids, offering more accurate predictions of bond rupture in
proteins, and similarly in other (bio)
polymers. SITH thus provides a powerful, interpretable tool for understanding energy distribution at the
quantum level, with possible implications in mechanochemistry and force field validation.
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All authors Daniel Sucerquia, Mikaela Farrugia, Andreas Dreuw, Frauke Gräter
Optics
Electro-Optic Modulation in Polycrystalline Barium Titanate Metasurfaces Enhanced by Poling
Eleni Prountzou, Helena C. Weigand, Virginia Falcone et al. (+2 more)
Electrically tunable metasurfaces leveraging the strong Pockel's effect in barium titanate (BaTiO$_3$ or BTO) are a promising platform for reconfigurable free-space optical devices. However, the high cost, limited scalability, and restricted substrate compatibility of epitaxial BTO films hinder its exploitation. Here, we demonstrate free-space optical modulators based on imprinted BTO metasurfaces with targeted designs for optical and electric field confinement within the active material. With resonances exhibiting high quality factors of up to 200, we demonstrate improved transmission modulation at sub-volt driving amplitudes and frequencies up to 5 MHz. Additional enhancement is achieved via ferroelectric domain
alignment, resulting in up to 25 % higher modulation strength compared to the unbiased case and up to 75 % compared to previous demonstrations. This enhanced EO response, arising from the effective permittivity engineering and domain orientation in these polycrystalline metasurfaces, holds significant potential for scalable and efficient EO modulators and active metasurfaces.
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All authors Eleni Prountzou, Helena C. Weigand, Virginia Falcone, Ülle-Linda Talts, Rachel Grange
Biological Physics
Steer'n Roll: A Stereoscopic Flow-Sensing Strategy for Planktonic Prey Detection and Capture
Tommaso Redaelli, Eva Kanso and Christophe Eloy
Planktonic organisms such as copepods sense swimming prey and sinking food particles through the hydrodynamic disturbances they generate. However, because these flow fields are often highly symmetric, they provide little directional information, making accurate localization of the source challenging. Here, we introduce the steer'n roll sensing and response strategy. This strategy combines stereoscopic flow sensing and a roll motion. Stereoscopic sensing allows plankton to disambiguate flow signals by integrating two spatially separated flow measurements, while a roll about the swimming axis enhances exploration of the three-dimensional space. We show that steer'n roll is efficient, achieving a 100% success rate, versatile across signal type, and robust to flow sensing noise, orientational
diffusion, and
turbulence. Together, these findings identify a biologically plausible mechanism for prey detection and capture via flow sensing, and offer testable insights into the sensory-motor strategies of planktonic organisms.
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Fluid Dynamics
Effect of wind turbulence on wave generation over a viscous liquid
Romain Mathis, Sébastien Cazin, Jeanne Methel et al. (+4 more)
When wind blows over the surface of a viscous
liquid, a clear transition from irregular small-amplitude streamwise-oriented wrinkles to well-defined nearly two-dimensional regular waves is observed at a critical wind velocity. We examine how free-stream
turbulence in the air influences the growth of wrinkles and regular waves, as well as the transition between these two regimes. Experiments are carried out in a wind tunnel, in which air is blown over a tank filled with silicone oil whose viscosity is fifty times higher than that of water. The free-stream
turbulence is enhanced using upstream grids, achieving relative
turbulence intensities up to 8%. Surface deformations are measured using Free-Surface Synthetic Schlieren with micrometer accuracy. Velocity measurements are performed using hot-wire anemometry above the interface and particle image velocimetry in the
liquid. Results reveal two primary effects of grid-enhanced free-stream
turbulence: an increase in the wrinkle amplitude, and a reduction in the critical wind speed at the onset of regular waves. Nevertheless, the wrinkle-wave transition still corresponds to an approximately constant friction velocity. Similar to a classical boundary layer over a flat plate, the friction velocity is found to decrease with fetch. From a wave energy balance, we develop a qualitative model explaining why, with the highly viscous
liquid considered here, this decrease in the friction velocity results in a non-monotonic variation of the wave amplitude with the fetch.
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All authors Romain Mathis, Sébastien Cazin, Jeanne Methel, François Charru, Jacques Magnaudet, Frédéric Moisy, Marc Rabaud
Optics
Zero-Order Diffraction Suppression in Full Field-of-View Computer Generated Holography: A Camera In the Loop Interferometric Approach
Alessandro Cerioni, Samuele Trezzi, Marco Astarita et al. (+6 more)
We introduce a novel interferometric approach for suppressing zero-order diffraction (ZOD) in phase-only computer-generated holography. The technique relies on the destructive interference between the zeroth-order light and a suppression beam in a plane optically conjugated to the spatial light modulator (SLM). A camera-in-the-loop (CITL) calibration procedure retrieves the optimal pixel-wise phase map that cancels out the ZOD component with high precision, while preserving the full modulation depth of the SLM. Experimental demonstrations on point-cloud and 2D/3D holograms achieve up to 99% suppression of the ZOD intensity, without loss of image quality or field of view. Once calibrated, the correction can be applied to any hologram without recomputation, enabling real-time operation and robust performance over time. This method removes a long-standing barrier to the practical deployment of full-field holography, facilitating the development of compact, high-fidelity
holographic engines for augmented and mixed reality displays.
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All authors Alessandro Cerioni, Samuele Trezzi, Marco Astarita, Tommaso Ongarello, Anna Cesaratto, Giulio Cerullo, Andrea Bassi, Gianluca Valentini, Paolo Pozzi
Chemical Physics
Spectroscopic Detection and Characterization of Cyanooxomethylium, NCCO$^+$
Marcel Bast, Julian Böing, Thomas Salomon et al. (+6 more)
Cyanooxomethylium, NCCO$^+$, a fundamental linear acylium ion, has been observed spectroscopically for the first time using action spectroscopy in ion trap apparatuses. A first low-resolution infrared spectrum was obtained between 500 to 1400 cm$^{-1}$ and 2000 to 2500 cm$^{-1}$ using the Free Electron
Laser for Infrared eXperiments (FELIX) and the FELion apparatus, employing infrared predissociation of the weakly bound NCCO$^+$-Ne complex. Subsequently, high-resolution studies of the bare ion were performed with the COLtrap II setup, one targeted at the CN-stretching mode $\nu_2$ around 2150 cm$^{-1}$ using leak-out spectroscopy and one at the pure rotational spectrum employing a leak-out infrared/millimeter-wave double resonance approach covering transition frequencies as high as 246 GHz. Spectroscopic detection and analysis were guided by high-level
quantum-chemical calculations performed at the CCSD(T) level of theory. The collected data permit accurate frequency predictions to support future astronomical searches with sensitive
radio telescopes.
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All authors Marcel Bast, Julian Böing, Thomas Salomon, Eline Plaar, Igor Savić, Mathias Schäfer, Oskar Asvany, Stephan Schlemmer, Sven Thorwirth
Accelerator Physics · Cross-listed from cond-mat.mes-hall
Transit-time oscillations in nanoscale vacuum diode with a pure resistive load
Bjart{\th}hór Steinn Alexandersson, Kristinn Torfason, Andrei Manolescu et al. (+1 more)
We examine the Ramo current in a nanoscale planar
vacuum diode undergoing field emission in the presence of a DC voltage supply and an external resistor. We describe a simple mechanism for generating persistent current oscillations in the diode due to the voltage drop across the external resistor (beam loading) which reduces the total field and inhibits the emission. The amplitude and the frequency, which is in the THz domain, depend on the operating parameters of the diode. Molecular dynamics simulations are used to find the characteristics and physical basis of the mechanism, and a simple analytical model is presented, in good agreement with the simulation.
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All authors Bjart{\th}hór Steinn Alexandersson, Kristinn Torfason, Andrei Manolescu, Ágúst Valfells
Atmospheric and Oceanic Physics
StormDiT: A generative AI model bridges the 2-6 hour 'gray zone' in precipitation nowcasting
Haofei Sun, Yunfan Yang, Wei Han et al. (+6 more)
Accurate short-term warnings for extreme precipitation are critical for global disaster mitigation but are hindered by a persistent predictability barrier at the 2-6 hour horizon – the "nowcasting gray zone." In this window, traditional observation-based extrapolation fails due to error accumulation, while numerical weather prediction is computationally too slow to resolve storm-scale dynamics. Recent generative AI approaches attempt to bridge this gap by decomposing precipitation into separate deterministic advection and
stochastic diffusion components. However, this decomposition can sever fundamental causal links between entangled atmospheric processes, such as the dynamic initiation of convection triggered by boundary advection. Here we present StormDiT, a unified generative model that treats weather
evolution as a holistic spatiotemporal problem, learning the coupled physics of the gray zone without human-imposed structural priors. Trained on a massive
dataset of 7,720 precipitation events from China, our model achieves a breakthrough in long-horizon stability. On a heavy-rainfall test set, it maintains skillful prediction for strong convection ($\ge$ 35 dBZ) with a Critical Success Index (CSI) near 0.2 across the full 6-hour forecast at 6-minute resolution. Crucially, the model exhibits superior probabilistic calibration, accurately quantifying operational risks. On the public SEVIR
benchmark, our unified paradigm more than doubles the state-of-the-art 1-hour performance for heavy rain and establishes the first robust baseline for 3-hour
forecasting. Furthermore, interpretability analysis reveals that the model attends to non-local physical precursors, such as
outflow boundaries, explicitly validating its emergent understanding of convective organization.
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All authors Haofei Sun, Yunfan Yang, Wei Han, Wei Huang, Huaguan Chen, Zhiqiu Gao, Zeting Li, Zhaoyang Huo, Zeyi Niu
Optics
Controlling X-ray emission with dispersion-engineered surface plasmon polaritons
H. Aknin, Y. Klein and S. Shwartz
We propose controlling the angular and spectral distribution of hard x-ray emission by entangling x-ray
photons with ultraviolet surface plasmon polaritons (SPPs) whose dispersion is engineered by a metal-dielectric multilayer on a nonlinear
crystal. Spontaneous parametric down-conversion of an x-ray pump produces a hard x-ray signal
photon correlated with an ultraviolet SPP mode near its resonance. Engineering the SPPs dispersion reshapes the phase-matching landscape and imprints tunable angular-spectral structure on the emitted x-ray
photons. The scheme enables compact, designable control of x-ray emission and extends surface-plasmon-assisted nonlinear and
quantum x-ray optics.
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Medical Physics · Cross-listed from cs.LG
A Learning-based Framework for Spatial Impulse Response Compensation in 3D Photoacoustic Computed Tomography
Kaiyi Yang, Seonyeong Park, Gangwon Jeong et al. (+4 more)
Photoacoustic computed
tomography (PACT) is a promising imaging modality that combines the advantages of optical contrast with ultrasound detection. Utilizing ultrasound transducers with larger surface areas can improve detection sensitivity. However, when computationally efficient analytic reconstruction methods that neglect the spatial impulse responses (SIRs) of the transducer are employed, the spatial resolution of the reconstructed images will be compromised. Although optimization-based reconstruction methods can explicitly account for SIR effects, their computational cost is generally high, particularly in three-dimensional (3D) applications. To address the need for accurate but rapid 3D PACT image reconstruction, this study presents a framework for establishing a learned SIR compensation method that operates in the data domain. The learned compensation method maps SIR-corrupted PACT measurement data to compensated data that would have been recorded by idealized point-like transducers. Subsequently, the compensated data can be used with a computationally efficient reconstruction method that neglects SIR effects. Two variants of the learned compensation model are investigated that employ a U-Net model and a specifically designed, physics-inspired model, referred to as Deconv-Net. A fast and analytical training data generation procedure is also a component of the presented framework. The framework is rigorously validated in virtual imaging studies, demonstrating resolution improvement and robustness to noise variations, object complexity, and sound speed heterogeneity. When applied to in-vivo breast imaging data, the learned compensation models revealed fine structures that had been obscured by SIR-induced artifacts. To our knowledge, this is the first demonstration of learned SIR compensation in 3D PACT imaging.
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All authors Kaiyi Yang, Seonyeong Park, Gangwon Jeong, Hsuan-Kai Huang, Alexander A. Oraevsky, Umberto Villa, Mark A. Anastasio
Optics
Lattice-mismatch Moire laser with strong flatband coupling
Donghwee Kim, Chiwon Shin, Changi Kim et al. (+5 more)
Inter-
cell and/or interlayer coupling in Moire superlattices can generate flatbands and collective eigenmodes that enable emergent physical phenomena, motivating extensive exploration of Moire-inspired photonic devices. However, the experimental validation of robust inter-
cell interactions in Moire photonic structures and the modulation of flatbands for specific photonic applications remain challenging. Here, we propose a
lattice-mismatch Moire cavity and demonstrate nanolasers enabled by strong flatband coupling. In contrast to a twist-angle Moire cavity, a
lattice-mismatch Moire cavity provides a stable flatband frequency and a substantial enhancement in Q factor compared to an isolated single-
cell cavity, as the unit-
cell size decreases. The photonic band-structure measurement of the small-unit-
cell Moire cavity by photoluminescence reveals pronounced flatbands.
Cell-resolved spectroscopy further confirms the presence of flatbands by identifying resonant peaks that consistently emerge across unit
cells in a Moire cavity with a
lattice mismatch of 102 nm, but not in a larger-unit-
cell Moire cavity with a mismatch of 60 nm. Furthermore, mode selection is achieved by reducing the center-hole size, thus isolating the hexapole mode from the degenerate dipole modes while maintaining strong inter-
cell coupling. Consequently, we demonstrate a low-threshold hexapole flatband
laser in a single mode. Therefore, the systematic modification of the relative
lattice parameters of the two constituent
lattices offers a promising strategy for developing Moire nanolasers and flatband nanophotonic devices.
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All authors Donghwee Kim, Chiwon Shin, Changi Kim, Gil-Woo Lee, You-Shin No, Jin-Kyu Yang, Heonsu Jeon, Hong-Gyu Park
Fluid Dynamics
Numerically Consistent Non-Boussinesq Subgrid-scale Stress Model with Enhanced Convergence
Yuenong Ling and Adrián Lozano-Durán
We extend the data-assimilation approach of Ling and Lozano-Durán (AIAA 2025-1280) to develop machine-learning-based subgrid-scale stress (SGS) models for large-eddy simulation (LES) that are consistent with the numerical scheme of the flow solver. The method accounts for configurations with two inhomogeneous directions and is applied to turbulent boundary layers (TBL) under adverse pressure gradients (APG). To overcome the limitations of linear eddy-viscosity closures in complex flows, we adopt a non-Boussinesq SGS formulation along with a dissipation-matching training loss. A second improvement is the integration of a multi-task learning strategy that explicitly promotes monotonic convergence with grid refinement, a property that is often absent in conventional SGS models. A posteriori tests show that the proposed model improves predictions of the mean velocity and wall-shear stress relative to the Dynamic Smagorinsky model (DSM), while also achieving monotonic convergence with grid refinement.
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Optics
Soft X-ray Reflection Ptychography
Damian Guenzing, Dayne Y. Sasaki, Alexander S. Ditter et al. (+9 more)
Scanning transmission X-ray microscopy and ptychography have become mature tools for high-resolution, element-specific imaging of nanoscale structures. However, transmission geometries impose stringent constraints on sample thickness and preparation, thereby limiting investigations of extended or bulk specimens, especially in the soft X-ray region. Here, we demonstrate reflection geometry soft X-ray ptychography as a robust imaging mode. Instrumental feasibility and spatial resolution are established using a lithographically defined Siemens
star and barcode test pattern on a multilayer substrate. We empirically demonstrate a full-pitch spatial resolution of ca. 45 nm from
Fourier ring correlation analysis of the reconstructed object. The results highlight the potential of the reflection geometry for nondestructive X-ray studies of materials without the need for transmissive samples.
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All authors Damian Guenzing, Dayne Y. Sasaki, Alexander S. Ditter, Abraham L. Levitan, Eric M. Gullikson, Scott Dhuey, Arian Gashi, Hendrik Ohldag, Sujoy Roy, David A. Shapiro, Riccardo Comin, Sophie A. Morley
Biological Physics
Roles of individual pigments in ultrafast excitation dynamics of light-harvesting phycobiliproteins revealed by recombinant techniques and two-dimensional electronic spectroscopy
Masaaki Tsubouchi, Takatoshi Fujita, Motoyasu Adachi et al. (+1 more)
Phycobiliproteins serve as highly efficient light-harvesting
antennae in cyanobacteria, yet the molecular factors governing their ultrafast energy relaxation and coherence dynamics remain incompletely understood. In this study, we investigate the role of pigment arrangement and pigment-
protein interactions by combining recombinant
protein engineering with two-dimensional electronic spectroscopy (2D-ES). In addition to wild-type allophycocyanin (APC) and C-phycocyanin (CPC), we artificially synthesized a {\beta}153 phycocyanobilin (PCB)-deficient CPC mutant, enabling direct experimental isolation of the contribution of this peripheral pigment. The absorption and fluorescence spectra show that removal of the {\beta}153 pigment primarily eliminates its spectral contribution without significantly altering the excitonic coupling between the {\alpha}84 and {\beta}84 pigments. Time-resolved 2D-ES reveals the close similarity between the dynamics of wild-type and {\beta}153-deficient CPCs, which demonstrates that the e̱ta}153 pigment plays a minor role in ultrafast relaxation dynamics. Instead, the differences between APC and CPC arise primarily from pigment-
protein interactions that modulate pigment structure and vibronic states. These results highlight the critical importance of local
protein environments in controlling energy relaxation and coherence in photosynthetic light-harvesting
proteins.
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All authors Masaaki Tsubouchi, Takatoshi Fujita, Motoyasu Adachi, Ryuji Itakura
Fluid Dynamics
Clustering and surface distributions of buoyant particles in open-channel flows
Ana Todorova, Robert K. Niven and Matthias Kramer
This study investigates the clustering behaviour and surface distributions of buoyant particles at the air-water interface in open-channel turbulent flow, focusing on the interplay between capillary attraction, hydrodynamic drag, and flow-driven lateral transport. Using controlled laboratory flume experiments, we systematically examine clustering dynamics for two particle types differing in size and density. To interpret the observed behaviour, we extend capillary-based clustering frameworks to open-channel flows by introducing a dimensionless clustering Weber number (We_cl) that captures the balance between the flow-induced disruptive force and capillary attraction, providing a compact description of the observed clustering behaviour. In addition, we demonstrate that secondary currents play a central role in surface particle transport, producing systematic lateral accumulation that depends on channel aspect ratio. Together, these findings extend capillary-driven clustering theory to open-channel
turbulence and reveal secondary currents as a key mechanism controlling particle surface distributions.
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Fluid Dynamics
Effect of initial Rayleigh mode on drop deformation under impulsive acceleration
Aditya Parik, Sandip Dighe, Tadd Truscott et al. (+1 more)
One of the fundamental ways of representing a droplet shape is through its Rayleigh-modes, where each mode corresponds to distinct surface-energy. Previous studies have focused on the effect of these modes on free oscillations of drops. In this paper, we systematically quantify how the different prescribed initial axisymmetric Rayleigh modes modulate aerodynamic energy uptake and the resulting deformation of an impulsively accelerated drop. Using experimentally validated VOF-based multiphase numerical simulations, we isolate the coupled effects of finite-amplitude surface oscillation modes and the associated initial surface-energy state by initialising the drops with well-defined $(n,0)$ modes and phases $\{0,\pi\}$, while conserving the equivalent drop volume. We find that the deformation outcome is governed by the drag due to the drop's initial geometry, and the dynamic coupling between the free modal oscillations and the forced aerodynamic deformation. We find that constructive superposition amplifies deformation, whereas destructive superposition can stabilise the drop even when the aerodynamic forcing is sufficient to deform an analogous spherical drop to breakup. Initial modes and phases that channel a larger fraction of the input power into deformation, in the form of oscillatory kinetic energy and additional surface energy, attain larger deformations and are closer to the fragmentation threshold. These couplings are especially pronounced in high-viscosity systems, where viscous dissipation is large and facilitates the transfer of a larger fraction of the total energy to translational kinetic energy instead of oscillatory kinetic energy. For low density-ratio systems, early-time coupling and energy transfer are the dominant mechanisms that govern drop deformation.
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All authors Aditya Parik, Sandip Dighe, Tadd Truscott, Som Dutta
Applied Physics
Non-Local Metasurface-aided Leaky-Wave Antennas
Seokjun Kim, Haneul Ryu and Minseok Kim
This work presents a non-local terahertz metasurface integrated into a leaky-wave
antenna for robust, wide-angle beam steering. The metasurface encodes a
holographic pattern by explicitly inducing tangential and normal susceptibilities, along with magnetoelectric coupling. This design maintains stable radiation performance even when the longitudinal wavenumber of the incident guided mode - and thus its effective impinging angle - varies as a function of frequency. In particular, we show that there exists a limit to achieving exact angular insensitivity and propose an optimization-based framework to obtain the required susceptibilities that closely approximate near angle-insensitive performance for stable beam-steering performance. Additionally, an iterative synthesis approach is introduced that maps abstract susceptibilities to physically realizable structures. Full-wave simulations demonstrate a beam-scanning range of nearly 50 degrees over the 2.0-2.7 THz band - a more than threefold improvement over conventional local-metasurface designs.
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Optics
Implications of temporal sampling in voltage imaging microscopy
Jakub Czuchnowski and Jerome Mertz
Significance: Voltage imaging microscopy has emerged as a powerful tool to investigate neural activity both in vivo and in vitro. Various imaging approaches have been developed, including point-scanning, line-scanning and wide-field microscopes, however the effects of their different temporal sampling methods on signal fidelity have not yet been fully investigated. Aim: To provide an analysis of the inherent advantages and disadvantages of temporal sampling in scanning and wide-field microscopes and their effect on the fidelity of voltage spike detection. Approach: We develop a mathematical framework based on a mixture of analytical modeling and computer simulations with Monte-Carlo approaches. Results: Scanning microscopes outperform wide-field microscopes in low signal-to-noise conditions and when only a small subset of spikes needs to be detected. Wide-field microscopes outperform scanning microscopes when the measurement is temporally undersampled and a large fraction of the spikes needs to be detected. Both modalities converge in performance as sampling increases and the frame rate reaches the decay rate of the voltage indicator. Conclusions: Our work provides guidance for the selection of optimal temporal sampling parameters for voltage imaging. Most importantly it advises against using scanning voltage imaging microscopes at frame rates below 500 Hz.
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Chemical Physics
Quantum statistics from classical simulations via generative Gibbs sampling
Weizhou Wang, Xuanxi Zhang, Jonathan Weare et al. (+1 more)
Accurate simulation of
nuclear quantum effects is essential for molecular modeling but expensive using path integral molecular dynamics (PIMD). We present GG-PI, a ring-
polymer-based framework that combines generative modeling of the single-bead conditional density with Gibbs sampling to recover
quantum statistics from classical simulation data. GG-PI uses inexpensive standard classical simulations or existing data for training and allows transfer across temperatures without retraining. On standard test systems, GG-PI significantly reduces wall clock time compared to PIMD. Our approach extends easily to a wide range of problems with similar Markov structure.
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All authors Weizhou Wang, Xuanxi Zhang, Jonathan Weare, Aaron R. Dinner
Atmospheric and Oceanic Physics · Cross-listed from hep-ex
Atmospheric Muon Measurements Near Tornadic and Non-Tornadic Storms in the US Central Plains
William Luszczak, Jana Houser, Matt Kauer et al. (+1 more)
Tornadoes and other severe weather hazards affect thousands of people every year. Despite this, the details surrounding tornadic processes including formation, decay, and longevity are not well understood, partially due to limitations of available instrumentation. Measurements of atmospheric pressure within tornadic systems currently rely almost entirely on in-situ instrumentation, and no existing techniques can provide two-dimensional spatial information of the atmospheric density field. Atmospheric
muons may hold a solution to this problem:
muons are attenuated by matter, and tornadic storms are large regions of low atmospheric density, suggesting that tornadic storms induce a directional perturbation on the atmospheric
muon flux. Measurements of this perturbation could then be used to infer the density field associated with severe weather. Simulations of these systems indicate that a robust measurement of the atmospheric density field would require a relatively large
muon detector, however smaller detectors may be able to detect ambient
muon flux perturbations if the storm is large and intense enough. This paper presents results from a pilot field study that measured the atmospheric
muon flux near tornadic storms during May 2025, including directional measurements of the
muon flux near tornadic mesocyclones and a measurement of the
muon flux near the base of a forming tornado.
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All authors William Luszczak, Jana Houser, Matt Kauer, Leigh Orf
Computational Physics · Cross-listed from cs.LG
Loss Landscape Geometry of Partial Differential Equation Emulators: Or, Symmetry Learning via Gradient Alignment
James Amarel, Robyn Miller, Nicolas Hengartner et al. (+5 more)
We study how neural emulators of partial differential equation solution operators internalize physical
symmetries by introducing an influence-based diagnostic that measures the propagation of parameter updates between
symmetry-related states, defined as the metric-weighted overlap of loss gradients evaluated along group orbits. This quantity probes the local geometry of the learned loss landscape and goes beyond forward-pass equivariance tests by directly assessing whether learning dynamics couple physically equivalent configurations. Applying our diagnostic to autoregressive fluid flow emulators, we show that orbit-wise gradient coherence provides the mechanism for learning to generalize over
symmetry transformations and indicates when training selects a
symmetry compatible basin. The result is a novel technique for evaluating if surrogate models have internalized
symmetry properties of the known solution operator.
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All authors James Amarel, Robyn Miller, Nicolas Hengartner, Benjamin Migliori, Emily Casleton, Alexei Skurikhin, Earl Lawrence, Gerd J. Kunde
Instrumentation and Detectors
Optimising Re-entrant Cavity Designs for Low Mass Axion Haloscopes
Raj Aryan Singh, Paige Rose Taylor, Elrina Hartmann et al. (+2 more)
Axion haloscopes provide a leading experimental approach to detecting QCD
axion dark matter through resonant
axion-
photon conversion in microwave cavities. Extending haloscope sensitivity to low
axion masses remains challenging due to the large resonator volumes required at sub-GHz frequencies. Re-entrant cavities offer a compact solution, but their performance depends strongly on
geometric optimisation. We present a comprehensive finite-element study of re-entrant cavity haloscope designs operating in the 100 to 500 MHz range, comparing their performance using effective scan time as a figure of merit. Among the configurations studied, we identify a double attack geometry that achieves a roughly threefold improvement in effective scan time compared to a conventional single-rod re-entrant cavity. We further investigate practical implementation strategies, including a hybrid design employing one fixed rod and one tunable rod, which preserves a scan time gain while reducing mechanical complexity. These results demonstrate a pathway to enhanced low-mass
axion haloscope sensitivity.
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All authors Raj Aryan Singh, Paige Rose Taylor, Elrina Hartmann, Geoffrey Brooks, Ben T. McAllister