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Physics Physics

physics Watch Physics

Friday 22 May

Atmospheric and Oceanic Physics · Cross-listed from cs.LG

Hybrid Quantum-Classical Corrective Diffusion Modeling for Meteorological Downscaling

Rui Wang, Edoardo Pasetto, Amer Delilbasic et al. (+3 more)

Statistical downscaling is a crucial component of the weather modeling field, where high-resolution outputs must be reconstructed from coarse-resolution inputs with the full cost of dynamical refinement. In this work, we investigate a hybrid quantum-classical corrective diffusion model for probabilistic statistical downscaling of weather fields. The proposed model inserts variational quantum circuit layers into the most compressed bottleneck of the diffusion UNet while leaving the regression branch fully classical. This placement tests whether quantum circuits can act as compact nonlinear feature maps for latent-channel mixing. We evaluate intra-channel and cross-channel ansätze on 10m wind components. On the 2020 validation set, the hybrid models remain stable, preserve the large-scale spatial organization of the generated wind fields, and improve both MAE and CRPS relative to a classical corrective diffusion model in several configurations. Structural diagnostics further show that the hybrid variants preserve kinetic-energy spectra and windspeed distributions similar to its classical counterpart while producing controlled changes in tail behavior, extreme-windspeed localization, and joint wind field components structure. Backend studies on the 2020 validation set show negligible impact from simulated device noise at the tested circuit scale, whereas real-hardware deployment remains limited by qubit availability and execution fidelity. The 2021 out-of-distribution test shows that these in-distribution gains do not transfer uniformly under temporal shift, revealing a generalization gap that motivates future mitigation through stabilization and regularization. These results show that bottleneck-level quantum hybridization can make a nontrivial contribution to weather statistical downscaling, while also highlighting that circuit scale and hardware deployment remain key limiting factors.
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All authors Rui Wang, Edoardo Pasetto, Amer Delilbasic, Morris Riedel, Kristel Michielsen, Gabriele Cavallaro

Instrumentation and Detectors

Development of a system for testing full-size CMS LGAD sensors

Kyungmin Lee, Hoyong Jeong, Junho Kim et al. (+3 more)

Low-Gain Avalanche Diode (LGAD) sensors, offering timing resolutions of the order of tens of picoseconds, are being widely adopted in particle physics experiments and related applications. As these applications scale to large numbers of sensors with varying pixel geometries, conventional manual characterization techniques become inadequate for large-scale quality control. We present a modular probe card system for automated electrical characterization of pixelated LGAD sensors, consisting of a probe card, a switching board, precision measurement instruments, and control software. The system supports flexible pixel selection and measurement. Its performance is demonstrated through current-voltage (I-V) and capacitance-voltage (C-V) measurements of a $16 \times 16$ LGAD array. A rapid row-wise I-V scan of the full array is completed in approximately 20 minutes, while a pixel-by-pixel I-V scan from 0 to 300 V with a 1 V step requires about 340 minutes. The switching matrix introduces less than 1 nA of leakage current even in a conservative worst-case configuration, remaining small compared with the leakage current of a normal LGAD pixel. The modular architecture and automation capability make the system a practical and scalable solution for large-scale LGAD sensor quality control and distributed testing environments.
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All authors Kyungmin Lee, Hoyong Jeong, Junho Kim, Seokhyeon Lee, Jaebak Kim, Jae Hyeok Yoo

Fluid Dynamics

CHIMERA: Couette Hydrodynamics for the Investigation of Multi-fluid Extreme-Reynolds Turbulence in Annuli

Pantxo Diribarne, Jérôme Chartier, Jérôme Duplat et al. (+1 more)

The CHIMERA (Couette Hydrodynamics for the Investigation of Multi-fluid Extreme-Reynolds Turbulence in Annuli) apparatus has been developed to investigate turbulent momentum transport in a canonical wall-driven flow using a wide variety of working fluids, from room-temperature gases to normal and superfluid helium. We present the design and characterization of a cryogenic Taylor-Couette facility in which torque is measured on a suspended outer cylinder using a torsion-pendulum sensor and a non-contact optical readout. This configuration avoids the need for cryogenic torque transducers or electrical instrumentation inside the cryostat while providing high sensitivity over a wide dynamic range. Measurements performed in gaseous helium at room temperature and in normal liquid helium reach Reynolds numbers up to 106 and agree well with established torque correlations, validating the apparatus over more than five decades in Reynolds number. Beyond providing such an exceptionally broad operating range with a single experimental facility and a single torque sensor, the principal motivation of CHIMERA is to enable direct comparisons of turbulent momentum transport in He I and He II under identical boundary conditions. By combining the same geometry and the same global torque diagnostic in both classical and quantum fluids, the apparatus provides a unique platform for investigating how wall-driven turbulence and its scaling evolve across the superfluid transition.
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All authors Pantxo Diribarne, Jérôme Chartier, Jérôme Duplat, Bernard Rousset

Atomic Physics

Spatial dealiasing of classical geomagnetic survey data through use of a microfabricated wearable quantum magnetometer

Stirling Scholes, Alissa Forsythe, Courtney Dyer et al. (+6 more)

Geomagnetic surveys provide insight into the subsurface for a range of applications, from fundamental understanding of geological processes, to mineral exploration and locating unexploded ordnance. A persistent challenge in performing such geomagnetic surveys is the joint problem of anthropogenic noise rejection and spatial aliasing, where the limited bandwidth (< 10 Hz) of traditional surveying instruments introduces artefacts into the surveyed field. Optically Pumped Magnetometers (OPMs) exploit quantum mechanical effects to achieve highly sensitive and stable magnetic field measurements at comparatively high bandwidths. Recent advances in manufacturing have enabled OPMs to be packaged in compact and lightweight systems (approx. 1kg), that are ideal for geomagnetic surveying. Here, we show how an OPM can directly contribute to the reduction of spatial aliasing in traditional PPM data. We carry both a PPM and OPM over a 20 km long transect across the Highland Boundary Fault (HBF) in Scotland. We leverage the continuous acquisition of the OPM sampling at 90 Hz, equivalent to every approx. 1 cm at walking pace (1 m/s) versus every approx. 200 m for our PPM (which had to be stationary for measurements) to reject magnetic noise and identify new small-scale (< 200 m) geological structures. Further, we discuss the logistical advantages of the hybrid survey in terms of portability, survey delivery, data density, and data quality.
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All authors Stirling Scholes, Alissa Forsythe, Courtney Dyer, Amy Gilligan, Karen Lythgoe, Jenny Jenkins, Marcin Mrozowski, Jack-Andrew Smith, Stuart Ingleby

Optics

Re-evaluation of bottleneck effect via a coupled monolayer WS_2/photonic crystal heterostructure

Jiaru Zhou, Wenze Lan, Hao Li et al. (+6 more)

Exciton-polariton condensates is an important type of Bose-Einstein condensate whose realization requires efficient relaxation of polaritons to the band-energy minima. However, this process is often obstructed by bottleneck effect near the anticrossing region of polariton dispersion. Although the exciton-polariton bottleneck effect has been extensively observed in various polariton system, but there is no a unified views of physical origin. Here, we construct an exciton-trion-photon coupling system in monolayer WS_2/photonic-crystal slab heterostructures. Momentum-resolved photoluminescence reveals the anticrossing polariton dispersions for the exciton resonance with a ~57 meV Rabi splitting and there is no characteristic anticrossing for trion resonance with a ~5 meV splitting at ~12 K. Enhanced polariton emission is observed around the trion-polariton crossing with elevating temperature. We attributes this exotic phenomenon to bottleneck effect and indicating that small Rabi splitting is the unified origin of bottleneck effect in polariton systems.
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All authors Jiaru Zhou, Wenze Lan, Hao Li, Yu Hua, Peng Fu, Geng Li, Xiaofeng Fan, Changzhi Gu, Baoli Liu

Fluid Dynamics · Cross-listed from quant-ph

Lowest order Carleman linearization for low Reynolds long-term behaviour of fluid flow simulations

Luca Cappelli and Sauro Succi

It is shown that the lowest (second) order truncation of the Carleman linearization of the fluid equations (C2) recovers the late stage of the evolution, namely the steady-state solution, although to a decreasing degree of accuracy at increasing Reynolds number. This asymptotic property is first proved analytically for the decaying logistic with external forcing and then shown to hold to a significant degree of accuracy also for the more complex case of two-dimensional Kolmogorov-like fluid flow at low Reynolds numbers, below $Re \sim 10$. This time-asymptotic property may open interesting prospects for the quantum simulation of low-Reynolds steady-state fluid flows.
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Applied Physics

Generalized Conductivity Modeling and Selective Harmonic Amplification in Time-Modulated Graphene Cavities

Ioannis M. Koutzoglou, Stamatios Amanatiadis, Nikolaos V. Kantartzis et al. (+1 more)

The selective harmonic enhancement in cavities formed by stacks of time-modulated graphene sheets and a reflecting boundary is investigated. A semi-analytic framework based on an operator formulation and the transfer matrix method is developed and validated against a modified finite-difference time-domain algorithm. The temporal dispersion of graphene is treated through both a generalized Taylor-expanded conductivity model and a reduced high-bias approximation. By employing particle swarm optimization to tune the cavity gaps, selected Floquet harmonics are engineered under distinct modulation regimes. Numerical results show strong enhancement of first-order sidebands in the high-bias regime, controlled third-order harmonic generation beyond the linear regime with an explicit trade-off between target amplification and total non-target leakage, and symmetry-induced purely even harmonic generation under zero-centered modulation.
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All authors Ioannis M. Koutzoglou, Stamatios Amanatiadis, Nikolaos V. Kantartzis, Theodosios D. Karamanos

Optics

Approaching physical limits of latent dimensionality in optical computing

Zhenyu Zhao, Zijun Qiu, Xuan Hu et al. (+8 more)

The physical implementation of artificial intelligence requires mapping computational processes onto the dynamic physical processes of the underlying computing platform. The photonic processors offer an intrinsically parallel and low energy framework for this mapping, however, a mismatch between the potential computing capability of a bounded optical domain and the human accessible manipulation range sets a hard integration density ceiling on existing architectures. Here, we address this challenge by investigating the integration density limits in photonic processors through exploring the fundamental physical limits on the latent dimensionality for maximum expressivity of a bounded optical domain. These physical limits potentially serve as universal metrics for evaluating optical computing capacity. To validate these, we design and realize ultracompact multimode photonic processors approaching these limits: a 2.2 um by 8 um processor achieves 86.7 % accuracy in experiment for iris flower classification, and a 20.6 um by 44.8 um processor reaches 92.9% accuracy in handwritten digit recognition. Finally, we scale this architecture to highly complex tasks by implementing a generative diffusion model for image synthesis. By grounding photonic processor design in the wave physics origin of latent dimensionality, our results supply the missing theoretical reference point for optical computing architecture.
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All authors Zhenyu Zhao, Zijun Qiu, Xuan Hu, Yao Zhou, Jinlong Xiang, Youlve Chen, Chaojun Xu, Yuchen Yin, Tao Lin, Yikai Su, Xuhan Guo

Biological Physics · Cross-listed from cond-mat.soft

Orientational frustration drives enhanced diffusion of anisotropic particles in a liquid labyrinth

Rohit Mangalwedhekar, Limeng Ruan, Somen Nandi et al. (+5 more)

Transport of nanoscale objects in complex, structured environments plays a key role in a wide range of processes, from biomolecular dynamics in extracellular spaces to transport in porous materials such as filters and catalysts. While anomalous diffusion is well established, how particle anisotropy governs transport under geometric constraints remains unclear. Here we use 3D single-particle tracking to investigate the diffusion of stiff one-dimensional carbon nanotubes in a continuous soft matter network of interconnected chambers and constrictions. Transport is anomalous and antipersistent, with strong length dependent confinement and trapping, consistent with obstructed diffusion. Unexpectedly, however, escape from confinement is poorly sensitive to nanotube length as opposed to what would be expected of pore mediated transport. Despite a tenfold length increase and significantly enhanced trapping, escape time increased by only ~1.4. Single-particle orientational tracking reveals the origin of this weak scaling. Indeed, long nanotube, i.e. those with length comparable to the chamber dimensions, dynamically align with constrictions enabling efficient, geometry-assisted escape that offsets increased confinement while shorter nanotubes need to screen the volume to find their escape path. These results uncover an alignment-mediated transport mechanism that decouples confinement strength from escape kinetics, distinct from pore-mediated transport mechanisms, establishing a quantitative framework for anisotropic diffusion in complex environments.
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All authors Rohit Mangalwedhekar, Limeng Ruan, Somen Nandi, Quentin Gresil, Marc Tondusson, Stephane Bancelin, Lea-Laetitia Pontani, Laurent Cognet

Fluid Dynamics

Full-component reconstruction of three-dimensional fluid stress tensors

Shunsuke Kumagai, Shun Miyatake, Ryusuke Cho et al. (+5 more)

Forces govern how fluids deform biological tissues, regulate cardiovascular function, and determine the performance and failure of soft materials. Recent advances in flow birefringence, including the use of suspended anisotropic nanomaterials to optically encode stress in fluids, have made direct stress measurement experimentally accessible in projection. However, direct experimental access to all six components of the three-dimensional (3D) fluid stress tensor has remained unattainable because optical measurements provide only path-integrated observables. Recovering local 3D stresses from such data constitutes an intrinsically underdetermined tensor tomography problem, where two optical observables must determine six independent stress components. Here we introduce U-FlowPET, an unsupervised physics-informed framework that integrates photoelastic tomography with the governing equations of fluid mechanics to reconstruct the full 3D stress tensor without relying on constitutive assumptions, geometric symmetry, or labeled training data. Rather than learning from labeled reference stress fields, the method identifies physically admissible stress fields that satisfy momentum balance and continuity while remaining consistent with measured optical projections. We validate the approach using analytical, numerical, and experimental datasets. In axisymmetric pipe flow with an analytical solution, all six stress components are reconstructed with normalized mean absolute errors below 4%. Robust reconstruction is further demonstrated in curved-pipe flow without symmetry assumptions and in experimental pipe-flow data despite measurement noise. By enabling direct 3D stress-field reconstruction from optical data alone, U-FlowPET extends fluid analysis from observing motion to quantifying force and establishes a new framework for stress-based diagnostics in biological flows and functional materials.
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All authors Shunsuke Kumagai, Shun Miyatake, Ryusuke Cho, William Kai Alexander Worby, Masanori Naito, Takahiro Ushioku, Masanobu Horie, Yoshiyuki Tagawa

Physics and Society

SpinFlow: A Physics-Informed Spin Field Framework for Traffic Phase Inference and Transition Detection

Haopeng Deng, Fucheng Zheng and Xinhai Xia

Active traffic management (ATM) is frequently hindered by traditional macroscopic models and rigid empirical thresholds that fail to capture metastable phase precursors, resulting in delayed, reactive interventions. To address this, we propose SpinFlow, a physics-informed spin-field framework unifying Kerner's three-phase theory with statistical physics for continuous macroscopic traffic phase inference. Inspired by the Heisenberg model, SpinFlow parametrizes spatially varying phase weights via a latent spin vector and a competitive-equilibrium mapping, allowing synchronized flow to emerge naturally. A physics-regularized Expectation-Maximization algorithm inverts this latent structure from high-resolution trajectories, jointly optimizing the spin field while softly enforcing mass conservation and spatial smoothness. We introduce the Phase Equilibrium Degree (PED) to quantify structural alignment and topologically localize phase-transition points. Across four real-world trajectory datasets, SpinFlow achieves $R_{q}^{2}$ up to 0.940, PED drops of 94.9-100%, and interpretable phase maps that outperform three heterogeneous baselines on forward accuracy, physics consistency, and bottleneck localization. SpinFlow pinpoints congestion nucleation without prior network topology, yielding a data-driven, physics-consistent trigger for ATM.
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Fluid Dynamics

On the Applicability of the Gas-Kinetic Scheme with Kinetic Boundary Conditions for Near-Continuum Hypersonic Flows

Wenpei Long, Junzhe Cao, Yue Zhang et al. (+1 more)

Rarefied gas effects are of critical importance for the aerodynamic performance of hypersonic vehicles operating at high altitudes. In these scenarios, conventional computational fluid dynamics (CFD) solvers break down as the linear constitutive relations underlying the Navier-Stokes equations cease to be valid. Based on direct modeling, the unified gas-kinetic scheme (UGKS) and the unified gas-kinetic wave-particle (UGKWP) method successfully capture non-equilibrium physics across all Knudsen numbers, yet they incur substantially higher computational costs than continuum solvers. Within the same kinetic framework, the gas-kinetic scheme (GKS) employs the Chapman-Enskog expansion for near-equilibrium flow physics and adopts the same kinetic boundary conditions as UGKS and UGKWP. This formulation naturally permits velocity slip and temperature jump, thereby extending the applicability of GKS into the slip and transitional regimes. By utilizing this natural kinetic slip boundary condition, the GKS provides a more physically faithful representation of non-equilibrium wall interactions than conventional CFD solvers equipped with Maxwell-type slip conditions, ultimately yielding more accurate aerodynamic predictions. To determine the applicability of the GKS in near-continuum flow regimes, we first examine a simple circular cylinder geometry, comparing surface quantities and distribution functions in detail. Furthermore, we investigate a 9{\deg}blunted cone, a 70{\deg} blunted cone with a cylindrical sting, and the Apollo 6 command module. This analysis focuses on integrated aerodynamic predictions, which are validated against experimental data, Direct Simulation Monte Carlo (DSMC) simulations, and other kinetic methods.
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All authors Wenpei Long, Junzhe Cao, Yue Zhang, Kun Xu

Optics

Accelerating ground state search of spatial photonic Ising machines with genetic-simulated annealing hybrid algorithm

Ze Zheng, Ruhui Ni, Jingyi Zhao et al. (+6 more)

Spatial photonic Ising machines (SPIMs) based on spatial light modulators (SLMs) have emerged as highly effective solvers for many tasks, including combinatorial optimization problems and spin-glass simulations. However, traditional SPIMs relying solely on the simulated annealing algorithm require a large number of measurement-feedback iterations to find a relatively optimal solution in complex energy landscapes, suffering from slow convergence and high time cost. Here, we propose an optical genetic-simulated annealing hybrid algorithm to accelerate the ground-state search of SPIMs. GA conducts a global coarse-grained search in the early iteration stage, while SA performs fine-grained local refinement in the late stage. Numerical simulations show that our method enables a higher solution quality of full-rank Max-Cut problems than pure GA or SA at different scales. We also experimentally demonstrate its superiority over conventional algorithms on a gauge-transformation time-division multiplexing SPIM for high-rank optimization problems under the same iteration budget. Our approach can be further developed with other advanced metaheuristic algorithms toward intelligent optical Ising computing systems.
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All authors Ze Zheng, Ruhui Ni, Jingyi Zhao, Xiaojian Hu, Wen Jiang, Yuegang Li, Hang Xu, Tailong Xiao, Guihua Zeng

Geophysics

Differentiating Eulerian and Lagrangian Tendencies in the Ocean Interior via a Dynamical Overturning Decomposition

Lei Han

Repeat observations provide essential constraints on long-term changes in the ocean interior, such as warming and cooling trends. However, attributing these Eulerian signals to either reversible isopycnal heaving or irreversible diabatic transformations remains a fundamental challenge. This ambiguity arises not only from limited velocity observations, but also from the lack of a diagnostic framework capable of explicitly disentangling Lagrangian transformation from Eulerian variability. Recognizing that Eulerian and Lagrangian tendencies can be represented through distinct perspectives of the overturning circulations, we apply a dynamical overturning decomposition to state-of-the-art reanalysis products in the Atlantic, Indo-Pacific, and South China Sea to investigate their long-term behavior. The utility of this framework is supported by strong correlations between independently derived kinematic and thermodynamic indices, indicating a tight coupling between advective and isopycnal-heaving transports. Our analysis reveals distinct dynamical regimes in which similar Eulerian tendencies arise from fundamentally different Lagrangian processes. In particular, we identify (i) previously undiagnosed diapycnal downwelling, despite its prediction by bottom-intensified turbulent dissipation, (ii) coexistence of apparent Eulerian upwelling and diapycnal downwelling, (iii) an Atlantic sub-overturning cell linked to intermediate water-mass formation, and (iv) cases where Eulerian densification masks Lagrangian lightening. These results demonstrate that Eulerian trends alone can be misleading indicators of reversible and irreversible behaviors. By explicitly separating adiabatic heaving from diabatic processes, this framework offers a physically consistent diagnostic for interpreting interior ocean changes and establishes a dynamical basis for assessing the reversibility of such changes.
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Atomic Physics

Attosecond shaping of high-current pulsed electron beams in a home-built 37-keV beamline

Yuichi Tachibana, Marie Ouillé, Takuya Hosobata et al. (+4 more)

Ultrashort electron pulses with a high average current provide a powerful means of enhancing time-resolved imaging and photon generation. In this study, we report the attosecond shaping of sub-relativistic electron beams using membranes in a newly developed apparatus that delivers a relatively high current (>2 electrons per pulse on a sample) with negligible space-charge effects. Optimizing the membrane arrangement minimizes the spread of electron-light delays to within a femtosecond over a wide range of incident angles. This enables the recording of attosecond streaking spectrograms, where net acceleration and deceleration, as well as monochromatization and energy broadening, are clearly observed. Through comparison with models, we estimate the durations of the bunched electrons to be 1.3 fs (FWHM) and 0.5 fs (RMS). Furthermore, we demonstrate the attosecond modulation of pulsed beams with a large energy spread originating from space charge effects. A modulation amplitude of 2 eV is shown to be sufficient to shape a beam with an initial spread of 15 eV (FWHM). These results represent a significant step toward the generation of an attosecond pulse containing one or more electrons.
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All authors Yuichi Tachibana, Marie Ouillé, Takuya Hosobata, Takashi Isoshima, Yoshiyuki Takizawa, Yutaka Yamagata, Yuya Morimoto

Applied Physics

Optimal designs of heterogeneous grid transit networks

Wenbo Fan, Haoyang Mao, Li Zhen et al. (+1 more)

A general Continuum Approximation (CA) model is proposed for optimizing transit network designs (TND) in grid cities under spatially heterogeneous demand. While conventional studies often assume rigid geometric line configurations (e.g., unbranched orthogonal grids), our framework allows the grid bus lines to route more flexibly by making lateral movements and to form network configurations with line detouring, merging, and diverging. The resulting line and stop densities, as well as service headways, vary continuously across both directions of the city, constrained solely by vehicle flow conservation. By respecting non-uniform demand distributions, our heterogeneous networks substantially enlarge the class of heterogeneous network designs that can be represented and optimized within a tractable CA framework. To efficiently solve the optimization problem, we develop a sequential geometric programming framework that transforms the model into a sequence of standard geometric programming problems. Numerical experiments validate the accuracy of the proposed model and the solution method by comparing system metrics estimated by the CA models against the actual values computed from the discretized network designs. Under representative spatially heterogeneous demand scenarios, comparisons demonstrate that our model effectively reduces generalized costs by over 7% against existing homogeneous and restricted heterogeneous TND models. Key findings indicate that: (i) the proposed framework consistently outperforms these conventional counterparts across all tested scenarios; (ii) the fully heterogeneous structure becomes particularly advantageous when patron demand exhibits strong spatial heterogeneity; and (iii) these flexible designs yield the greatest benefits in high-demand, low-wage, and large-area cities.
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All authors Wenbo Fan, Haoyang Mao, Li Zhen, Weihua Gu

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

Pulsed thermal annealing enables switching of chiral antiferromagnetic order with a sub-millitesla field in Mn$_3$Sn

Xiaokang Li, Jing Zhang, Xiaodong Guo et al. (+1 more)

The manipulation of antiferromagnetic (AFM) order is a central theme in modern spintronics. In this work, we achieve reliable switching of the chiral AFM state in the Weyl antiferromagnet Mn$_3$Sn using a heat pulse combined with a very small magnetic field as small as 0.1 mT. By systematically measuring the anomalous Hall effect (AHE) in high-quality single crystals, we show that the field needed for switching decreases as the temperature approaches the Néel temperature $T_N$, and vanishes at $T_N$. Pulsed thermal annealing above $T_N$ followed by cooling in a tiny external field enables full and reproducible switching of the magnetic octupole order. Our results show that thermal softening (heating above $T_N$ to temporarily remove the magnetic anisotropy) is a key step that lowers the energy barrier to nearly zero. This allows an extremely weak directional field (like the effective field from spin-orbit torque in thin-film devices) to set the final magnetic state during cooling. We also provide a simple model to estimate the temperature rise in nanoscale devices under current pulses, giving practical guidance for device design. This work highlights that thermal effects are not a side issue but an important partner to spin torques, and suggests that future work should take both into account.
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All authors Xiaokang Li, Jing Zhang, Xiaodong Guo, Zengwei Zhu

Fluid Dynamics

Free surfaces in turbulence - A unified framework from water surfaces to elastic solids

Giulio Foggi Rota, Andrea Mazzino and Marco Edoardo Rosti

What do the ocean surface and a swaying flag have in common? Both are deformable surfaces exhibiting chaotic motion when exposed to turbulent flows. Whether such motion is primarily driven by flow turbulence or by nonlinear dynamics intrinsic to the surface remains debated. Surface waves can interact nonlinearly and transfer energy across scales through the cascade of wave turbulence, a behaviour observed at interfaces between otherwise quiescent fluids and in controlled laboratory experiments. They can as well induce turbulent motions in the neighbouring fluids (wave-induced-turbulence), provided the local Reynolds number is large enough. Realistic environments, however, are more complex and typically involve the simultaneous presence of wave turbulence and wave-induced-turbulence with turbulence-induced-waves, the dynamic relevance of which remains unclear. Here we develop a theoretical framework describing the response of a deformable surface to pressure fluctuations generated by a turbulent flow, and validate it using numerical simulations of the air-water interface in quasi-realistic conditions, complemented by simulations of a deformable rubber layer. Our linear theory, which excludes nonlinear wave-wave interactions, predicts distinct dynamical regimes depending on whether intrinsic surface dynamics emerge or whether the interface is enslaved by flow turbulence. Remarkably, although our fully resolved and nonlinear simulations do not inhibit the onset of wave turbulence, interface spectra measured in the configurations studied here are controlled at leading order by turbulent pressure forcing and linear surface response, in strong agreement with our theoretical assumptions. Our predictions appear compatible with aerial surveys of the ocean surface, highlighting the need for further measurements to distinguish among wave turbulence and turbulence-induced-waves.
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Optics

Mid-infrared nonlinear pinhole imaging

Yanan Li, Kun Huang, Jianan Fang et al. (+2 more)

Pinhole imaging is the most primitive and simplest lensless imaging paradigm, capable of transcending the physical limitations of conventional lens optics. This modality is particularly attractive for accessing a virtually infinite depth of focus or operating at extreme wavelengths. Here, we devise and implement a mid-infrared (MIR) pinhole imaging system at 3.07 $\mu$m based on nonlinear spatial filtering. Instead of using a physical aperture, the involved pinhole is optically formed by a near-infrared pump at 1.03 $\mu$m within a nonlinear crystal, which allows flexible and precise control over the effective aperture size to optimize imaging performance. Meanwhile, the MIR rays passing through the nonlinear pinhole are spectrally upconverted to facilitate sensitive imaging via a silicon camera. Consequently, the implemented upconversion pinhole imaging enables a large depth of field over 35 cm, beyond the reach of typical lens-based upconversion imagers. Furthermore, depth-resolving imaging across a large depth range is demonstrated in both the reflection and transmission modes based on time-of-flight and trigonometric techniques, respectively. The achieved capabilities – featuring large operation depth, wide field of view, and flexible adaptability to various illumination conditions – highlight the potential of the presented MIR imaging architecture for expansive scene detection and motion-aware applications in industrial inspection and night vision.
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All authors Yanan Li, Kun Huang, Jianan Fang, Zhuohang Wei, Heping Zeng

Optics

Mid-infrared single-pixel imaging via two-photon optical encoding

Huijie Ma, Kun Huang, Jianan Fang et al. (+3 more)

Mid-infrared (MIR) imaging offers powerful capabilities for label-free chemical analysis, yet its practical deployment remains hindered by the high cost and cryogenic complexity of conventional cameras. Two-photon absorption (TPA) provides a promising route to room-temperature MIR detection, but existing TPA imagers based on raster scanning or array detectors are constrained by slow acquisition speed or limited detection sensitivity. Here we present a scanning-free MIR single-pixel imaging approach based on non-degenerate TPA in a silicon detector. The involved spatial encoding is realized by a near-infrared structured pump with a resolution of 7 $\mu$m, thus allowing high-fidelity MIR optical modulation through the phase-matching-free nonlinear interaction. Consequently, the spatially modulated TPA response is intrinsically integrated in the single-element photodetector, which favors computational reconstruction of the impinging MIR image by correlating measured intensities and predetermined patterns. Notably, the use of advanced algorithms of compressed sensing and deep learning facilitate image recovery under sub-Nyquist sampling with a compression ratio of 10% and photon-starved illumination with an incident light flux of 0.5 pJ/pulse. Furthermore, a multispectral imaging over 2.5-3.8 $\mu$m is manifested for chemical discrimination of plastic films. The presented architecture would offer a broadband and sensitive alternative for MIR imaging in various fields ranging from biomedical diagnostics to material inspection.
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All authors Huijie Ma, Kun Huang, Jianan Fang, Ziyu He, Yan Liang, Heping Zeng

Plasma Physics

NIMROD-to-IMAS workflow for extended-magnetohydrodynamic data with reusable datasets and implications for IMAS schema development

Alexei Y. Pankin, Fatima Ebrahimi, Qian Gong et al. (+5 more)

Extended magnetohydrodynamic (MHD) simulations of tokamak plasmas regularly produce outputs in multi-dimensional, multiple-field formats; these code-specific formats make it difficult to do cross-code validation/coupling and analyze at a database scale. In this paper, a workflow that converts NIMROD code inputs and outputs to records compatible with version 4 of the ITER IMAS Data Dictionary is presented. The scope of the workflow includes preprocessing of NIMROD code inputs, conversion of hierarchical NIMROD code HDF5 dumps, COCOS-consistent treatment of the coordinate system and sign convention, and encoding finite-element poloidal meshes and toroidal Fourier components through IMAS General Grid Description. Furthermore, the workflow allows for provenance and integrity metadata to be included while providing optimal I/O operations for large array structures. An example conversion based on an NIMROD code simulation of edge harmonic oscillations performed for the DIII-D discharge 163518 [A.Y. Pankin, et al., Nuclear Fusion 60.9 (2020), p. 092004] is used to validate the conservation of essential equilibrium, profile, perturbation, and grid data in the resulting IMAS records. Finally, this implementation exposes gaps in the current IMAS framework that need to be addressed to accommodate extended MHD data, and it highlights the metadata, provenance, and governance needs of the downstream use cases in the form of dataset validation, integration, and machine learning.
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All authors Alexei Y. Pankin, Fatima Ebrahimi, Qian Gong, Jacob King, Andreas Kleiner, Jesus Dominguez-Palacios, Norbert Podhorszki, Eric Suchyta

Thursday 21 May

Classical Physics

Tensile wrinkling and creasing of an elastic half-space under a suction load

Roberta Springhetti and Davide Bigoni

A famous and thoroughly investigated instability set-up, susceptible to wrinkling and creasing, consists of an elastic half-space being prestressed under a dead load, applied at infinity and, possibly, on its surface. We consider the case of a pressure or a suction applied on the surface and show that wrinkling and creasing occur in a surprising way, completely different from dead load. With reference to incompressible neo-Hookean elasticity and assuming the prevalence of a uniaxial prestress state induced by the application of a uniform pressure, no wrinkling or creasing is foreseen, whereas – unexpectedly – they do when reversing the sign of pressure, which is then a suction, thus leading to tensile creasing and tensile wrinkling. When a biaxial prestress state is considered, it is shown that some loading paths can be envisaged, able to grow to infinity without causing any instability. Consequently, we suggest that, according to its sign, pressure can promote or delay surface instabilities, a finding which may have implications for mechanobiology or microfluidic fluid-structure interaction.
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Space Physics

Aurora Hunter: A Two-Stage Framework for Probabilistic Visibility Forecasting

Zongyuan Ge, Chenwaner Zhang, Haoyang Li et al. (+4 more)

Aurora visibility at a given location requires two physically distinct conditions to hold at once: aurora occurring overhead, governed by solar wind-magnetosphere coupling, and observing conditions that permit detection, governed by cloud cover and moonlight. Approaches that conflate the two weaken the space-weather signal and limit cross-site generalizability. We develop Aurora Hunter, a two-stage cascade that separates occurrence prediction from observing-condition assessment. Stage 1 uses 43 physics-driven features to predict P(aurora identifiable in all-sky images) via gradient-boosted trees trained on joint Tromso+Kiruna data (about 16,600 hours, 2015-2023). Stage 2 models P(unobscured image class | identifiable) with logistic regression on 15 observing-condition features, trained on hours with identifiable aurora. The cascade P(visible) = P(identifiable) x P(unobscured | identifiable) achieves retrospective ROC-AUC of 0.958 (Tromso test, 2019-2020) and 0.933 (independent Kiruna, 2024), improving on the occurrence stage used alone by +0.095 and +0.097. Transfer to Skibotn, the one station withheld entirely (2022-2025), is limited. SHAP analysis identifies magnetic local time, the Kp x nightside interaction and the three-hour mean Kp as the dominant features (44% of attribution), consistent with auroral oval physics. Hemisphere-wide occurrence maps combine the Stage 1 amplitude, on a clear-sky basis, with the Feldstein oval parameterization. By providing location-specific visibility probabilities with measured reliability rather than coarse geomagnetic indices, the framework links space weather research to practical observation planning. An operational proof of concept is available at https://aurora-hunter.onrender.com
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All authors Zongyuan Ge, Chenwaner Zhang, Haoyang Li, Hantai Zhang, Wei Zhou, Wenxin Gu, Zhaoming Wang

Atmospheric and Oceanic Physics

Volador 1.0: A Data-Driven Air-Sea Full-Coupling Regional Forecast Model with Submesoscale-Permitting Based on MOE-Swin-Transformer Framework

Yuhang Zhu, Jianxin Wang, Yu-kun Qian et al. (+6 more)

A data-driven air-sea full-coupling regional forecast model with submesoscale-permitting, named "Volador 1.0", is developed for the South China Sea (SCS). The model features a Swin-Transformer framework integrated with a Mixture-of-Experts (MoE) system, a latent space interaction architecture based on Cross-Grid Bidirectional Cross-Attention, and a fast-slow dual-branch architecture. Both the three-month hindcast test and the 15-day operational real-time forecasting demonstrate that Volador 1.0 has a very encouraging and promising performance in 0-72h forecasting of temperature and salinity in the 0-500m upper ocean as well as the sea surface height with root-mean-square-error (RMSE) or mean absolute error (MAE) smaller than or at least comparable to those from the reanalysis datasets REDOS V2.0 and GLORYS12 and the state-of-the-art regional numerical model Regional Ocean Modeling System (ROMS). In particular, Volador 1.0 demonstrates its capability of capturing/forecasting submesoscale processes including internal waves, with an energy spectrum well representing sub- to mesoscale energy cascade as expected by the classical turbulence theory. Further analysis based on ablation experiments shows that the air-sea full-coupling framework, which takes into account the dynamic exchanges of momentum and heat fluxes between the atmosphere and the ocean, indeed helps improve the model's performance compared to the non-full-coupling one. Volador 1.0, though still subject to refinement in the coming future with a large space for improvement, blazes a path for an accurate, fine and fast marine environment forecasting, and thus could help promote our capability of disaster prevention and mitigation in the SCS as well as in other coastal regions where these innovative techniques can be applied.
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All authors Yuhang Zhu, Jianxin Wang, Yu-kun Qian, Yineng Li, Yahui Liu, Yankun Gong, Shilin Tang, Shiqiu Peng, Tao Song

Medical Physics

Multinuclear fingerprinting

Gonzalo G. Rodriguez, Zidan Yu, Lauren O'Donnell et al. (+2 more)

We developed a new magnetic resonance imaging method called multinuclear fingerprinting (MNF) which leverages simultaneously-acquired proton (1H) and sodium (23Na) data to generate seven quantitative maps of the whole brain: proton density (PD), T1 and T2 relaxation times from water, and tissue sodium concentration (TSC), T1, T2short and T2long from Na+ ions. MNF consists of two parts: (1) simultaneous 1H/23Na magnetic resonance fingerprinting (MRF), and (2) a super-resolution (SR) algorithm to increase the 23Na resolution to match the 1H resolution. It was tested on the brain of seven healthy subjects at 7 T, with a final resolution of 1.5x1.5x5 mm3 for all maps acquired in 13 min. MNF could provide new fundamental insights into the inter-relationship between morphology (i.e. tissue structure from the 1H maps) and physiology (i.e. ion homeostasis from the 23Na maps) in vivo to help improve our understanding of the human brain in general, and to study neuropathologies and their treatments. Since all 1H/23Na MRF data is acquired simultaneously, all images are exactly co-registered with identical spatial and temporal resolutions. MNF could be useful in future longitudinal studies for assessing local time-dependent and conjoint 1H/23Na MR changes during tasks or interventions. MNF was initially developed for neuroimaging, but it can be adapted to any other parts of the body.
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All authors Gonzalo G. Rodriguez, Zidan Yu, Lauren O'Donnell, Martijn A. Cloos, Guillaume Madelin

Optics

General-Purpose Photonic Computing Primitive for Contemporary Artificial Intelligence

Shupeng Ning, Chenghao Feng, Zhenxiang Xu et al. (+4 more)

Photonic computing offers a promising route to accelerating artificial intelligence (AI) by providing high analog bandwidth, low latency, and low energy consumption. However, existing optical neural networks (ONNs) struggle with substantial hardware overhead and limited support for the dynamic, arbitrary matrix operations essential for modern AI architectures. Here we present the dynamic universal encoding tensorcore (DUET), a general-purpose photonic computing paradigm based on vectorized operand differential interferometric cells (VODICs). By exploiting inherent structural symmetry, this design provides a full-range linear encoding interface that directly accommodates signed operands. This approach eliminates the sign-based path splitting, nonlinear remapping, and auxiliary preprocessing typically required in conventional ONNs, thereby reducing latency and minimizing hardware and memory overhead. We further implement a hardware-aware training (HAT) strategy to alleviate the impact of on-chip non-idealities and ensure stable inference. DUET is experimentally validated across diverse architectures and application domains, ranging from image classification and medical segmentation to Transformer-based content generation, demonstrating competitive performance. By extending optical computing to universal, full-range operators across diverse model architectures, DUET provides a viable pathway toward general-purpose optical acceleration for contemporary AI workloads.
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All authors Shupeng Ning, Chenghao Feng, Zhenxiang Xu, Hanqing Zhu, David Z. Pan, Jiaqi Gu, Ray T. Chen

Fluid Dynamics

Weakly nonlinear interaction of capillary waves in a finite system: leading interaction process and scales' range of direct energy cascade

Alexander O. Korotkevich

During comprehensive study of weakly nonlinear interaction of surface capillary waves, processes of resonant and non-resonant interactions were considered both numerically and analytically: merging of two waves into one and waves on the ring (in Fourier space, isotropic spectrum) into larger diameter ring. It was shown numerically, that these resonant processes are the leading ones and other processes with respect to them are at least weaker if manifest themselves at all. It was confirmed, that resonant the processes are the major ones which contribute to the long time dynamics. In the case of isotropic turbulence of capillary waves the formation of wave turbulence's Zakharov-Filonenko spectrum is demonstrated. It was also shown, that this spectrum in finite systems has a finite range of scales. Due to finiteness of the numerical simulation or experimental area the discreteness of the wavenumbers grid arrest local in Fourier space resonant interaction when smaller scales are considered. Scaling of the range of realization of the Zakharov-Filonenko spectrum, depending on main parameters of the numerical or experimental setup (average steepness and characteristic size), is derived analytically and partially confirmed numerically.
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Fluid Dynamics · Cross-listed from cs.LG

Open datasets and machine learning for two-phase heat transfer: a review following a spatial-temporal taxonomy

Christy Dunlap, Ridwan Olabiyi, Firas Al-Hindawi et al. (+9 more)

Two-phase heat transfer underpins boiling, condensation, immersion cooling, flow boiling, energy conversion, and electronics thermal management, but its coupled interfacial physics make data reuse and model comparison difficult. This narrative review synthesizes open datasets, machine-learning methods, and reusable software for two-phase heat-transfer research, with emphasis on boiling, multimodal sensing, and thermal-management datasets. We organize the review around a spatial-plus-temporal dimensionality taxonomy, denoted S+TD, that classifies data objects by the dimensionality of the measured, simulated, or derived fields, including 0+0D point values, 0+1D time series, 1+1D profiles, 2+0D images, 2+1D videos, 3+0D/3+1D fields, and mixed multimodal records. The taxonomy is used to connect dataset types to AI tasks such as tabular regression, acoustic sequence learning, image segmentation, video analysis, inverse heat-flux reconstruction, surrogate modeling, and multimodal fusion. The review also develops a roadmap for physics-aware open data, including metadata definitions, evidence and reuse-maturity labels, benchmark splits, decoders, baseline models, and community databanks. NED3 resources are discussed as one implementation case within a broader open-data ecosystem rather than as a complete solution. The main conclusion is that progress in two-phase AI now depends as much on findable, decodable, benchmarkable, and physically interpretable data infrastructure as on model architecture.
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All authors Christy Dunlap, Ridwan Olabiyi, Firas Al-Hindawi, Hari Pandey, Stephen Pierson, Daniel Curl, Braden Stevens, Mohammad Ishraq Hossain, Annapurna Parjuli, Chinmaya Joshi, Ashif Iquebal, Han Hu

Plasma Physics

Pre L-H Transition Radial Electric Field and Transport Validations of Edge and Scrape-off Layer Gyrokinetic Simulations at ASDEX Upgrade

B. J. Frei, C. Angioni, G. Lo-Cascio et al. (+5 more)

This work presents a stepwise validation of the evolution of the radial electric field (Er) and heat transport during the pre L-H transition phase using full-f gyrokinetic simulations of the edge and scrape-off layer in the ASDEX Upgrade (AUG) tokamak, including X-point geometry. Several L-mode time slices up to the L-H transition from a dedicated hydrogen discharge, featuring stepwise increases in ECRH input power, are selected [N. Bonanomi et al., Phys. Plasmas 31, 072302 (2024)] and simulated with the GENE-X code. As the edge boundary conditions are progressively increased between the time slices, particle and heat fluxes rise, and the radial electric field Er well deepens. A detailed validation of the Er profiles and of the Er well depth shows excellent agreement with experimental measurements at the successive time slices approaching the L-H transition. A force balance decomposition identifies turbulence-driven poloidal flows as the dominant contribution within the Er well. Edge turbulence is governed by a competition between electron drift waves and trapped-electron modes. The introduction of an edge density source, modeling neutral gas ionization, is shown to be essential to reproduce experimentally relevant density profiles, Er, and edge ion heat fluxes, which are dominated by both turbulent and diamagnetic contributions. This stepwise validation constitutes an important milestone toward predictive, first-principles gyrokinetic simulations of the L-H transition power threshold.
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All authors B. J. Frei, C. Angioni, G. Lo-Cascio, W. Zholobenko, P. Ulbl, R. Bilato, F. Jenko, the ASDEX Upgrade Team

Computational Physics

Full-Scattering-Matrix Deterministic Phonon Boltzmann Transport Simulation

Y. Sungtaek Ju

Solutions to the phonon Boltzmann transport equation under the relaxation-time approximation (RTA) are fundamentally limited in that they do not account for the off-diagonal elements of the scattering matrix, which encode intermode energy redistribution. We find that the phonon in-scattering matrix is globally incompressible, requiring nearly its full rank for any useful Frobenius accuracy. The incompressibility worsens as the Brillouin zone is refined. We show that, despite this difficulty, one can develop a computationally efficient 3D BTE solver incorporating the complete scattering matrix by leveraging our two structural discoveries: the non-equilibrium phonon distribution inhabits a remarkably low-dimensional subspace of mode space regardless of how many phonon modes exist, and the leading singular modes of the scattering operator align selectively with this transport-active subspace. Consequently, truncation incurs negligible transport error even under large norm error. The phonon streaming operator's mode-diagonal character further motivates a hybrid architecture that exploits these two properties. When applied to nanoscale structures emulating a fin field-effect transistor, our BTE solver quantifies a geometry-independent multiplicative correction to the temperature rise predicted under RTA. Our theoretical work and resulting BTE solver help enable rigorous study of phonon transport and systematic design of devices and structures in the ballistic and quasi-ballistic phonon transport regime.
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