Fluid Dynamics
A Residual Learning Approach for Unsteady Aerodynamic Load Prediction
Divya Sanghi and Carlos E. S. Cesnik
This paper investigates the feasibility of using residual learning to improve unsteady aerodynamic load prediction for aeroelastic applications. The machine learning technique selected for the study is the long short-term
memory (LSTM) neural network, which is used for its suitability for sequential data with aerodynamic
memory effects. The approach is investigated for the NLR 7301 airfoil
benchmark using high-fidelity CFD lift data for prescribed pitch and plunge motions in the transonic flow regime in the presence of shock motion. An analytical unsteady aerodynamic model based on the Wagner function is used as a physics-based baseline, and the neural network is trained to learn the difference between the CFD lift coefficient and the Wagner prediction. The residual model is compared with a direct neural-network model trained to predict the CFD lift coefficient. The comparison includes feature and normalization studies, external
benchmark cases, and leave-one-out and leave-family-out generalization tests across a range of sinusoidal and non-sinusoidal motions. The residual model performs best when its inputs align with the Wagner formulation variables, generally giving lower error and more consistent performance across training runs, though the direct model remains more accurate for some high-frequency cases. The residual model also generalizes better in the leave-one-out and leave-family-out tests, with a smaller increase in error than the direct model when entire motion families are withheld from training. Overall, the results indicate that residual learning shows promise as a modular approach for augmenting classical low-order aerodynamic theories, especially when the physics baseline removes a structured part of the aerodynamic response and leaves a lower-variance correction for the neural network to learn.
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Chemical Physics
Benchmarking Least-Squares Tensor Hypercontraction Techniques for Molecular Systems
Niklas Paulicks and Johannes Tölle
Finding a low-rank approximation for the two-electron integral (ERI) tensor is a crucial step towards reducing the computational cost of many-body electronic structure methods. In recent years, a range of new tensor factorization techniques, like the so-called tensor-hypercontraction (THC) approach, have been developed to achieve this goal. Unfortunately, a systematic comparison of accuracy and efficiency of different THC construction
algorithms is missing. In this work, we address this gap by benchmarking these techniques across a wide range of molecular systems. In addition to offering useful insights into the advantages and disadvantages of the different techniques, we provide reference implementations in the newly developed open-source library, PyTHC.
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Computational Physics
Investigation of the Asymptotic Properties of Active Impedance in Large Finite Array Antennas
Harald Hultin, Lucas Åkerstedt and B. L. G. Jonsson
This paper presents an improved full-wave solver for finite array
antennas, and uses this solver to examine asymptotic properties of active impedance for large regular arrays. The improved solver is based on a preconditioning scheme that has been adapted for use on more general finite geometries, and an improved data structure. These two improvements result in a fast and stable solver with a lower
memory footprint. By investigating the active impedance of finite arrays it is found that, even for arrays with 1000 elements, asymptotic behavior may differ from infinite arrays. Tied to these properties, different predictors on how the active impedance of the center element in the array behaves are presented. The two best predictors work very well for the wideband arrays investigated, and may be used to decide when array approximations, such as unit
cell methods, are appropriate, rather than general statements on array size.
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Plasma Physics
Control of Magnetic Reconnection in High Energy Density Plasmas
J. L. Latham, B. K. Russell, C. Dong et al. (+6 more)
Magnetic reconnection governs the explosive release of
magnetic energy in systems from the
solar corona to fusion
plasmas, yet controlling it in the laboratory has remained out of reach. Here we demonstrate active control of reconnection in high-power
laser-driven
plasmas using a third, relativistic-intensity
laser pulse that injects filaments of electron current into the reconnecting system. Two moderate-intensity
lasers drive colliding magnetized plumes that reconnect, forming plasmoids in the current sheet as seen in
proton deflectometry. The relativistic
laser generates
magnetic fields matching the polarity on either side of the layer, and, depending on its arrival time, either accelerates the breakup of the current sheet or suppresses reconnection. Arriving early, before the plumes strongly interact, it builds a pocket of
magnetic pressure that repels them via flux pileup; arriving after the current sheet forms, it accelerates electrons that extend current filamentation instabilities into the upstream, causing rapid dissipation of the reconnecting
magnetic field. This approach opens a route to steering
magnetic energy flow in fusion
plasmas and broadens the range of systems accessible to laboratory astrophysics.
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All authors J. L. Latham, B. K. Russell, C. Dong, C. A. Walsh, K. G. Miller, P. T. Campbell, L. Willingale, P. Nilson, K. Krushelnick
Fluid Dynamics
Towards Rapid Prototyping of Spray Injectors: A Regime-Agnostic Neural Operator Surrogate for Gas-Liquid Interface Evolution
Paolo Guida, Po-Han Chen, Hong G. Im et al. (+1 more)
Spray atomisation rapidly creates large
liquid-gas interfacial areas and is central to many industrial processes. However, predicting spray behaviour and surface area remains difficult: experiments cannot access all spray regions, while CFD becomes prohibitively expensive as finer structures develop. Data driven surrogates can learn interface
evolution, enabling rapid design space exploration, operating condition ranking, and ultimately spray control. We investigate how state representation, neural architecture, and physics-informed regularisation affect long horizon autoregressive
forecasting of spray interfaces, particularly conservation. Our principal model is a boundary-conditioned
Fourier Neural Operator (FNO) that predicts the
evolution of the signed distance function (SDF) from the
liquid-gas interface. It is trained on 2D sharp interface Volume-of-Fluid CFD simulations spanning several atomisation regimes. The SDF-FNO retains interface fidelity better than an FNO trained directly on volume fraction, but is outperformed by a U-Net. Objective function ablation shows that a
liquid inventory penalty improves conservation at a modest cost to local interface accuracy. We also introduce a physics-informed extension combining an open-domain target-increment
liquid balance penalty, a narrowband Eikonal regulariser that preserves signed distance geometry, and a phase-boundedness penalty. Although this model trains stably, it leaves forecast error, interface overlap, and inventory behaviour essentially unchanged relative to the data driven baseline. Finally, we demonstrate the surrogate by ranking injection conditions according to interfacial area generated per unit gas injection power across the operating envelope of a fixed geometry.
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All authors Paolo Guida, Po-Han Chen, Hong G. Im, William L. Roberts
Physics and Society
Spatially explicit feature importance for building height estimation using research-access high-resolution SAR and optical sensors
Guilherme Iablonovski, Pierre-Louis Frison and Tatiana Silva da Silva
Accurate building height information at the individual footprint scale is essential for material stock accounting and post-disaster damage assessments yet remains difficult to obtain at city scale in the Global South where airborne
LiDAR coverage is rare and commercial very high-resolution imagery is cost-prohibitive or unavailable. While recent works have demonstrated building height estimation using freely available Sentinel imagery, the resolution ceiling of resulting products is still coarse for material stock analysis. This study incorporates products derived from data freely accessible under scientific research licenses, TerraSAR-X StripMap and PlanetScope, alongside Sentinel-1 to predict building heights in a large city in Brazil. To account for the spatial autocorrelation in the training set, features from all sources are integrated in a geographically weighted random forest model, returning an RMSE of 5.34 m and R2 of 0.756 against a
LiDAR reference
dataset. Local feature importance showed predictor dominance to vary consistently across intra-urban contexts, with footprint geometry dominating for low-rise buildings, shadow-derived height for taller and more isolated structures, and spectral reflectance for the tallest buildings in the set. Sentinel-1 backscatter and InSAR occupy complementary spatial niches, with no single sensor uniformly preferable across the set. Results provide optioneering guidance and insight over satellite-derived products predictive relevance in distinct contexts, which global machine learning or neural network models cannot offer.
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Accelerator Physics
Machine learning assisted Bayesian calibration of an accelerator digital twin from orbit response data
Christopher Kelly, Kevin A. Brown, Georg H. Hoffstaetter et al. (+2 more)
Digital twins of particle accelerators are used to plan and control operations and to design data collection campaigns. Accurate modeling typically requires knowledge of quantities that are hard to measure directly, e.g., magnet
alignments, transfer functions relating power supply currents to
magnetic fields, magnet nonlinearities, and stray fields. In this work we introduce multiplicative parameters to the quadrupole transfer functions to parametrize these effects. We use
Bayesian methods to probabilistically estimate these parameters and their uncertainties by calibrating the Bmad digital twin to beam measurements performed at the AGS Booster at Brookhaven National Laboratory. The inference is computationally accelerated using a machine learning emulator of the physical accelerator digital twin trained to a perturbed-parameter ensemble of Bmad simulations. The result is a joint posterior distribution over the parameters constrained by the data, taking into account beam monitor errors. Incorporating estimates of the parameters into the digital twin is shown to result in a significant improvement in the quality of the model and provides error bars on the model parameters and predictions.
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All authors Christopher Kelly, Kevin A. Brown, Georg H. Hoffstaetter, Weijian Lin, Nathan M. Urban
Optics
Robust Orbital Angular Momentum Transfer Using Low-Cost Diffractive Optics
Beatriz Morales-Cruzado, Benjamin Perez-Garcia, Francisco G. Peérez Gutiérrez et al. (+1 more)
Reliable transfer of orbital angular momentum (OAM) to microscopic objects typically relies on high-fidelity
vortex beams generated by programmable spatial light modulators or precision-fabricated phase optics. Here, we demonstrate that robust OAM transfer in optical tweezers can be achieved using static binary holograms printed on acetate substrates. The printed diffractive optics generate Laguerre-Gaussian
vortex beams with sufficient spatial fidelity to induce controlled optical torque and stable rotational manipulation of polystyrene microspheres in a high-numerical-aperture optical tweezers system. Despite a diffraction efficiency of only approximately 2%, the generated beams enable reproducible particle rotation using less than 1 mW of optical power in the first diffraction order. The rotational dynamics were systematically characterized as a function of incident optical power and topological charge, revealing the expected increase in angular velocity with both parameters, consistent with OAM-driven torque in the overdamped regime. These results demonstrate that efficient optical angular momentum transfer is remarkably tolerant to the reduced efficiency of passive printed diffractive optics, establishing a robust, scalable, and high-damage-threshold platform for structured-light optical manipulation with applications in microfluidics, biophysics, optomechanics, and optical trapping.
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All authors Beatriz Morales-Cruzado, Benjamin Perez-Garcia, Francisco G. Peérez Gutiérrez, Carmelo Rosales-Guzmán
Atomic Physics
Optically Writable Atomic Vapor Memory as a Substrate for Optical Reservoir Computing
Elizabeth Robertson, Mingwei Yang, Lina Jaurigue et al. (+3 more)
We present an optical random access
memory (ORAM) based on warm cesium (Cs) atomic vapor and demonstrate its operation as the physical substrate of a reservoir computer. Information is stored in the hyperfine population distribution of a Cs ensemble via optical pumping and retrieved through differential probe absorption. Spatial multiplexing via acousto-optic deflection provides eight addressable
memory rails able to store up to 3.8 bits of information per rail. Employing this platform as a temporally multiplexed reservoir, we achieve a kernel rank ($\mathrm{KR}= 8.8 \pm 0.4$), and a minimum bit error rate of $0.02 \pm 0.01$ on the Exclusive-or (XOR)
benchmark. We find the limited
memory lifetime constrains the achievable temporal depth, encouraging further research into fast addressable
memories. This constitutes the first demonstration of a free-space, optically writable atomic RAM as a substrate in an optical reservoir computing system.
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All authors Elizabeth Robertson, Mingwei Yang, Lina Jaurigue, Guillermo Gallego, Kathy Lüdge, Janik Wolters
Atmospheric and Oceanic Physics
Anthropogenic Heat in Urban Climate Systems: Forcing, Sensitivity, and Feedback
Dan Li, Alvin Christopher Galang Varquez, Ting Sun et al. (+4 more)
Anthropogenic heat flux, the heat released to the environment from human activities such as building energy use, transportation, industrial processes, and human metabolism, is a defining feature of the urban
climate system. It is an important contributor to the urban heat island (UHI) effect and influences a wide range of urban meteorological processes. Its significance extends beyond urban climatology because of its close connections to energy consumption, greenhouse gas emissions, and
climate adaptation. Despite decades of research, anthropogenic heat flux remains one of the least well-constrained components of the urban energy balance. Moreover, its climatic significance has often been assessed from an applied perspective, with less emphasis on developing transferable physical understanding of how anthropogenic heat flux acts as a forcing, how urban temperatures respond, and how feedbacks modify that response. This review develops a forcing-response-feedback framework for synthesizing current understanding of the role of anthropogenic heat flux in the urban
climate system and identifies priorities for future research.
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All authors Dan Li, Alvin Christopher Galang Varquez, Ting Sun, Yuya Takane, Jiachuan Yang, Mingze Ding, David Sailor
Plasma Physics
Tunable high-charge relativistic electron beams via direct laser acceleration in hohlraum-preheated foam targets
Ziyao Wang, Jieru Ren, Zhigang Deng et al. (+28 more)
Direct
laser acceleration (DLA) in near-critical-density (NCD)
plasmas can efficiently generate high-charge relativistic electron beams, yet beam parameters depend critically on precise
plasma state manipulation. Solid-ablation NCD
plasmas evolve rapidly, posing severe controllability challenges. We produce NCD
plasma via indirectly heating foam targets with ns
laser driven hohlraum soft X-ray. Electrons are generated through irradiating the
plasma with another picosecond
laser. Tuning the
laser pulse delay $\tau$ enables control of
plasma profiles and beam parameters. Experiments show that when the foam is heated ($\tau$ = 6 ns, 9 ns), the beam exhibits $T \sim 13$ MeV effective temperature, $E_k \sim 80$ MeV cutoff energy, and hundreds of nC/sr charge for $E_k > 7.5$ MeV. These values are significantly higher than those from solid-foil ($T$ $\sim$ 2.7 MeV, $E_k$ $\sim$ 20 MeV, $Q$ $\sim$ 9 nC/sr) and cold-foam ($T$ $\sim$ 12 MeV, $E_k$ $\sim$ 50 MeV, $Q$ $\sim$ 5 nC/sr) interactions. At a longer delay of $\tau$ = 15 ns, the charge increases further while the temperature decreases, and at a shorter delay of $\tau$ = 3 ns, both temperature and charge are lower. 3D PIC simulations link these observations to the interplay between the microstructure of the cold foam and the evolving
plasma density profile at different delay times, which together determine the beam charge, effective temperature, and divergence. The finding provides a routine to generate and tailor the relativistic electron beams, which is essential for designing
laser-driven electron sources for high energy density physics and photonuclear reaction applications.
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All authors Ziyao Wang, Jieru Ren, Zhigang Deng, Wenqing Wei, Wei Qi, Olga N. Rosmej, Nikolay E. Andreev, Sergey Yu. Gus'kov, Rafael Yakhin, Yifang Gao, Bubo Ma, Mingzhe Yang, Shizheng Zhang, Xuyang Luo, Dieter H. H. Hoffmann, Peng Zhou, Ke Jiang, Taiwu Huang, Bo Cui, Weiwu Wang, Shaoyi Wang, Quanping Fan, Zhurong Cao, Sixin Wu, Yue Yang, Leifeng Cao, Yuqiu Gu, Yuchi Wu, Weimin Zhou, Zongqing Zhao, Yongtao Zhao
History and Philosophy of Physics
Astrobiology and the Transformation of Scientific Epistemology
Kristina Šekrst
Astrobiology occupies an unusual position within the philosophy of science. Confronted with the n = 1 problem - having only a single example of life to study - it attempts to investigate life beyond Earth while relying entirely on Earth's biosphere as its reference point, a constraint that creates unique epistemic challenges. Unlike traditional sciences with clear predictive frameworks, astrobiology operates as what we might call a transient science: a discipline functioning without foundational certainties, relying predominantly on abductive
reasoning, and confronting hypotheses that may remain untestable for decades. It is, in essence, a science of absence - of evidence, certainty, and analogy - where progress lies in refining conceptual and experimental tools to recognize unfamiliar forms of life. This positions astrobiology alongside emerging fields like artificial intelligence and cognitive science within a broader transformation of how scientific knowledge is constructed when dealing with phenomena that transcend direct empirical access.
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Data Analysis and Statistics · Cross-listed from hep-ph
VERaiPHY – Validation & Evaluation for Robust AI in PHYsics
Gaia Grosso, Ramon Winterhalder, Lydia Brenner et al. (+2 more)
Modern machine learning is leading to substantial gains in precision, flexibility, and computational efficiency in fundamental physics. Statistical validation, uncertainty quantification, and robustness assessment are less systematically addressed. The VERaiPHY initiative (Validation & Evaluation for Robust AI in PHYsics) is a series of articles developed within the PHYSTAT programme, aimed at establishing statistical standards for the development, evaluation, and deployment of ML techniques. Each article focuses on a specific methodological domain from a statistics perspective and clarifies statistical questions, tests, and the interpretation of results. This opening article establishes the probabilistic, statistical, and machine learning foundations that the later contributions assume, together with the notation used throughout.
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All authors Gaia Grosso, Ramon Winterhalder, Lydia Brenner, Louis Lyons, Tilman Plehn
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Atomistic Structure Generation and Neural-Network Screening of Hard Carbons to Identify High-Capacity Sodium Storage
Harry Mclean, Aiden Daniel Emery, Theodore Thomas Walton et al. (+2 more)
Hard carbons are established anodes for lithium-ion batteries and leading candidates for sodium-ion batteries, yet their electrochemical performance is governed by a heterogeneous network of graphitic domains, defects, and nanopores that conventional atomistic methods cannot model at the required length scales. We combine universal machine-learned interatomic potentials with the RAFFLE structure-generation framework to construct 13,096 realistic hard carbon models containing up to 4,378 atoms, matching experimentally measured densities, porosities, and sp$^2$/sp$^3$ bonding fractions. Explicit sodium intercalation of representative structures reproduces the characteristic sloping-to-plateau voltage profiles, revealing that capacity increases with decreasing carbon density and increasing porosity. To screen the full library, we train a lightweight neural-network surrogate that predicts capacity directly from the host using frozen universal-potential descriptors augmented by
geometric void features. The surrogate identifies high-capacity candidates exceeding 800 mAh g$^{-1}$, which are validated by full intercalation calculations. This scalable framework links hard carbon microstructure to sodium-storage performance and provides atomistic design principles for high-capacity anodes. More broadly, the workflow enables systematic exploration of synthesis-dependent amorphous microstructures, including precursor chemistry, pyrolysis, heteroatom doping, and pore engineering, providing a route toward atomistically informed hard carbon design.
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All authors Harry Mclean, Aiden Daniel Emery, Theodore Thomas Walton, Ned Thaddeus Taylor, Steven Paul Hepplestone
Optics
Neutron Interferometers from Stacked Holographic Photopolymer Gratings
Saba Shams-Lahijani, Tobias Jenke, Juergen Klepp et al. (+2 more)
Long-wavelength
neutron interferometry using discrete optical elements is notoriously challenging due to stringent
alignment and stability requirements. Here, we introduce a monolithic double-Laue
neutron interferometer fabricated from a stack of commercial Bayfol HX photopolymer films. By recording
holographic gratings simultaneously in multiple layers, we create a robust device that is inherently aligned, bypassing traditional stability problems. We demonstrate the device's function by observing the characteristic interference fringes in the diffracted intensity of both light and very cold
neutrons. The interferometer is then used to perform in-situ characterization of the
neutron beam's spectral profile, demonstrating its utility as a compact spectrometer. Our work establishes stacked
holographic gratings as a simple, versatile, and powerful platform for matter-wave interferometry and metrology.
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All authors Saba Shams-Lahijani, Tobias Jenke, Juergen Klepp, Christian Pruner, Martin Fally
Fluid Dynamics · Cross-listed from cond-mat.soft
Hydrodynamic Mode Coupling: Effects of density variations in nanoscale channel flows
L. Heitmeier and J. S. Hansen
We apply a modal framework for investigating the effect of density variations on
gravity-type driven flows at the nanoscale. Using eigenfunction decomposition of the density and acceleration fields, each shear-pressure mode is separated into a homogeneous contribution and an inhomogeneous contribution determined by the
Fourier amplitudes of the density and applied acceleration. This decomposition provides a direct means of identifying how density variations and external forcing couple and govern the flow behavior. We first revisit the Poiseuille flow and show that for channel heights larger than the characteristic intermolecular distance the homogeneous contribution dominates the long wave length (small wave vector) response, consistent with previous simulation results. In contrast, for sinusoidally driven flow, selective excitation of acceleration modes can produce the opposite behavior, with the inhomogeneous contribution dominating the long wave length response. The results show that the effect of the density variations depends on the specific flow; specifically the detailed mode coupling between the acceleration and density fields. The framework presented here provides a direct systematic approach for understanding and predicting the flow depending on the applied acceleration.
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Plasma Physics
Influence of the ectonic emission mechanism on the collisionless expansion of a multicomponent cathode plasma
Vasily Yu. Kozhevnikov
In this paper, the authors delve into the collisionless kinetic theory of planar
vacuum diodes to investigate how a pulse-periodic (ectonic) cathode
plasma emission mechanism influences the non-thermal expansion of the cathode
plasma and "anomalous" ion acceleration. Another aspect explored in this paper is how pulse-periodic emission affects the comparative dynamics of motion of multi-charged ions from the cathode material. Using kinetic theory, we conclude that the ectonic emission mechanism affects both the macroscopic picture of
plasma expansion and the intricacies of electric potential redistribution over one complete emission period.
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Biological Physics
An information-theoretic perspective on feed-forward loop abundances in transcriptional networks
Mintu Nandi, Sudip Chattopadhyay and Suman K Banik
In the transcriptional networks of Escherichia coli and Saccharomyces cerevisiae, the eight feed-forward loop (FFL) motifs occur at markedly different frequencies. Although previous studies have linked the abundant C1- and I1-FFLs to specific dynamical functions, a common account of the broader pattern is lacking. To address this gap, we adopt an information-theoretic approach. An FFL transmits information through two paths that share an input and converge on an output, suggesting that their interaction may contribute to differences among motifs. To investigate this, we decompose input-output mutual information (MI) into pathway MI and interference MI (IMI). Here, the pathway MI collects the contributions of individual pathways, whereas IMI identifies the contribution that arises from their interference. We find that within a representative parameter regime, IMI values of FFLs produce a hierarchy that closely resembles the abundance ordering in E. coli, whereas total and pathway MIs do not. Motivated by this observation, we perform constrained optimization that identifies parameter regimes compatible with abundance-like targets for both S. cerevisiae and E. coli. We relate the optimized IMI hierarchy to pathway interference strength and local pathway sensitivities to understand the underlying biophysical origin. Our framework thus probes the correspondence between pathway interference, information transmission, and motif-abundance hierarchies.
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Optics
Real-time estimation of the transmission matrix of an atmospheric channel
Cade Peters, Raphael Bellossi, Douglas McDonald et al. (+3 more)
Optical wavelengths have received significant
attention in free-space channels and are vital for applications in communications, imaging and sensing. Their widespread implementation is motivated by a variety of factors including improved bandwidths, increased security and higher energy efficiency. However, these advantages cannot be fully brought to bear in real-world scenarios due to the deleterious effects of atmospheric
turbulence. Induced by small temperature and pressure fluctuations in the environment that vary rapidly in space and time, these effects cause significant power losses which decrease SNR, induce severe crosstalk in communication links, and greatly limit resolution of long-range imaging systems. To overcome this, we numerically and experimentally investigate the reconstruction of the transmission
matrix of a time-evolving atmospheric channel with a real-time recursive optimization routine. We demonstrate that this estimation technique is able to keep up with the
evolution of the channel and enables a significant improvement of communication-relevant quantities such as the coupling of the received light into a single-mode fiber while notably reducing the probability and duration of power outages, even in strong
turbulence. Our results have immediate applications in free-space optical communication in both the classical and
quantum regimes.
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All authors Cade Peters, Raphael Bellossi, Douglas McDonald, Andrew Forbes, Szymon Gladysz, Giacomo Sorelli
Applied Physics · Cross-listed from cond-mat.mes-hall
Robust stabilization of high-frequency magnetic droplets in W-CoFeB-MgO nanoconstriction spin Hall nano-oscillators
Hind Prakash, Arunima TM, Roman Khymyn et al. (+1 more)
Magnetic droplets are highly nonlinear
spin-wave
solitons that can be excited in nanoscale spintronic devices with strong perpendicular
magnetic anisotropy. Although extensively studied in nanocontact-based
spin-torque oscillators, their stabilization in pure
spin current-driven devices such as
spin Hall nano-oscillators (SHNOs) has remained elusive. Here, we micromagnetically demonstrate the robust stabilization of non-propagating high-frequency droplets in CMOS-compatible W/CoFeB/MgO nanoconstriction SHNOs under oblique
magnetic fields. While the constriction geometry gives rise to noncircular droplet shapes in an inhomogeneous effective field landscape, stable droplet modes exhibiting complete core magnetization reversal and pronounced hysteresis are observed. At lower current densities, droplets display breathing oscillations with periodic expansion and contraction, whereas higher drive currents lead to drift, deformation, and the emergence of sidebands around the fundamental frequency. Tuning the strength and orientation of the applied
magnetic field alters the effective field landscape, allowing droplets to escape confinement and propagate over distances exceeding 2$\mu$m.
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All authors Hind Prakash, Arunima TM, Roman Khymyn, Himanshu Fulara
Space Physics · Cross-listed from astro-ph.EP
A Semi-Analytical Theory for Improved Orbit Design of the GARATÉA-L
Luiz Arthur Gagg Filho and Sandro da Silva Fernandes
This work proposes a semi-analytical theory for improving orbit design of the GARATÉA-L Brazilian lunar mission. The dynamical model incorporates the lunar gravitational potential up to degree 12 and order 3 harmonics and a third-body perturbation model accounting for the eccentricity and inclination of the Earth's orbit with respect to the Moon. Through Hori's method, short- and medium-period terms are eliminated from the
Hamiltonian to derive a first-order theory in mean orbital elements. It is demonstrated that nominal frozen orbits designed under simplified circular and equatorial assumptions for the motion of the third body are not maintained in this more realistic dynamical environment, leading to significant eccentricity growth and potential collisions of the probe with the lunar surface. The inclusion of the third body's inclination and eccentricity breaks the system's axial
symmetry, introducing the longitude of the ascending node into the double-averaged variational equations and rendering stationary frozen orbits practically unattainable. Consequently, the problem is addressed through a parametric study around the simplified model's frozen conditions to identify “low-drift" states where eccentricity variations are highly decreased. A new nominal orbit is proposed for GARATÉA-L. Numerical validation against high-fidelity propagation and JPL ephemeris confirms that this new configuration maintains the “low-drift" behaviour throughout the mission, ensuring orbital safety and avoiding the collision predicted by simpler models.
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Computational Physics · Cross-listed from math.NA
On Robust Alpha-Damping Viscous Scheme
Hiroaki Nishikawa
In this paper, we investigate the convergence of an implicit defect-correction solver for a viscous discretization based on the alpha-damping scheme for unstructured grids. We show that significantly more robust iterative convergence is achieved by evaluating the damping term at the midpoint between two adjacent
cell centers (edge midpoint) rather than at the face centroid. A one-dimensional
Fourier analysis reveals that the implicit solver tends to be stable when the damping term in the residual is smaller than that used to construct the Jacobian. This observation suggests that the solver can be stabilized by effectively reducing the magnitude of the damping term in the residual - an effect achieved by the edge-midpoint evaluation. Robust convergence is demonstrated numerically for two-dimensional viscous-flow problems on highly irregular mixed-element and triangular grids.
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Applied Physics · Cross-listed from quant-ph
Single-atom detection with a quantum-controlled mechanical oscillator
Maxime Perdriat, Maciej Dziewiecki, Josef-Anton Agner et al. (+4 more)
Using supersonic expansion, we create a time-gated, directional beam of Xe atoms with a narrow momentum distribution and detect their collisions with a levitated nanosphere cooled to its
quantum ground state. We observe individual momentum kicks below 50 keV/c with 96% confidence and distinguish directional momentum transfer from the atomic beam against the background of thermal collisions. Our experiments constitute a first step toward the exploration of distance-dependent short-range interactions between atoms and levitated systems, as well as toward the use of levitated platforms for impulsive force sensing in previously unexplored parameter regimes.
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All authors Maxime Perdriat, Maciej Dziewiecki, Josef-Anton Agner, Massimiliano Rossi, Frederic Merkt, Martin Frimmer, Lukas Novotny
Optics
Body-of-Revolution Finite-Element Model of Plasmon-Enhanced Fluorescence
Luke C. Ugwuoke, Farooq Kyeyune and Tjaart P. J. Krüger
Plasmon-enhanced fluorescence (PEF) is one of the most widely investigated optical phenomena in hybrid systems of emitters and plasmonic nanoantennas, with applications ranging from biosensing to single-molecule emission microscopy. In this work, we extend finite-element modelling of PEF beyond spherically symmetric geometries using a body-of-revolution finite-element method (BOR-FEM). By exploiting exact or equivalent rotational
symmetry, 3D emitter-nanoantenna systems are reduced to computationally efficient 2D formulations while retaining the essential electromagnetic interactions governing excitation and emission. We validate the framework against three previously investigated emitter-nanorod systems, including one requiring an equivalent axisymmetric
geometric transformation, before applying it to an emitter-core-shell nanorod system. Specifically, we investigate the PEF of the terminal chlorophyll emitter of the major plant light-harvesting complex (LHCII), the most abundant membrane
protein on Earth, interacting with a gold core-dielectric shell nanorod with one or two dielectric shells. The simulations reveal that the interplay between excitation enhancement, radiative-rate enhancement, and non-radiative Ohmic losses gives rise to four distinct shell-thickness-dependent operating regimes (quenching, enhancement, suppression, and decoupling), with recovery of the intrinsic
quantum yield in the decoupling regime. The predicted enhancement factors for experimentally relevant dual-shell nanorods agree well with previously reported measurements. These results establish BOR-FEM as an efficient and versatile framework for modelling PEF in rotationally-symmetric nanoantenna geometries and in non-axisymmetric geometries that admit equivalent axisymmetric representations, providing a practical route for the rational design and optimisation of plasmon-enhanced bio-nanophotonic systems.
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Applied Physics
Large area Waveguide Energy Harvesting Based on Fully Polarized Elastic Topological Metamaterials
Hanbang Deng, Bowei Wu, Tingfeng Ma et al. (+2 more)
To address the challenge that elastic wave energy can only transmit through narrow path waveguides in topological metamaterials, the proposal of large area waveguides effectively breaks through this technical bottleneck. Nevertheless, elastic waves are vector waves with complex multi component transmission characteristics. Realizing the cooperative transmission of in plane and out of plane fully polarized components poses substantial challenges for elastic wave energy transmission and trapping applications. To tackle the above mentioned problems, this paper proposes a fully polarized elastic topological
heterostructure based on the
quantum valley
Hall effect. First, symmetric unit
cell structures are designed to obtain unit
cells with distinct topological properties for in plane and out of plane modes, and multiple types of supercell structures are fabricated to realize the simultaneous transmission of fully polarized elastic wave energy for both in plane and out of plane components. Furthermore, a gradient valley locked structure is designed using large area waveguide states to constrain and converge the transmitted energy, and its energy harvesting performance is analyzed. The results demonstrate that the proposed structure enables coupled transmission of fully polarized elastic wave components. Moreover, the energy harvesting capability of the gradient valley locked phononic
crystal plate is approximately 4.79 times that of conventional single component transmission structures, which greatly improves the efficiency and transmission stability of acoustic energy harvesting. This work provides new insights for the engineering application of topological metamaterials in the field of energy harvesting.
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All authors Hanbang Deng, Bowei Wu, Tingfeng Ma, Teng Wang, Kun Hong
Atomic Physics · Cross-listed from quant-ph
Irradiation-Induced Spin Bath Evolution and as-Grown Hydrogen Defects in CVD Diamond Revealed by NV-Based DEER Spectroscopy
Olga Rubinas, Jeroen Prooth, Michael Petrov et al. (+4 more)
The aim of this paper is to provide the reader with a review and current state of the art of the fabrication of high T2 coherence diamond, optimised by the use of double electron-electron resonance (DEER) spectroscopy. Using DEER, we study the formation, transformation, and annealing of paramagnetic defects in as-grown CVD diamond and after post-processing. Electron irradiation leads to the formation of an additional S = 1/2 resonance in the DEER spectrum, which we consider to be a composite X ensemble. By tracking the concentrations of X and P1 point defects during annealing from 650C to 1200C, we find that the X ensemble initially consists of a mixture of V-
spins and interstitial
spins, which disappear at about 650C. Vacancies migrate during annealing, forming clusters that persist to 1000C and disappear upon annealing at 1200C, contributing to the X ensemble signal. We have developed a model of the influence of the mixed
spin bath on the coherence of NV centers, which includes independent couplings with P1 centers, V-, divacancies, and interstitials. Detailed DEER studies allowed us to reveal and resolve a weak signal from two additional S = 1/2 species associated with hydrogen: NVH- and consistent with a substitutional hydrogen defect, which overlaps the vacancy spectral line. Taken together, these results show that the NV-DEER method is a powerful tool for investigating paramagnetic defects in diamond with high precision and nanoscale resolution, essential for material optimisation. The achieved high T2 coherence time is consistent with the
spin bath model, and the
crystals reach the quality required for advanced
quantum sensing applications.
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All authors Olga Rubinas, Jeroen Prooth, Michael Petrov, Remy Vandebosch, Emilie Bourgeois, David Chvatil, Milos Nesladek
Computational Physics · Cross-listed from math.NA
Fast high-order solvers for the Lippmann–Schwinger equation in piecewise-smooth heterogeneous media
Thomas G. Anderson, Juan Burbano-Gallegos, Luiz M. Faria et al. (+1 more)
This article presents a fast, high-order Nyström solver for the two-dimensional Lippmann–Schwinger equation arising from time-harmonic scattering by penetrable, piecewise-smooth heterogeneous media. Relying on high-order evaluation of the Newtonian potential on unstructured grids adapted to interfaces of discontinuity, the methodology achieves high-order accuracy using existing fast
algorithms such as the fast multipole method. As an iterative method the solver exhibits rapid convergence when coupled to a preconditioning strategy that exploits a class of structured-grid solvers—fast solution methods offering quasi-linear time and
memory complexity and nearly-constant iteration counts, but long limited in accuracy. The preconditioning strategy couples the Nyström discretization—given by high-order quadrature nodes over a (curved) unstructured mesh conforming to the support of the spatially varying contrast—to a uniform Cartesian grid underlying the fast preconditioner via a pair of transfer operators. The resulting preconditioner inherits the frequency-robust behavior of its Cartesian counterpart without sacrificing the
geometric flexibility and high-order accuracy of the unstructured discretization. We prove that invertibility of the proposed preconditioner holds under explicit conditions on the mesh sizes and on the Cartesian preconditioner. Numerical experiments demonstrate that the preconditioned system requires significantly fewer GMRES iterations than its unpreconditioned counterpart, with iteration counts almost independent of mesh size and wavenumber, and illustrate the method's robustness for inhomogeneities with piecewise-smooth refractive indices and jump discontinuities across interfaces.
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All authors Thomas G. Anderson, Juan Burbano-Gallegos, Luiz M. Faria, Carlos Pérez-Arancibia
Optics · Cross-listed from cond-mat.quant-gas
KPZ scaling in one-dimensional arrays of photon condensates
Michiel Yzewyn and Michiel Wouters
Bose-Einstein condensates of
photons in dye filled microcavities are known to feature many properties of the ideal bose gas at thermal
equilibrium. Nevertheless, the finite
photon life time renders them driven dissipative systems where losses are balanced by continuous driving by a pump
laser. We show here with simulations based on a classical field model that their driven-dissipative nature causes their first order coherence to feature Kardar-Parisi-Zhang (KPZ) scaling, a phenomenon well known in the related condensates of
exciton-polaritons. Remarkably, we find that the KPZ scaling even occurs in a regime with large density fluctuations. We discuss the modification of the scaling by the occupation of excited states and how to recover the universal scaling behavior by spectral filtering.
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Computational Physics
Probabilistic Inverse Modeling of Contaminant Transport via a Conditioned-on-Design Bayesian Physics Informed Neural Network
Milad Panahi, Giovanni Michele Porta, Monica Riva et al. (+1 more)
We address the inverse problem of reactive transport in heterogeneous porous media, where unknown model parameters must be inferred from sparse experimental observations. The problem is complicated by strong nonlinearities, spatial heterogeneity, and limited data availability. We propose a Conditioned-on-Design
Bayesian Physics-Informed Neural Network (CoDe-BPINN), which combines a domain-decomposed PINN solver with a
Bayesian inference network that learns the conditional distribution of model parameters given experimental design variables. The framework is trained by maximizing a physics-informed Evidence Lower Bound (ELBO), enabling simultaneous reconstruction of spatiotemporal concentration fields, probabilistic parameter estimation, and uncertainty quantification. We demonstrate the approach using laboratory experiments on contaminant transport through a multilayer porous column with an iodinated contrast medium. The model accurately reproduces breakthrough dynamics while revealing systematic parameter dependence on flow conditions. In particular, it identifies a nonlinear decrease in effective sorption capacity with increasing flow rate and porosity, consistent with kinetic limitations and reduced adsorbent mass. The
Bayesian formulation also uncovers a strong negative correlation between sorption affinity and sorption capacity, quantifying the intrinsic non-identifiability of the inverse problem. CoDe-BPINN provides a robust framework for parameter inference and uncertainty quantification in data-scarce reactive transport problems.
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All authors Milad Panahi, Giovanni Michele Porta, Monica Riva, Alberto Guadagnini
Space Physics · Cross-listed from astro-ph.EP
The PANSY Meteor Head-echo Orbit Catalogue: Continuous Antarctic Radar Observations of Southern Meteoroid Streams
Juha Vierinen, Jorge L. Chau, Koji Nishimura et al. (+7 more)
Meteor head echoes from high-power, large-aperture radars provide pulse-resolved positions and velocities for individual micrometeoroids in a submillimeter-radius range that contribute significantly to the mass influx to Earth. We present the first meteor head-echo orbit catalogue from the Antarctic Syowa Mesosphere–Stratosphere–Troposphere/Incoherent Scatter radar (PANSY). The catalogue contains two million meteors and 50 million pulse-resolved measurements. The observed radiant distribution contains the helion, antihelion, south toroidal and apex sources, and provides unprecedented head-echo coverage of southern ecliptic latitudes. The initial detection-height distribution is found to be double-banded, with both bands increasing in height with meteor speed and exhibiting distinct radiant distributions, consistent with a mixture of meteoroid-size differences and differential ablation. Estimation of dynamic mass indicates that the survey is sensitive to initial radii of approximately 100 micrometers. As part of an initial exploration of the catalogue, we investigate the nighttime alpha Capricornids (CAP) and the extended Daytime Capricornids-Sagittariids (DCS) radiant. Their similar activity durations at opposite nodes are consistent with membership in the CAP–169P/NEAT complex. The radiant distribution suggests a new meteor shower candidate, with peak flux near
solar longitude 110 degrees, mean Sun-centered ecliptic radiant longitude 291.0 degrees, latitude -48.2 degrees, and geocentric speed 48.7 km s^{-1}. During catalogue production, event-level raw voltage cuts are retained temporarily to support improvements in data analysis. This first catalogue release, covering 2025 January 26 to 2026 July 26, will be useful for further studies of the southern-hemisphere Earth-crossing meteoroid population.
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All authors Juha Vierinen, Jorge L. Chau, Koji Nishimura, Taishi Hashimoto, Nico Pfeffer, Daniel Kastinen, Devin R. Huyghebaert, Johan Kero, Masaki Tsutsumi, Kaoru Sato