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Physics Physics

physics Watch Physics

Friday 4 September

Chemical Physics

Measurements of Diffusion Coefficients of CO$_{2}$ in 1-Butanol with a New Laminar Jet Apparatus and PFG-NMR, Pointing to Interfacial Mass Transfer Effects

Oliver Großmann, Sarah Mross, Jens Wagner et al. (+3 more)

A novel laminar jet apparatus (LJA) was constructed for precise gas-liquid mass transfer measurements up to 12 bar, significantly extending the technique's operating window. It was applied to carbon dioxide + 1-butanol between 283 K and 333 K. Corresponding measurements were performed using pulsed field gradient NMR spectroscopy (PFG-NMR), which does not involve interfacial mass transfer. Fick diffusion coefficients from LJA and self-diffusion coefficients from PFG-NMR were compared in the limit of infinite dilution, where both must coincide. Both methods show consistent trends, but LJA data are systematically lower. Experimental errors cannot explain the deviations. We therefore hypothesize an additional gas-liquid interfacial mass transfer resistance. PCP-SAFT combined with density gradient theory predicts high CO$_{2}$ enrichment at the interface, and the deviations correlate with this enrichment. Whether such an interfacial resistance exists and is caused by enrichment remains to be established in future studies.
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All authors Oliver Großmann, Sarah Mross, Jens Wagner, Kerstin Munnemann, Fabian Jirasek, Hans Hasse

Computational Physics · Cross-listed from quant-ph

Impact of Data Loss in Postprocessing on Training and Inference of Quantum Neural Networks

Soraya V. Panambalom, Edoardo Altamura, Nick Chancellor et al. (+1 more)

As quantum hardware scales to larger devices, the classical software layers that interface with it must evolve in step. Postprocessing routines developed and tested primarily in simulator settings can encode assumptions that no longer hold on utility-scale devices, leading to data loss that can be difficult to detect from high-level model outputs alone. We present a case study of SamplerQNN, the sampling-based quantum neural network class in the Qiskit Machine Learning library. Here, the postprocessing method applies a filter that assumes measurement bit-strings are in virtual qubit space. On our quantum hardware runs, where bit-strings span over 100 physical qubits, this filter led to the loss of 85 to 99.6% of valid measurement shots, depending on the transpiler's qubit placement. The resulting probability vector is unnormalised, allowing distorted prediction and loss values to propagate through the model without an API-level warning. We demonstrate the impact across five experiments on two IBM backends: for inference, accuracy drops from 0.94 to 0.39 on the same raw measurements; for training, the loss signal is compressed by 22 to 27$\times$, substantially reducing the sensitivity of the optimiser to the objective landscape. The behaviour arises in all released versions of the library (0.8.4 to 0.9.0). We implemented a layout-based marginalisation fix, merged into the GitHub codebase as Pull Request \#1041, that makes SamplerQNN postprocessing forward-compatible with current and upcoming hardware.
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All authors Soraya V. Panambalom, Edoardo Altamura, Nick Chancellor, Jonte R. Hance

Optics

Bounds on Propagation Constants in Dielectric Gratings

Ehsan Faghihifar

We establish analytical bounds on the normalized longitudinal propagation constants $\beta=k_z/k_0$ of modes in lossless dielectric diffraction gratings. If $\epsilon_{\max}$ denotes the maximum relative permittivity, we show that regular modes ($\beta^2\in\mathbb{R}$) satisfy $\beta^2\le\epsilon_{\max}$ despite the lack of a scalar dispersion relation. We further show that the so-called ghost modes ($\beta^2\notin\mathbb{R}$), admitted by the non-Hermitian nature of the associated eigenproblem, satisfy $|\mathrm{Re}(\beta)|\le\sqrt{\epsilon_{\max}}/2$. Both bounds are obtained directly from the Fourier-series formulation of the fully coupled vectorial eigenproblem.
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Fluid Dynamics

Fisher Information Dynamics: A Kinematic Framework for Phase Space Ordering with Applications to Shock Layers and Turbulence

Yingchuan Wu

Order here denotes the sharpness of probability-density gradients as quantified by Fisher information, distinct from thermodynamic order parameters. A kinematic framework for phase space ordering is established based on the Fisher information production rate, which possesses a rigorous thermodynamic foundation through the de Bruijn identity, Stam inequality, and dissipation theorem. A four-term decomposition into isotropic contraction, traceless shear, divergence gradient, and boundary flux is derived from the continuity equation. Extending to the Fokker-Planck equation, the non-positivity of the diffusive dissipation term is proved, with strict negativity for non-uniform densities. A vorticity-independence theorem shows that purely rotational velocity fields do not alter the order measure, and explicit geometric sign criteria enable prediction of where order is generated or destroyed. Through exact solutions of the Burgers shock layer, a pointwise identity between compression and divergence-gradient contributions is uncovered, underlying the three-term balance. In two-dimensional incompressible turbulence, a statistical two-term equilibrium (vanishing time-averaged production) is established as the null hypothesis: the conservative reference state from which three-dimensional turbulence departs through vortex stretching. Variational steady states of the associated Wasserstein gradient flow imply vanishing of the total production rate. This framework provides a diagnostic and predictive tool for analyzing ordering dynamics in non-equilibrium systems.
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Fluid Dynamics

Unveiling wing turbulence dynamics through explainable deep learning

Samuel Molina-Casino, Andrés Cremades, Sergio Hoyas et al. (+3 more)

The three-dimensional organization of coherent structures in the turbulent flow over aircraft wings remains elusive, limiting our ability to reduce fuel consumption. Here, we use explainable artificial intelligence to characterize these structures by predicted flow evolution rather than classical predefined kinematic criteria. After training a deep neural network to predict the short-term evolution of the flow, we identify the highest-relevance flow regions using Shapley-value attribution methods. We have found that as the flow decelerates towards the trailing edge, predictive importance shifts from near-wall low-speed structures to three-dimensional pairs of high- and low-speed fluid regions. Matching no single classical structure family, these pairs progressively dominate the dynamically relevant flow. Most stand spanwise side-by-side, enclosing a near-vertical momentum interface with the strongest velocity jump. Their geometry remains invariant in viscous units while their volume expands when approaching separation. Our results reveal a predictive organization that traditional paradigms overlook, opening new ways to control turbulent flows.
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All authors Samuel Molina-Casino, Andrés Cremades, Sergio Hoyas, José I. Cardesa, François Chedevergne, Ricardo Vinuesa

Optics

Fabrication-Aware Design of a Hybrid Metasurface-Bragg Mirror for Low-Noise Precision Optics

Mika Gaedtke, Christian Kranhold, Markus Walther et al. (+3 more)

High-reflectivity coatings for precision interferometry must simultaneously minimize optical losses and thermally driven displacement noise. Dielectric Bragg mirrors provide robust high reflectance but rely on thick multilayer coatings, whereas metasurface mirrors provide high reflectance and low noise but are sensitive to fabrication-induced deviations. A fabrication-aware photonic design framework is introduced that combines a resonant single-layer metasurface, an etch-stop layer, an antiresonant spacer, and a reduced Bragg reflector. Fabrication effects, including geometric tolerances and line-edge roughness, are explicitly considered in the optical design. Full-wave electromagnetic simulations are combined with a truncated-Gaussian Monte Carlo analysis to determine the performance distribution under the assumed fabrication conditions. The ideal metasurface design achieves a modeled non-reflected power of $1-R<10^{-5}$. After roughness-aware reoptimization, the modeled non-reflected power remains below $1.04\cdot10^{-4}$ at $80\%$ fabrication yield. For the cryogenic ETpathfinder gravitational-wave testbed, two Bragg layer pairs reduce the non-reflected power of the complete stack to approximately $6.6\,\mathrm{ppm}$. The estimated thermal displacement-noise amplitude spectral density is $1.97\cdot10^{-20}\,\mathrm{m/\sqrt{Hz}}$ at $100\,\mathrm{Hz}$. The architecture connects fabrication robustness, optical performance, and thermal-noise reduction within a single design framework.
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All authors Mika Gaedtke, Christian Kranhold, Markus Walther, Falk Eilenberger, Stefanie Kroker, Thomas Siefke

Optics

Fisher-information retention under local driving in non-Hermitian feed-forward chains

Qingrui Bai, Zhichao Li and Junlong Kou

When local drive hardware is installed before a sensing task is revealed, directional non-Hermitian buildup creates a tradeoff between targeted preparation and spatial coverage. We quantify this tradeoff for stable linear scatterers with proper complex Gaussian output statistics. For parameters encoded in the internal generator, and at fixed coherent internal resource, the drive hardware enters the optimized mean-response Fisher information only through the projector onto the internally reachable subspace, while the preparation Gramian sets the source cost. In an on-resonance feed-forward chain, nested Green-function columns decompose into disjoint port intervals, and the site-local retention factors in each interval sum exactly to unity. Directionality concentrates this unit downstream, so the worst-site retention decays exponentially when one port serves many sites; for $m$ equal intervals, a single probe shared by all tasks has a worst-site retention lower by a further factor $m$ than task-specific reoptimization. Joint source-power and internal-resource constraints connect this fixed-resource law to source-limited preparation. A noisy RLC/VCCS model illustrates the retention law with stored electromagnetic energy, covariance Fisher information, and component disorder. The resulting bounds turn directional buildup into a port-layout criterion: source savings for a selected task are accompanied by a spatial coverage cost for tasks unknown at the hardware-design stage.
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Optics

Sub-2-Cycle, Terawatt Pulses via Double-Stage Multi-Pass Cell Compression of an Yb Laser

Victor Koltalo, Jaismeen Kaur, Louis Daniault et al. (+8 more)

We report a terawatt-class, sub-2-cycle post-compressed Yb-based laser system operating at kHz repetition rate. 18 mJ, 400 fs pulses delivered at 1 kHz by a commercial Yb:YAG laser are spectrally broadened and temporally compressed in a double-stage multi-pass cell setup featuring an argon-filled Herriott-type cell followed by a helium-filled array-type cell, achieving an overall compression factor of 65. The resulting compressed pulses are measured to have 6.2 fs duration (1.8 optical cycles at 1030 nm) and 12.5 mJ energy, corresponding to 1.4 TW effective peak power. To the best of our knowledge, this constitutes the highest peak power reported to date for a few-cycle, kHz-repetition-rate, post-compressed Yb laser system. Focused intensity measurements yield a normalized vector potential of a0 = 3.0, confirming the applicability of this light source for laser wakefield acceleration.
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All authors Victor Koltalo, Jaismeen Kaur, Louis Daniault, Antoine Cavagna, Mickael Allemand, Florent Pallas, Antoine Courjaud, Emilien Gontier, Cédric Sire, François Sylla, Rodrigo Lopez-Martens

Physics and Society · Cross-listed from stat.ME

A Strictly Proper Scoring-Rule Theory for Calibrating Stochastic Car-Following Models

Shirui Zhou, Shiteng Zheng, Junzhe Ding et al. (+2 more)

Problem definition: Fixed parameters and inputs in a stochastic simulator induce a distribution over complete trajectories, not one trajectory. Calibration must assess this distribution, including variability and temporal dependence, against observations. Yet stochastic car-following models are commonly calibrated with trajectory-error objectives inherited from deterministic modelling. Methodology/results: We establish a scoring-rule theory of stochastic calibration. Strict propriety requires the data-generating distribution to uniquely minimise expected score. MRMean-I, the average run-wise error, drives separable stochastic spread to zero; MRMean-II, the error of the ensemble-mean trajectory, cannot identify a parameter that changes only spread; and MRMin, the error of the closest simulated run, has a population target that changes with ensemble size. These results are confirmed for stochastic Intelligent Driver Model extensions with additive acceleration noise and random desired headway. We recommend exact maximum likelihood when the correct transition density is available; otherwise, an unbiased simulation-based estimator of a strictly proper score. The energy score meets this requirement and gives the best held-out distributional prediction among the evaluated simulation-based objectives, although both models retain too-narrow bands and miss persistent disturbances. Implications:Strict propriety separates a valid calibration target from parameter identifiability and model adequacy. The theory applies to vector-valued outputs from stochastic transportation simulators; the car-following experiments illustrate its scope.
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All authors Shirui Zhou, Shiteng Zheng, Junzhe Ding, Rui Jiang, Junfang Tian

Plasma Physics

Impact of ion-beam stopping power on proton-boron fusion yield in the pitcher-catcher scheme driven by ultra-intense laser

J. Y. Hua, X. F. Li, J. X. Wang et al. (+3 more)

The effect of stopping power on proton-boron fusion is investigated for a proton beam propagating through boron plasma. Due to the stopping power, the electron temperature of the boron target rises as the proton beam deposits energy. Consequently, a feedback mechanism becomes significant when the trailing part of the beam propagates into the preheated plasma. By coupling this phenomenon with the proton-boron fusion process, fusion yields are systematically investigated by varying the central energy of the proton beam, as well as the thickness and density of the boron target. It is found that, under the influence of stopping power, the optimal central energy for fusion deviates from the intrinsic 672 keV resonance and shifts to approximately 900 keV. Moreover, the present results are substantiated by particle-in-cell simulations, which provides a valuable reference for subsequent high-yield hydrogen-boron fusion.
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All authors J. Y. Hua, X. F. Li, J. X. Wang, Y. X. Leng, Y. Tian, R. X. Li

History and Philosophy of Physics

From the Light Quantum to the Photon: The Evolution of a Physical Concept

Aaron Collavini, Valentina Bologna, Francesco Longo et al. (+2 more)

This work examines the physical and conceptual evolution of the light quantum from Planck's blackbody theory to the theoretical and experimental developments that led to the quantization of the electromagnetic field. The present study shows that the decisive transition occurred in Einstein's quantum theory of radiation (1916-1917). Absorption, stimulated emission, and spontaneous emission were formulated as elementary probabilistic mechanisms whose statistical balance alone reproduces the blackbody spectrum. In particular, spontaneous emission requires the emission of a light quantum, thereby implicitly proving its physical necessity before its theoretical status was clarified. At the same time, the already existing term photon began to acquire a stable usage following Lewis's 1926 proposal and became increasingly associated with Einstein's light quantum. By the mid-1920s, the central problem had shifted from whether light quanta were physically required to how radiation could be incorporated into the emerging quantum-mechanical formalism. This transition marks a key stage, illustrating how initial debates about the existence of light quanta gave way to their integration into a comprehensive theoretical structure. The resulting asymmetry between the novel quantum description of matter and the still-classical description of radiation, called into question by the phenomenon of spontaneous emission, identifies the physical problem that led to the quantization of the electromagnetic field.
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All authors Aaron Collavini, Valentina Bologna, Francesco Longo, Stefano Ansoldi, Fulvio Parmigiani

Chemical Physics

Operando imaging of intercalation memory in MXenes

Franz Groebmeyer, Mohsen Beladi, Christoph G. Gruber et al. (+6 more)

Ion intercalation enables reversible control of charge, structure and function in layered solids. Yet layered materials contain nanosheets with different thicknesses and stacking, whose intercalation pathways are averaged out in ensemble measurements. This becomes critical under Angstrom-scale confinement, where ion transport couples to solvent reorganization and host deformation, leaving the origins of kinetics, reversibility and activation unresolved. Here we combine operando interferometric scattering and interference reflection microscopy to resolve proton-driven dynamics in individual single- and multilayer Ti3C2Tx MXene flakes and show that even a few stacked layers introduce a significant kinetic barrier. Cycling then separates nanosheets into three persistent behaviors: reversible monolayers, restacked multilayers with incomplete recovery and delayed deintercalation, and coherently stacked multilayers that self-stabilize through reversible folding. Operando synchrotron X-ray diffraction shows this memory at electrode scale, where the interlayer structure converges towards a reproducible state. Our findings reveal cycling-induced structural memory that governs subsequent intercalation in layered MXenes.
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All authors Franz Groebmeyer, Mohsen Beladi, Christoph G. Gruber, Ruocun Wang, Pol Salles, Nhu Quynh Nguyen, Jakub Drnec, Yury Gogotsi, Emiliano Cortes

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

Nuclear quantum effects in the thermal conductivity of solid hydrogen

Hengtai Zheng, Zezhu Zeng and David E. Manolopoulos

We use a combination of path integral and lattice dynamics methods to calculate the thermal conductivity of solid parahydrogen. Path integral molecular dynamics is first used to calculate a centroid potential of mean force at each temperature, on which a harmonic phonon basis is constructed using the finite displacement method. We then calculate anharmonic force constants on the centroid potential and solve the linearised phonon Boltzmann transport equation for the thermal conductivity. The resulting renormalised phonon dispersion curves, heat capacity, and thermal conductivity are all in remarkably good agreement with experimental measurements. We find that the heat transport is dominated by collective relaxon modes at low temperatures and cannot be captured by making the phonon relaxation time approximation. Indeed, quantitative agreement with the experimental thermal conductivity is only achieved when the nuclear quantum effects in the centroid potential of mean force, phonon boundary scattering, and hydrodynamic transport are all explicitly considered. This is also likely to be the case for other quantum crystals.
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Optics · Cross-listed from cond-mat.mes-hall

Nonreciprocal plasmonic response of drift-biased two-dimensional metals

Gonzalo Álvarez-Pérez and Joel D. Cox

We develop a nonlocal electrodynamic framework for drift-biased two-dimensional electron gases (2DEGs) with Dirac (linear) and parabolic (quadratic) dispersions, deriving closed-form drift-dependent conductivity tensors from the Boltzmann transport equation. We obtain the plasmon dispersion and near-field emission of a point dipole, revealing nonreciprocal propagation in both systems. At equal drift parameter, the parabolic 2DEG exhibits stronger nonreciprocity than the Dirac system, although we find that a larger drift parameter does not by itself produce stronger nonreciprocity: the response is set by the interplay of drift and plasmon nonlocality. As such, the combination of strong nonlocality and experimentally accessible drift velocities of semiconductor 2DEGs identifies parabolic systems as a promising platform for tunable, nonreciprocal plasmonics.
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Applied Physics

Noise-Resilient Detection of Neuronal Spikes by a Hopf-Bifurcation Device

Jitendra Kumar, Roberto Fenollosa, Gonzalo Rivera-Sierra et al. (+4 more)

Detecting weak transient signals in noise is a persistent challenge in sensing, communication, and electrophysiology. Here, we demonstrate a physical weak-signal detector based on a semiconductor negative differential resistance (NDR) device operated near a Hopf bifurcation. A coherent input that persists over the response time of the dynamical system can drive a transition between quiescent and oscillatory states, whereas faster stochastic fluctuations are largely suppressed. This nonlinear transformation converts a weak analog threshold crossing into all-or-none voltage spikes and therefore provides asynchronous signal detection without a reference clock. Using a modulated photovoltaic signal, we detect a weak frequency component of 100 Hz as a demonstration, at an input signal-to-noise amplitude ratio as low as 1/500, and reliably recover it in the output spectrum. We then apply the same principle to neuronal multisite extracellular recordings. After standard band-pass filtering, the raw microelectrode signal is transformed by the NDR dynamics, enhancing the distinction between neuronal spikes and background fluctuations. The resulting detected spike times agree closely with those obtained using a traditional spike-detection pipeline. These results establish bifurcation-engineered NDR dynamics as a compact hardware approach to noise-resilient signal discrimination and event-based analog-to-digital conversion that will be useful for neuroprosthetic devices.
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All authors Jitendra Kumar, Roberto Fenollosa, Gonzalo Rivera-Sierra, So-Yeon Kim, Adam Armada-Moreira, Juan Bisquert, Michele Giugliano

Plasma Physics

Revisiting kinetic electrostatic electron non-linear (KEEN) waves in the presence of dynamical ions

Rostislav-Paul Wilhelm, Philipp Krah, Kai Schneider et al. (+2 more)

We revisit the kinetic electrostatic electron nonlinear (KEEN) waves studied by Afeyan et. al in 2014 using a hybrid flow-mapping strategy that combines the characteristic mapping method (CMM) with numerical flow iteration (NuFi). The study extends the classical setup to dynamical ions, comparing their impact on the long-time KEEN dynamics with the static-ion case. To this end, we extend the CMM-NuFI framework with a multi-map strategy, assigning one map to the ion and one to the electron characteristic flow. The resulting problem exhibits a wide separation of spatial and temporal scales, driven by the fine structures generated by the ponderomotive force and by the large ion-to-electron mass ratio, which renders it computationally prohibitive for conventional grid-based methods. Our multi-map CMM-NuFI method efficiently resolves these disparate scales, enabling long-time simulations of KEEN dynamics with fully dynamical ions.
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All authors Rostislav-Paul Wilhelm, Philipp Krah, Kai Schneider, Fabio Bacchini, Virginie Grandgirard

Geophysics

Bayesian inversion of multilayer $\mathrm{CO}_2$ migration from seismic plume observations using a graph-based finite-rate invasion-percolation model

Elling Svee, Jo Eidsvik, Kasper Hunnestad et al. (+1 more)

Vertical migration of $\mathrm{CO}_2$ in layered sandstone reservoirs is controlled by thin shale barriers whose properties are often poorly known. We develop a Bayesian framework that uses time-lapse seismic plume observations to estimate effective parameters governing lateral and vertical $\mathrm{CO}_2$ migration. The forward model is a fast graph-based invasion-percolation model that extends conventional IP by representing both capillary-controlled filling of structural traps beneath shale barriers and finite-rate transfer through them. Parameters are inferred with approximate Bayesian computation and sequential Monte Carlo sampling, and the posterior samples are propagated into forecasts. Applied to real data from Sleipner, posterior simulations reproduce the broad distribution of $\mathrm{CO}_2$ across nine sand units and its redistribution between 2010 and 2023. In contrast, the quasi-static model fails to reproduce this temporal evolution. Complementary synthetic experiments assess parameter recovery, forecasting, monitoring duration, and model misspecification. These experiments show that the information gained from monitoring depends on the migration events captured, with breakthrough and post-breach redistribution providing particularly strong constraints. This combination of fast simulation, probabilistic updating, and interpretable effective parameters makes the framework well suited to repeated forecast revision during active injection, especially when full-physics inference is too computationally demanding.
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All authors Elling Svee, Jo Eidsvik, Kasper Hunnestad, Philip Ringrose

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

Liquid-liquid phase separation precedes crystallization in supercooled water-glycerol solutions

Iason Andronis, Sharon Berkowicz, Mariia Filianina et al. (+10 more)

Understanding the structural evolution of supercooled water-glycerol solutions is important for cryopreservation, yet distinguishing liquid-state transformations from ice crystallization remains challenging. Here, we investigate a deeply supercooled water-glycerol solution by X-ray photon correlation spectroscopy (XPCS) in ultra-small-angle X-ray scattering (USAXS) geometry, combined with wide-angle X-ray scattering (WAXS). This combination simultaneously captures the structural and dynamical evolution of the supercooled liquid upon quenching to cryogenic temperatures (172 K). We observe discontinuous changes in the liquid structure on molecular length scales and formation of microscale domains. The dynamics slow down during this stage and exhibit hyper-diffusive, ballistic-like relaxation. This transformation precedes ice crystallization, which we identify from the emergence of ice Bragg peaks in WAXS, allowing the two processes to be temporally separated. Phase-field (Cahn-Hilliard) simulations qualitatively reproduce the experimental observations and show that a spinodal-decomposition scenario is consistent with the measured scattering evolution. These findings are consistent with a liquid-liquid phase separation scenario preceding ice crystallization and provide a route to disentangle the two processes in supercooled aqueous systems.
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All authors Iason Andronis, Sharon Berkowicz, Mariia Filianina, Maddalena Bin, Robin Tyburski, Robert Bauer, Yuriy Chushkin, Federico Zontone, Michael Sprung, Wojciech Roseker, Fabian Westermeier, Felix Lehmkühler, Fivos Perakis

Fluid Dynamics · Cross-listed from nucl-th

Thermal boundaries for relativistic fluids without a conserved charge

Lorenzo Gavassino, Soeren Schlichting and Gabriel S. Denicol

We study an ultrarelativistic fluid with no conserved particle number in a planar slab geometry bounded by two parallel, thermally conducting plates held at fixed (possibly different) temperatures. The fluid-wall interaction is described within kinetic theory by modeling the fluid as self-interacting radiation: a gas of bosons emitted and absorbed by the walls according to black-body laws, while mutual collisions enforce local equilibration. From this microscopic setup we derive effective boundary conditions for the hydrodynamic fields, finding that the walls behave as modified absorbing boundaries (and not as thermostats). In particular, the fluid temperature at the boundary does not generally coincide with the wall temperature. We prove that the resulting initial-boundary-value problem is well posed. When the plates are held at different temperatures, the system develops a uniform steady flow from the hotter to the colder wall, with energy density equal to the arithmetic mean of the corresponding black-body energy densities in the limit of a small temperature difference.
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Optics

Relaxing Coherence Requirements on Laser Sources for Nanoscopy through Optical Fiber Technique

Kaifa Xin, Mengdie Hou, Ao Yang et al. (+8 more)

High numerical-aperture (NA) focusing of cylindrical vector beams (CVBs) typically requires costly, high-quality lasers to supply a stable vector pupil field. Here, we introduce fiber-conditioned vectorial nanofocusing, in which an optical-fiber-based mode-selective coupler projects a strongly distorted beam of a diode that costs two orders of magnitude less than the reference laser into radially or azimuthally polarized CVBs. A three-tolerance analysis clarifies its operating principle by establishing separate requirements for spatial state, temporal coherence and residual wavefront error. The resulting fields reproduce expected high-NA focal signatures and generate orientation-sensitive single-molecule excitation patterns consistent with reference-laser measurements, lowering the barrier to structured-light experiments.
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All authors Kaifa Xin, Mengdie Hou, Ao Yang, Márton Gelléri, Hyun-Keun Lee, Antonio Virgilio Failla, Jiafeng Lu, Xianglong Zeng, Mischa Bonn, Jesper Lægsgaard, Xiaomin Liu

Chemical Physics

Derivation of the Sample-Size Scaling of TWO-NN Intrinsic-Dimension Estimates from Molecular Dynamics Trajectories

Riccardo Capelli

The intrinsic dimension of a dataset is the number of independent directions needed to describe the space occupied by its data. Estimators based on nearest neighbors infer this number from how the probability to find a neighbor point grows around each sampled point. Because the distances $r$ between neighbor points decrease as the sample grows, the estimated dimension can depend strongly on the number of available points. Here, we derive the large-sample behavior of the TWO-NN estimator for data drawn from a smooth $d$-dimensional space. The typical nearest-neighbor distance scales as $N^{-1/d}$, and smooth deviations from a locally uniform distribution produce successive corrections proportional to $N^{-2/d}$. We test this result using the trajectories coming from ten independent $100~\mu$s simulations of alanine dipeptide. Configurations are represented by all pairwise distances among the ten heavy atoms. This representation has a known geometric dimension of $3n_{\mathrm{at}}-6=24$. Over the investigated range, the TWO-NN estimate shows no systematic dependence on the temporal spacing between configurations, but increases from approximately $7.5$ to $15.6$ as the sample size grows from $10^2$ to $2\times10^5$. Extrapolations that retain corrections through $r^2$, $r^4$, and $r^6$ give limiting dimensions of $25.23$, $22.89$, and $27.00$, respectively. All three estimates lie close to the known dimension and collectively bracket it, supporting the proposed scaling. Their spread provides a direct estimate of the systematic uncertainty associated with the truncation. The derived scaling therefore explains the strong sample-size dependence of TWO-NN and provides a practical route from finite sample estimates to the underlying geometric dimension.
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Applied Physics · Cross-listed from quant-ph

Microkelvin resolution thermometry at the nanometre scale

Jack W. Hart, Soham Pal, Julien R. E. Roth et al. (+8 more)

Accurate temperature readings of transient events at the nanometer scale are challenging due to the low sensitivity of available sensors. Nanodiamonds containing nitrogen-vacancy (NV) centers have been used for nanoscale thermometry in complex environments, including inside living cells. However, their performance has been limited by short coherence times and low photon counts. In this work, we use isotopically-purified dual-NV nanodiamonds and a bespoke quantum sensing chip to showcase an order of magnitude improvement in temperature measurement sensitivity compared with previous reports. We demonstrate robust temperature measurements with an error of 682 $\mu$K, experimental sensitivities below 50 mK/$\surd \text{Hz}$ and a shot-noise limited sensitivity of 9.6 mK/$\surd \text{Hz}$. To confirm the utility of these high-performance nanothermometers, we quantify the temperature change induced by the thermometry measurement itself, specifically the optical excitation laser used to probe the NV spin state. In addition, we observe directly at the nanometre scale the transient heating caused by the exothermic mixing of dimethyl sulfoxide in water. Sub-millikelvin resolution and millikelvin sensitivity thermometry unlock the possibility of monitoring minute thermal fluctuations in living systems and assessing catalyst performance at the nanometre scale.
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All authors Jack W. Hart, Soham Pal, Julien R. E. Roth, Katie Ninham, Abbie H. Aleksandrova, Xander Peetroons, Soumen Mandal, Oliver A. Williams, Gavin W. Morley, Mete Atature, Helena S. Knowles

Medical Physics

Attention-guided super-resolution of 4D flow MRI in carotid arteries

Ali Mokhtari and Dominik Obrist

Four-dimensional (4D) flow magnetic resonance imaging (MRI) is a powerful non-invasive technique for visualizing and quantifying complex blood flow patterns in vivo. Despite its clinical promise, broader adoption is limited by low spatial resolution and sensitivity to noise, which restrict accurate assessment of critical hemodynamic biomarkers such as wall shear stress, pressure gradients, and turbulent kinetic energy. To overcome these challenges, we propose a deep learning-based super-resolution framework that integrates multi-scale feature extraction and attention mechanisms to enhance the quality of 4D flow MRI data. The model was trained on a dataset of 120 patients with 240 stenosed carotid arteries. High-resolution ground truth data were generated using patient-specific computational fluid dynamics (CFD) simulations based on segmented vascular geometries and physiologically realistic boundary conditions, and the resulting velocity fields served as targets for supervised learning. The proposed architecture uses convolutional block attention modules (CBAM) to guide the network toward clinically relevant spatial features and to suppress noise in low-resolution inputs. Quantitative results show that the attention-guided model substantially reduces the root mean square error (RMSE) compared with a baseline model without attention, and qualitative velocity contour analysis confirms improved reconstruction of intricate flow patterns. These findings highlight the capacity of the model to restore high-fidelity flow fields under noisy conditions and support the use of deep learning to extend the clinical utility of 4D flow MRI for non-invasive hemodynamic assessment.
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Fluid Dynamics

Homoclinic-shedding in the steady forced water-wave problem

Jack Keeler and Mark Blyth

Recently, an infinite set of steady solitary-wave solution branches was discovered for inviscid and irrotational flow over a localised topographic depression. These solutions were restricted to critical flow, when the Froude number is unity. Several questions were raised, including i) what happens to the solution structure as the flow speed is continued into the supercritical regime? and ii) how does the decay rate of the topography affect the solution structure? In this article, we answer these questions by examining exact steady solutions of the fKdV model and numerical solutions of the fully nonlinear Euler system over i) trench, ii) Gaussian and iii) generalised Agnesi topographies. We uncover a highly non-trivial bifurcation structure consisting of spirals and closed loops, characterised by the phenomenon of `homoclinic shedding', where pairs of solitary waves are emitted up- and downstream as the amplitude is varied.
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Optics

Frugal Effective Models for Nanophotonic Scattering: Optimizing Global Polarizability Matrices for Metasurface Design

Sofia Ponomareva and Peter R. Wiecha

Accurate nano-photonics simulations of large scale devices like optical metasurfaces require high accuracy reduced models for the device constituents. We present an automated framework for the optimization of Global Polarizability Matrix (GPM) models, which represent a complex scatterer as a small set of non-local effective dipoles. Our goal is to find the most frugal model that reproduces a particle's scattering response within a user-defined accuracy. The method iteratively removes redundant dipoles while re-adapting the positions of the remaining ones via gradient based optimization, stopping at the smallest model that still meets the target. Automatic differentiation, combined with an untrained neural network that reparametrizes the dipole positions, helps to place the dipoles at physically intuitive locations. We demonstrate the versatility of this approach across diverse geometries, from two dimensional ridges over simple spheres to complex three-dimensional particles, achieving compression factors of typically two orders of magnitude compared to full-wave simulations, for target accuracies in the order of few percent. We finally demonstrate how accurate, frugal effective models enable large-scale meta-deflector optimization without periodic approximations. This robust recipe for constructing frugal effective models paves the way for the rapid simulation of large-scale photonic assemblies, required for example for metasurface design.
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Biological Physics · Cross-listed from cond-mat.soft

The elasticity of semiflexible polymers with reversible spontaneous curvature in two dimensions

Donghyeon Kim and Panayotis Benetatos

Many semiflexible filaments exhibit structural asymmetries that lead to a curved ground state (curvature in the absence of thermal fluctuations, external forces, or torques). This property is known as spontaneous curvature. Many semiflexible polymers can reversibly develop spontaneous curvature through internal conformational transitions or through transient interactions with their molecular environment. In this article, we show that such reversible spontaneous curvature, even in the absence of transitions in the value of the bending stiffness, provides a minimal mechanism for ensemble-dependent elasticity. We formulate an analytically tractable two-state modified wormlike-chain model in two dimensions, in which an uncurved state (without spontaneous curvature) competes with a curved state (possessing spontaneous curvature). The transition is controlled by an activation energy. Within the weak-bending approximation, we obtain the Gibbs and Helmholtz partition functions for a stretched filament with reversible constant (uniform along the backbone) or sinusoidal spontaneous curvature and for a grafted bistable filament driven either by an end torque or a bending force. Stretching or bending induces a crossover from spontaneous-curvature-dominated to entropic elasticity. We show how the elastic response differs in the two ensembles (Gibbs vs Helmholtz). In addition, we consider the case where the curved state is also characterized by a higher value of the bending stiffness. In that case, a reentrant transition is possible as we stretch the bistable filament.
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Atomic Physics

Dead-zone-free free-induction-decay alkali-metal atomic magnetometer

X.-K. Wang, J. He, H.-H. Deng et al. (+2 more)

The detection dead zone is an important systematic limitation in scalar atomic magnetometers, constraining their practical utility. In this work, we demonstrate a sensitive dead zone free scalar magnetometer by integrating previously established techniques into a FID magnetometer based on Bell Bloom optical pumping. The dead zone is eliminated by inserting a reflecting mirror within a multipass cavity assisted atomic cell, which folds the optical beam into orthogonal paths. Our analysis reveals that interregion cross talk is essential for interpreting the resulted experimental signals. The sensor exhibits oscillation signal amplitude variations within a factor of three across all orientations in three dimensional space, and a field sensitivity better than 80 fT/Hz^(1/2) over the full space. We further characterize the heading error in the geomagnetic field range, where experimental results agree with theoretical predictions within 0.7 nT. Additionally, the sensor can operate in a closed loop mode by feeding back the real time frequency extracted from the FID signal to modulate the pump beam, we characterize the magnetic field slew rate of the sensor. This work paves the way towards a sensitive vector FID magnetometer.
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All authors X.-K. Wang, J. He, H.-H. Deng, W. Gao, D. Sheng

Optics

Modulation-Frequency Dependence of Spatial Resolution in Optical Correlation-Domain Reflectometry

Keisuke Motoda, Takaki Kiyozumi and Yosuke Mizuno

The spatial resolution of optical correlation-domain reflectometry (OCDR) has conventionally been described by an expression that is independent of the modulation frequency $f_m$, source linewidth $\delta\nu$, and receiver resolution bandwidth (RBW). However, our previous measurements showed that the spatial resolution $\Delta z$ improves with increasing $f_m$. Here, we develop a theoretical model for OCDR with a frequency shifter by evaluating the electrical power detected by an electrical spectrum analyzer and explicitly including $\delta\nu$ and the RBW $B$. The model predicts two regimes. At low $f_m$, $\Delta z$ decreases approximately in proportion to $1/f_m$, with the proportionality determined by the combined source and receiver spectral response. At high $f_m$, $\Delta z$ approaches a constant value determined by the modulation amplitude $\Delta f$ and independent of the source linewidth and RBW filter. Measurements at RBW = 1 MHz reproduced the transition between these regimes over correlation orders up to 2048. At RBW = 10 MHz, a Voigt representation of the spectral response overestimated $\Delta z$, whereas direct use of the measured unmodulated beat spectrum reduced the discrepancy to approximately 10 to 20%. These results provide a quantitative description of the modulation-frequency dependence of OCDR spatial resolution and clarify its trade-off with measurement range.
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Medical Physics

BEAM3R: Beam's-eye-view architecture with Mamba-3 for implicit dose reconstruction

Chen Cheng, Michael Ferraro, James Grover et al. (+2 more)

To enable accurate and rapid photon control point and proton beamlet dose calculation in the DoseRAD2026 challenge, we present BEAM3R, a dose estimation framework operating in beam's-eye-view (BEV). Our core innovation combines a Mamba-3 state-space depth-sequence core with physics-based transport conditioning to model long-range depth transport without expensive 3D convolutions. BEAM3R shares a 2D CNN encoder-decoder architecture for photon and proton dose tasks, processing per-plane BEV slices. Proton beamlets are conditioned on water equivalent thickness and remaining range, encoding the parameters determining Bragg peak position. Photon models use a bidirectional Mamba-3 core to capture dose contributions from materials downstream of the calculation point, while the proton model uses a forward core with learned energy-prefix tokens and a Bragg-peak refinement module. To reduce interpolation artifacts and support high spatial resolution, we introduce axial grid alignment of BEV lattices with CT slices and an implicit super-resolution representation via sub-pixel phase packing, evaluated by a differentiable Triton-accelerated resampler that reconstructs packed cubic B-spline coefficients directly in CT space. For MRI-based tasks, synthetic CTs (sCT) are generated by a patch-based conditional GAN with a SwinUNETR backbone. On the preliminary DoseRAD2026 test set, CT-to-photon and CT-to-proton models achieved 1%/1 mm local gamma pass rates of 96.8% and 96.0%, with stratified plan-level MAEs of 0.0041 and 0.0079. Substituting sCT reduced gamma pass rates to 89.7% for photon and 75.4% proton plan level doses, with stratified plan-level MAEs of 0.0093 and 0.0336. Standardised runtimes were 23.4 s and 18.4 s for CT-to-photon and CT-to-proton prediction, increasing to 39.7 s and 42.8 s for the corresponding MRI-based pipelines.
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All authors Chen Cheng, Michael Ferraro, James Grover, David E J Waddington, Emily Hewson

Atomic Physics

Analytical model for polarization transfer during gas-phase collision events in spin-exchange optical pumping: Spin-$\frac{1}{2}$ $^{129}$Xe versus spin-$\frac{3}{2}$ $^{131}$Xe

Perttu Hilla, Rajgowrav Cheenikundil and Juha Vaara

Spin-exchange optical pumping (SEOP) is a method for producing spin-hyperpolarized noble gas nuclei, such as 129Xe and 131Xe, which are used in various magnetic resonance applications from fundamental physics to quantum sensing and medical imaging. In SEOP, optically polarized alkali-metal atoms transfer their spin polarization to the noble gas nuclei in gas-phase collision events via the hyperfine coupling (HFC) between the alkali valence electron and the noble gas nucleus. While the polarization transfer physics of spin $I = 1/2$ nuclei, such as 129Xe, is relatively well understood, that of spin $I > 1/2$ nuclei, such as 131Xe ($I = 3/2$), has been far less studied, and no rigorous theoretical model has been presented to date. To this end, we derive a simple analytical model for the upper limit, neglecting relaxation, of the SEOP polarization transfer, applicable to noble gases with arbitrary nuclear spin. Analytical evaluation of the Baker-Campbell-Hausdorff expansion for the time evolution of the spin density operator $\hat{\rho}(t)$ reveals that only even-order terms in the HFC contribute to the polarization transfer, with the leading-order quadratic term being the most significant. We obtain a result similar to that derived for the spin-exchange cross section by Herman [Phys. Rev. 137, A 1062 (1965)], but in a more general framework for the time evolution of $\hat{\rho}(t)$ that is also more familiar to magnetic resonance researchers. The model is applied to understand the difference in the polarization transfer efficiency between 129Xe and 131Xe, yielding results in agreement with previous experiments. We also validate the model by comparison to detailed numerical multiscale simulations of the SEOP process, where full quantum-chemically computed spin Hamiltonians sampled from molecular dynamics simulations of the gas-phase collision events are used to propagate the spin dynamics.
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