Optics
Towards digital phantoms: emulating scattering with a spatial light modulator
Kelsey Everts, Cade Peters and Andrew Forbes
The distortion of light's degrees of freedom when passing through complex random media is of great interest across a diversity of fields, e.g., scattering in biological studies. Emulating such media in a controlled laboratory setting conventionally relies on real-world physical samples (e.g., white paint), inhomogeneous mixtures with embedded scatterers, or biological tissue-mimicking phantoms. Such methods, while effective in certain contexts, are not without complexity and limitations: the exact medium properties are challenging to control and often require laborious preparation, external characterisation techniques, are not easily reproducible between studies and cannot be matched precisely by numerical simulations. Here, we propose a simple all-digital implementation of random scattering which can be readily implemented on any setup capable of producing digital holograms. Our approach employs binary random phase masks encoded onto a spatial light modulator which perturbs the input beam's phase and amplitude. We highlight two methods to precisely tune distortion strengths which show excellent agreement between simulated and measured results. We demonstrate distortion strengths comparable to real-world scattering samples and illustrate two example applications to emulate scattering of scalar and vectorial structured light. Finally we showcase the versatility of this toolkit for emulating various amplitude and phase profiles and suggest several easy to implement alternative modalities accessible with this method. This digital phantom circumvents many of the practical challenges of physical samples, making it ideally suited for applications at the intersection of structured light, biological imaging and optical communications.
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Fluid Dynamics
Air entrainment by an inclined smooth water jet
Théophile Gaichies, Arnaud Antkowiak, Anniina Salonen et al. (+1 more)
Air entrainment can occur when a water jet impacts a water/air interface, a process central in various real systems, ranging from dam spills to breaking waves. Despite its prevalence, a comprehensive description of the mechanism controlling bubble size distribution remains elusive. Here, we establish a link between the geometry and the dynamics of the cavity observed when an inclined impinging jet impacts a water interface and the resulting bubble cloud. We show that the bubbles result from the destabilization of the wavefield developing at the interface of the cavity. The origin of this wave field is the creation of a shear layer, due to the asymmetric detachment of the flow field from the interface.
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All authors Théophile Gaichies, Arnaud Antkowiak, Anniina Salonen, Emmanuelle Rio
Optics
Active control of phase matching in nonlinear metasurfaces using Pancharatnam–Berry phase
Madona Mekhael, Roman Calpe, Tommi K. Hakala et al. (+2 more)
Reconfiguring the spectral output of nonlinear metasurfaces after fabrication remains challenging. We address this by exploiting the nonlinear Pancharatnam–Berry phase of $C_{3v}$-symmetric plasmonic metasurfaces. By integrating two metasurfaces inside a multipass
cell, we experimentally demonstrate continuous spectral tuning of second-harmonic generation (SHG) phase-matching peaks across a 900–970 nm pump range by rotating one metasurface relative to the other. The extracted
geometric phase follows the $3\sigma\theta$ dependence, and a full $2\pi$ tuning cycle is completed with $120^{\circ}$ of physical rotation. This establishes
geometric-phase metasurfaces as a reconfigurable nonlinear platform, where mechanical rotation enables post-fabrication and broadband tuning of nonlinear optical responses.
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All authors Madona Mekhael, Roman Calpe, Tommi K. Hakala, Robert Fickler, Mikko J. Huttunen
Fluid Dynamics
A Volume of Fluid Immersed Boundary Method for Industrial Polymer Mixing
Emilia Capuano, Daniele Cerroni, Holger Marschall et al. (+3 more)
This work develops advanced numerical methods for free-surface simulations of
polymer mixing processes, integrating a Volume of Fluid (VOF) interface-capturing approach with a non-conforming Immersed Boundary (IB) method to model two-phase flows of highly viscous
polymer melts and air within partially filled rotating mixing devices, implemented within the Finite Volume OpenFOAM library. To overcome severe numerical instabilities arising from the strong viscosity contrast between
polymer melts and air, a block-coupled scheme providing fully implicit viscous
diffusion treatment is integrated into the VOF-IB framework, relaxing time-step stability constraints and substantially reducing computational cost with respect to standard segregated solvers. The resulting BC-VOF-IB solver is applied to industrially relevant geometries of single- and twin-screw extruders, yielding physically consistent predictions of velocity and pressure fields under partial filling conditions. While further developments, most notably the inclusion of thermal effects, remain necessary, the proposed framework represents a meaningful step toward bridging academic CFD research and the practical demands of industrial
polymer processing.
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All authors Emilia Capuano, Daniele Cerroni, Holger Marschall, Giorgio Negrini, Nicola Parolini, Marco Verani
Plasma Physics
Towards Virtual Qualification in Nuclear Fusion: Demonstrating Probabilistic Model Validation on a High Heat Flux Component
J. T. Horne-Jones, M. Baxter, A. Tayeb et al. (+4 more)
Qualification of components operating in future fusion power plants will be heavily reliant on simulations of component behaviour. The lack of representative test environments for many aspects of the expected operating environment will necessitate full or partial virtual qualification of components. The cornerstone of virtual qualification is credible validation of the simulation models on which it relies. In this work, we present a probabilistic model validation framework that forms the basis for implementation of virtual qualification in fusion. We demonstrate our framework on a representative component; a high heat flux heat sink subject to a tightly coupled multi-physics loading. We perform data-rich, optimised experiments, in which we implement high fidelity diagnostics and rigorously quantify aleatoric and epistemic uncertainty on all measurements. Our simulation approach efficiently samples input uncertainty distributions to predict probability boxes describing component response, using a statistical surrogate to replicate behaviour of the finite element model we wish to validate. We then used a novel implementation of the modified area validation metric to quantify the model form error of the finite element model, isolating it from the aleatoric and epistemic experimental uncertainty. We discuss the contribution of our validation approach towards virtual qualification, and the benefits of the risk-based decision-making it facilitates. The experimental, simulation, and validation
datasets are published as a
benchmark of a probabilistic validation approach for fusion, and for use in development of new model validation methodologies.
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All authors J. T. Horne-Jones, M. Baxter, A. Tayeb, L. Fletcher, J. Paterson, S. Biggs-Fox, A. Harte
Fluid Dynamics
Information-Preserving SGS model based on the local inter-scale equilibrium hypothesis
Takeru Hashimoto, Takahiro Tsukahara and Ryo Araki
Large eddy simulation has been widely used to simulate
turbulence at balanced computational cost and accuracy. Many Subgrid-Scale (SGS) models have been proposed over the years, where data-driven and machine learning-aided approaches set the recent trend. To address the problem of extrapolation in these models, we propose a new data-driven SGS model based on an information-theoretic picture of
turbulence. To this end, we estimate the model parameters by maximizing mutual information, which correspond to the scale-by-scale local
equilibrium hypothesis in developed
turbulence or "information preservation." An a priori test confirmed that the estimated parameters are in good agreement with the previously reported empirical values. Furthermore, a posteriori tests on periodic box
turbulence and channel
turbulence exhibited accuracy comparable to the existing models. These results suggest the utility of the information-theoretic picture of
turbulence for constructing more generic SGS models without the need for empirically prescribed model parameters, while enhancing physical interpretability beyond black-box approaches.
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Chemical Physics
Geometrical Imperfections in a Digital Quadrupole Mass Filter: A Comprehensive Simulation Study in the First Stability Zone
Brotin Taraphdar, Sukanya Jana, Pintu Mandal et al. (+1 more)
Geometrical imperfections in quadrupole mass filters introduce higher-order field components that can significantly influence device performance, particularly under non-sinusoidal excitation. In this work, a comprehensive simulation study is carried out to investigate the effect of geometrical imperfections on the performance of a rectangular wave driven quadrupole mass filter operating in the first stability zone. Radial field distortions arising from controlled variations in rod geometry and position, including single rod radius variation, single rod displacement, diagonal rod radius variation, and diagonal rod displacement, are examined. These imperfections introduce octupole field components that distort the ideal quadrupolar field distribution. The influence of such distortions on key performance parameters, namely mass resolution and ion transmission efficiency, is systematically evaluated. The results show that the presence of radial asymmetry leads to a degradation of both resolution and transmission efficiency in all cases considered. Furthermore, the study reveals a strong dependence of mass filter performance on the initial state of the applied pulsed waveform, specifically whether the asymmetric rod pair is subjected to the high or low level of the RF pulse. These findings provide important insights into the tolerance limits of geometrical imperfections and their impact on the performance of pulsed wave driven quadrupole mass filters, which are relevant for the design and optimization of high-resolution digital mass filtering systems.
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All authors Brotin Taraphdar, Sukanya Jana, Pintu Mandal, Nabanita Deb
Optics
Bin Latent Transformer (BiLT): A shift-invariant autoencoder for calibration-free spectral unmixing of turbid media
Martin Hohmann
The accurate recovery of constituent-level optical properties from integrating sphere measurements is a central analytical challenge in pharmaceutical analysis, food science, and biomedical diagnostics. Neural network autoencoders can extract spectrally resolved absorption and scattering coefficients for each constituent without prior knowledge, but their fully connected encoders bind learned features to absolute wavelength indices, causing accuracy loss under spectrometer calibration drift or hardware exchange. This work introduces the Bin Latent
Transformer (BiLT)-Autoencoder, in which the dense encoder is replaced by a cross-
attention scanner: 16 learnable probe vectors query a convolutional feature map, aggregating morphological spectral information independently of absolute wavelength position. A physics-constrained linear decoder with enforced absorption/scattering separation and a three-phase curriculum augmentation strategy complete the architecture. On a
liquid phantom
benchmark (intralipid and two ink absorbers; 496 samples), the model achieves $R^2 = 0.979$ and $0.975$ for $\mu_a(\lambda)$ and $\mu_s'(\lambda)$, respectively, on held-out test spectra, maintaining $R^2 > 0.90$ for $\mu_a$ and $R^2 \approx 0.99$ for $\mu_s'$ across the full tested shift range of $\pm 10$ spectral bands. The model generalises to a simulated spectrometer with a broader instrument line shape (${\approx}24$nm FWHM) without retraining, retaining $R^2 \approx 0.96$ and $0.974$ for the two channels.
Attention map analysis reveals a physically interpretable two-component probe strategy: sparse anchor probes at absorption-edge wavelengths combined with a diffuse, SNR-driven ensemble at the high-transmittance long-wavelength region, which recruits additional probes dynamically under noise to provide implicit spectral averaging.
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Optics
Systematic Investigation and Suppression of Fluorescence in High-Sensitivity Cavity-Enhanced Raman Gas Sensing
Severin Hager-Roiser, Robert Zimmerleiter, Paul Gattinger et al. (+3 more)
Raman spectroscopy enables broadband, multi-species gas analysis by providing access to an entire vibrational spectrum in a single measurement. However, the sensitivity of gas-phase Raman sensing is often limited by weak signals and fluorescence background from various optical elements that constrain the achievable signal-to-noise ratio (SNR) through signal-dependent noise contributions (e.g. shot noise). Here, we present a cavity-enhanced Raman spectroscopy (CERS) gas sensor employing a 500 mW, 532 nm continuous wave (CW)
laser and a simple, non-resonant two-mirror multi-pass cavity (MPC) operated at ambient pressure and near the concentric condition, providing up to 45 internal reflections. To quantitatively capture the impact of fluorescence on performance, a CCD-specific noise model was developed that links fluorescenceinduced baseline levels to measurement noise. Complementary optical simulations were employed to assess the signal collection efficiency in the MPC. Through a systematic analysis of fluorescence sources, the background was reduced substantially by step-wise elimination of fluorescent optics. The fluorescence-minimized setup resolves weak Raman signatures in ambient-air spectra, including CO2 peaks, O2 and N2 overtones, and ambient CH4 (2 ppm). Calibration measurements for O2 (diluted in N2), N2 (in O2) and H2 (in N2) demonstrate detection limits of 11 ppm, 5 ppm and 3 ppm, respectively, with a 180 s measurement time. The results highlight fluorescence mitigation as a key design lever for robust, field-oriented CERS instrumentation for trace gas sensing.
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All authors Severin Hager-Roiser, Robert Zimmerleiter, Paul Gattinger, Ivan Zorin, Johannes D. Pedarnig, Markus Brandstetter
Fluid Dynamics
Kinematic Closure of Drop Impact
Mete Abbot and Daniel Bonn
Predicting how far a
liquid droplet spreads upon impacting a solid surface is governed by a complex competition between inertia, surface tension, and viscous dissipation. Existing models typically estimate this maximum spreading diameter by prescribing the spreading time or velocity from a decoupled asymptotic limit, restricting predictive accuracy across regimes. Here, we formulate a reduced kinematic description by resolving both the characteristic spreading time and spreading velocity from an energy balance coupling capillary storage and viscous dissipation. Unifying these two asymptotically constrained closures via the kinematic relation $D_{\max} = V_s t_s$ yields a compact, parameter-free approximation for the maximum spreading ratio that bridges the inertio-capillary and inertio-viscous regimes. We quantify the accuracy of this reduced closure against the exact implicit energy relation and demonstrate that it quantitatively collapses our experimental measurements alongside extensive literature data across wide ranges of Weber and Ohnesorge numbers, droplet sizes, and surface wettabilities without adjustable prefactors.
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Computational Physics · Cross-listed from cond-mat.str-el
CERTIFY-ED: A Multi-Layer Verification Framework for Exact Diagonalization of Quantum Many-Body Systems
Sarang Vehale and Ritu Goel
Exact diagonalization (ED) is a workhorse technique in computational
quantum many-body physics, but published ED results are rarely accompanied by machine-checkable evidence of their numerical correctness. The community typically relies on the implicit trust chain LAPACK $\to$ user code $\to$ result, with at most informal agreement against another package treated as confirmation. We argue that this practice is inadequate for a method whose output frequently underpins theoretical claims, and we present certify-ed, a verification framework designed to be used alongside existing ED packages (QuSpin, XDiag, ALPS) rather than as a replacement for them. The framework consists of (i) a multi-oracle eigensolver that runs three independent LAPACK paths and reports their pairwise disagreement, (ii) thirteen logically independent validation layers covering algebraic invariants, analytic limits, alternative
algorithms, arbitrary-precision reference computation, conservation laws, dynamical consistency, and finite-size scaling, and (iii) tamper-evident SHA-256 hashed certificates that downstream consumers can verify. The framework also ships an error-injection layer that confirms the entire pipeline detects six injected error classes. Running on sixteen physics models from one-dimensional
spin chains to two-dimensional Kitaev honeycomb clusters, our reference implementation passes 53 of 53 unit tests and 81 of 81 individual validation tests in under thirty seconds, with maximum disagreement against QuSpin of $1.6\times 10^{-14}$ across 320
eigenvalue comparisons, and agreement with 50-digit mpmath reference values to $1.6\times 10^{-15}$. The package is released under the MIT license on Zenodo and Github
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Optics
Theory of Supercritical Coupling And Generalized Bound States in the Continuum
Sergio Balestrieri, Bruno Miranda, Silvia Romano et al. (+1 more)
Bound states in the continuum (BICs) arise from destructive interference suppressing radiation despite spectral overlap with the continuum. Here we show that Friedrich–Wintgen interference naturally emerges from a bright–dark supermode decomposition of resonances coupled through a shared radiation channel. In this basis, any finite leakage of a quasi-BIC induces a causality-driven reactive coupling enabling non-Hermitian pumping of the dark sector. We derive the optimal condition for this process and show that it corresponds to the supercritical coupling regime previously identified in [Nature 626, 765 (2024)], while naturally recovering universal quasi-BIC asymmetry scaling. Extending the theory to Dirac-like dispersions in photonic
crystal slabs, we identify an open-Dirac singularity where the Dirac gap matches the supercritical regime. A four-wave
Hamiltonian quantitatively reproduces rigorous coupled-wave analysis, revealing the breakdown of conventional critical coupling. Near this regime, absorptive cross-coupling induces coherent absorption interference and enables suppression of effective dissipative losses beyond conventional material limits. These results motivate the concept of a generalized bound state in the continuum (gBIC) as a limiting non-Hermitian state where radiative and effective gain compensate, producing a true divergence of the total quality factor. Overall, this work establishes a unified framework connecting BIC interference, Dirac
topology, and non-Hermitian physics for ultra-high-Q enhancement and loss engineering in open photonic systems.
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All authors Sergio Balestrieri, Bruno Miranda, Silvia Romano, Gianluigi Zito
Chemical Physics · Cross-listed from cond-mat.soft
Nanostructure of PEGDA-PEG hydrogel membranes and how it controls their permeability
Sixtine de Chateauneuf-Randon, Malak Alaa Eddine, Bruno Bresson et al. (+7 more)
The spacial heterogeneity of hydrogels composed of PEGDA and added
polymer chains is expected to play a crucial role on their transport properties which can be exploited in filtration or tissue engineering. However little is known about the arrangement of the
polymer chains in the
matrix and the length scales of these heterogeneities. Here we combine solid-state NMR and Small Angle
Neutron Scattering to unravel the structure and dynamics of PEGDA hydrogels containing added PEG chains of various concentrations. Our results show that the samples present heterogeneities in both the PEGDA and PEG concentrations and suggest that the PEG chains entangle with the PEGDA network. When plotting the sample permeability, K, as a function the specific surface of the PEGDA heterogeneities we obtain a master curve, showing that the heterogeneity of the PEGDA
matrix controls the permeability of the sample. Moreover the scaling K ___ V/S suggests a structure composed of facetted PEGDA/PEG heterogeneities separated by a network of aqueous thin and flattened films in which the water can permeate.
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All authors Sixtine de Chateauneuf-Randon, Malak Alaa Eddine, Bruno Bresson, Thomas Salez, Sylvain Prévost, S. Belbekhouche, Théo Merland, Cédric Lorthioir, Clémence Le Coeur, C. Monteux
Physics and Society
Topology-dependent criticality in triplet majority-rule dynamics with collective reversal on quenched networks
Roni Muslim
We study a triplet majority-rule opinion-dynamics model with collective reversal on quenched networks. Interactions occur on local triplets composed of one
agent and two of its neighbors, while collective reversal acts only on unanimous triplets. This rule separates local conformity from external perturbations that disrupt local agreement. We show that quenched network
topology shifts the order–disorder critical point away from the well-mixed value. For Barabási–Albert, Erdős–Rényi, random regular, and Watts–Strogatz networks, the estimated critical exponents remain close to the mean-field values, suggesting mean-field-like universal behavior within the system sizes studied. The strongest shift of the critical point occurs for Watts–Strogatz networks, where clustering and local correlations make the ordered phase less stable. A rewiring analysis of Watts–Strogatz networks further shows that the ordered phase becomes more stable as the network becomes more random. These results indicate that quenched
topology primarily controls the location of the transition, while the collective-reversal mechanism largely preserves mean-field-like critical behavior.
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Optics
Probe- and Substrate-Dependent Visibility of Mie Resonances in Silicon Nanospheres
Yonas Lebsir, Huatian Hu, P. A. D. Gonçalves et al. (+5 more)
Silicon nanospheres are high-quality optical resonators and promising building blocks for Mie-tronic devices. While the Mie resonances of an isolated sphere are well understood, practical implementations require substrates that inevitably modify the measured optical response. Here, we investigate how substrates alter the observable spectrum of individual nanospheres, focusing on three fundamentally different cases: a thin silicon nitride membrane, that emulates a free-standing particle, bulk silicon, which is common in experiments, and gold, where mirror charges lead to hybrid optical modes. Cathodoluminescence and dark-field spectroscopy, combined with electrodynamic simulations, show that the measured resonances are not intrinsic to the particle but depend strongly on the environment and the excitation mechanism. We find that substrate-induced effects and probe-specific selection rules can suppress, enhance, or even invert the spectral signatures of electric and
magnetic modes. These results provide practical guidelines for interpreting and designing substrate-supported dielectric resonators for Mie-tronic applications.
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All authors Yonas Lebsir, Huatian Hu, P. A. D. Gonçalves, Hiroshi Sugimoto, Minoru Fujii, N. Asger Mortensen, Christos Tserkezis, Sergii Morozov
Biological Physics · Cross-listed from cond-mat.soft
Tracer-free Contactless Acoustic Microrheometry Quantifies Viscoelastic Spectrum of Phase-separated Condensates
Kichitaro Nakajima, Taichi Yoshikawa, Yuta Suzuki et al. (+13 more)
The rheology of phase-separated condensates plays a central role in applications spanning advanced materials design and cellular processes, yet quantitative characterization of their viscoelasticity remains challenging due to the limitations of existing microrheological methods that require tracer particles or mechanical contact. Here, we establish tracer-free and contactless acoustic microrheometry as a versatile platform for quantifying the frequency-dependent complex shear modulus of single microscale condensates over 0.01-10 Hz. Using spatiotemporally controlled acoustic radiation force generated within a micro-acoustic resonator, this method deforms condensates for creep-recovery and oscillatory viscoelastic measurements. Quantitative validation using dextran condensates in a polyethylene-glycol continuous phase successfully captures their size- and frequency-dependent mechanical responses, while application to nucleic-acid condensates reveals salt-dependent internal viscoelastic changes at single-condensate resolution. By enabling quantitative dissection of condensate mechanics without invasive probes, acoustic microrheometry provides a broadly applicable framework for investigating phase-separated condensates across materials science, soft matter physics, biology, and beyond.
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All authors Kichitaro Nakajima, Taichi Yoshikawa, Yuta Suzuki, Shuta Nakatani, Kanta Adachi, Nobutomo Nakamura, Sanae Murayama, Hiroki Sakuta, Naoya Yangisawa, Nadia A. Erkamp, Tomas Sneideris, Mao Fukuyama, Masateru Taniguchi, Miho Yanagisawa, Hirotsugu Ogi, Tuomas P.J. Knowles
Atmospheric and Oceanic Physics
Enabling High-Accuracy Data Assimilation with Limited Ensembles via Machine Learning-Based Covariance Correction
Zhou Yao, Zhilin Li, Li Zhao et al. (+4 more)
Data assimilation (DA) integrates numerical model forecasts with observations to achieve the optimal state estimation. Ensemble-based methods, such as the ensemble Kalman filter (EnKF), are widely used for state estimation for high-dimensional and nonlinear dynamic systems. However, their performance strongly depends on the ensemble size, therefore causing a tradeoff problem between analysis accuracy and computational cost. To address this problem, this study presents a machine learning-based EnKF framework that maintains high accuracy with a relatively small ensemble size. Specifically, a multilayer perceptron (MLP) function is built to predict the difference between the forecast error covariances estimated from a limited ensemble and a sufficiently large ensemble, with the latter being assumed to be an accurate approximation of the underlying truth. This predicted covariance difference term is then incorporated into the EnKF
algorithm via an element-wise scaling strategy, resulting in an amended forecast covariance
matrix that better approximates the true uncertainty level and sequentially produces more accurate analysis results. To demonstrate the feasibility and robustness of the proposed
algorithm, we perform a set of numerical experiments with the Lorenz-63 and Lorenz-96 systems under various configurations, and the results consistently indicate that the proposed
algorithm can significantly outperform the standard EnKF with the same limited ensemble size, by achieving notably higher analysis accuracy while remaining computationally efficient. This approach provides a practical and feasible pathway to accurate and computationally efficient data assimilation for high-dimensional and nonlinear dynamic systems.
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All authors Zhou Yao, Zhilin Li, Li Zhao, Zeng Liu, Zhaokuan Lu, Seungnam Kim, Guangyao Wang
Medical Physics
Computed Tomography Reconstruction Algorithm Using Markov Random Field Model
Taiga Shimomiya, Taichi Kusumi, Masayuki Uesugi et al. (+4 more)
X-ray computed
tomography (CT) reveals the materials' internal structures non-destructively from a tilt series of projected images. Filtered back projection (FBP) is a widely-adopted reconstruction
algorithm in CT owing to its small computational cost. Under low-dose or sparse-view conditions, however, FBP often amplifies noise, severely degrading the reconstructed images. In this study, we evaluated the performance of a
Bayesian CT reconstruction
algorithm based on the Markov random field model under such adverse conditions. Through simulations, we demonstrated that the proposed
algorithm shows higher reconstruction performance than FBP under both low-dose and sparse-view conditions. The hyperparameters are estimated by minimizing the
Bayesian free energy, enabling adaptive reconstruction that reflects the noise characteristics of the observed projection data. These results suggest that the proposed
algorithm can broaden the applicability of CT to dose-sensitive applications and time-constrained measurements, where only limited observed projection data are available.
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All authors Taiga Shimomiya, Taichi Kusumi, Masayuki Uesugi, Akihisa Takeuchi, Yuki Sada, Hayaru Shouno, Masato Okada
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates
Zeyu Wang, Shuya Yamazaki, Martin Hoffmann Petersen et al. (+11 more)
The appearance of generative models has opened vast chemical spaces in the design of functional materials. Although machine learning interatomic potentials (MLIPs) have substantially accelerated
phonon calculations, high-fidelity prediction of
lattice thermal conductivity ąppa}lat still requires accurate treatment of anharmonic interactions, which remains a key challenge for existing potentials across novel chemical spaces. To address this challenge, we present a comprehensive
benchmark of 15 surrogate models for predicting ąppa}lat using the Phonix database, which contains 6,966 entries with anharmonic
phonon properties derived from first-principles calculations. Firstly, We categorize these surrogate models into three distinct groups: Physical-informed feature descriptors combined with ML models, end-to-end deep neural networks, and pre-trained MLIP-
embeddings combined with ML models. By evaluating model performance across random, space-group disjoint (testing generalization to unseen
crystal symmetries), and Out-Of-Distribution splits (OOD
dataset that testing extrapolation to property regimes beyond the training range) based on ąppa}lat, we probe both interpolation and exploration capabilities. Our results reveal that MLIP-embedded models excel in interpolation within well-sampled regions, deep neural network models especially ALiEGNN demonstrate superior robustness in OOD regimes critical for discovering novel low-ąppa}lat. Additionally, we find a systematic degradation in performance when the structural representation is reduced. Although surrogate models exhibit lower accuracy than direct simulations using first-principles calculation, they reduce computational costs by orders of magnitude, enabling efficient high-throughput screening of thermoelectric materials with minimal loss in generative design workflows.
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All authors Zeyu Wang, Shuya Yamazaki, Martin Hoffmann Petersen, Masato Ohnishi, Tomiya Yamamoto, Wei Nong, Jianghai Wang, Ruiming Zhu, Masatoshi Hanai, Michimasa Morita, Toyotaro Suzumura, Zekun Ren, Junichiro Shiomi, Kedar Hippalgaonkar
Chemical Physics
Gel-Chemistry-Controlled Heavy-Metal Transport and Retention in Cementitious Gel Nanopores: A Molecular Dynamics Study
Weiqiang Chen, Qiyao He and Kai Gong
Cementitious materials are widely used for hazardous-waste encapsulation, yet molecular mechanisms governing heavy-metal ion retention across gel chemistries remain insufficiently resolved. Previous MD studies have focused on individual gel systems and pore-averaged metrics, limiting direct comparison across gel chemistries. Here, classical molecular dynamics simulations were used to investigate adsorption-controlled mobility of Pb2+, Ba2+, and Cs+ in nanopores of C-S-H, C-(N)-A-S-H, and N-A-S-H gels. Combining pore-averaged and spatially resolved diffusivity, residence-time analysis, ion-density profiles, 2D adsorption maps, radial distribution functions, coordination analysis, and interfacial binding-strength descriptors establishes a framework linking gel surface chemistry to mobility suppression while distinguishing local mobility from spatial ion partitioning effects on pore-averaged transport. Ion mobility is reduced in all gel nanopores relative to bulk, but the extent and mechanism vary strongly with gel chemistry. C-(N)-A-S-H with higher interfacial Al/Si substitution exhibits the strongest retention, driven by ion accumulation around Al-linked oxygen species via an ion-exchange-like mechanism with charge-balancing Na+. C-S-H immobilizes ions primarily through surface hydroxyl oxygens and Ca-mediated linkages, whereas N-A-S-H exhibits more distributed binding environments. Pb2+ and Ba2+ show broadly similar immobilization mechanisms, whereas Cs+ exhibits more gel-dependent interactions with silicate and aluminosilicate oxygen sites. A relative total binding strength (rTBS) descriptor shows a strong positive correlation with ion immobilization across gel types, ion species, and pore sizes. These results clarify gel- and ion-specific retention mechanisms and link interfacial binding strength to pore-averaged mobility suppression in idealized cementitious nanopores.
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Atomic Physics · Cross-listed from cond-mat.quant-gas
Interband Berry connection measurement in the optical honeycomb lattice
Shao-Wen Chang, Malte N. Schwarz, Erin G. Moloney et al. (+2 more)
The geometry of Bloch bands affects many physical properties of crystalline solids and other spatially periodic systems. Direct experimental determination of such geometry is an active area of research. In this work, we focus on the fundamental connection between optical excitations and the relative geometry of pairs of Bloch bands, as characterized by the interband Berry connection. We simulate the response of electrons in solids to optical excitation by the response of ultracold fermionic atoms in optical
lattices to periodic modulation of the
lattice position. The strength of resonant excitation between bands, measured at each quasimomentum and for various
lattice-shaking polarizations, directly maps out the interband Berry connection. We apply this method to the optical honeycomb
lattice, driving excitations between the ground $n=1$ band and the excited $n'=\{2,3,4\}$ bands. We observe transparency lines of quasimomenta at which the response to excitation of specific polarization is zero. Further, the interband Berry connection between bands 1 and 3 shows irreducible Dirac strings connecting the $K$ and $K'$ points in the Brillouin zone, lines along which the interband Berry connection abruptly changes orientation. Our work establishes optical response as a powerful tool for characterizing geometrical and topological properties of band structure.
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All authors Shao-Wen Chang, Malte N. Schwarz, Erin G. Moloney, Ke Lin, Dan M. Stamper-Kurn
Optics
General Criteria for Certifying Genuine High-Dimensional Quantum Teleportation
Neng-Fei Gong and Tie-Jun Wang
Developing reliable methods for certifying the dimension of a given
quantum system or process is essential to ensure the validity of claimed realization of high-dimensional (HD)
quantum advantages. The existing criteria for certifying genuine HD
quantum teleportation (HDQT) mainly focus on demonstrating the successful transmission of genuine HD
quantum states. However, a complete certification of HDQT must also identify the
entanglement dimension of resource, which is critical for verifying whether the transmission capacity and noise resilience meet the necessary thresholds. Here we propose two universal criteria (based on fidelity and robustness, respectively) for certifying genuine HDQT behaviors that can close this gap by fully identifying the dimension of the
entanglement. Both criteria require only the input and output teleportation data and remain feasible under partial Bell-state measurements. Furthermore, the robustness-based criterion has stronger noise resistance and it requires no prior assumptions about local operations, making it robust even in black-box scenario. Our results establish a universal and reliable theoretical framework for validating the core
quantum advantage in HDQT, pivotal for ensuring the reliable links in HD
quantum networks.
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Instrumentation and Detectors
Outer Detector of Hyper-Kamiokande
R. Shinoda
Hyper-Kamiokande (HK) is the world's largest water Cherenkov ring-imaging detector, planning to start data taking in 2028. The Outer Detector (OD) surrounds the Inner Detector and plays a critical role in rejecting background events entering from outside, particularly
cosmic-ray
muons. We report on the selection of $8\,\mathrm{cm}$ diameter photomultiplier tubes (PMTs) for the OD, comparing Hamamatsu R14374 and NNVT N2031 candidates, and present the evaluation of
cosmic-ray
muon background reduction performance using a full detector simulation. Hamamatsu PMTs were adopted for their superior in-water detection efficiency in deep-UV and stability. The
cosmic-ray
muon reduction inefficiency reaches $O(10^{-6})$ with OD-based cuts alone, and $O(10^{-9})$ is expected when combined with fiducial volume cuts, which is sufficiently negligible for nucleon decay and atmospheric
neutrino analyses.
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Physics Education
The Gendered Cost of Lower Grades: Women's Physics Perceived Recognition and Identity Suffer Disproportionately If They Earn Less Than A Grade
Jaya Shivangani Kashyap, Christian D. Schunn and Chandralekha Singh
Perceptions of disciplinary recognition and identity can be shaped by various forms of feedback and experiences. Here we focus on the potential effects of course grades on the perceievd recognition and physics identity of students. We analyze patterns in changes in physics identity and perceived recognition from pre course to post course across three cohorts of university students enrolled in calculus-based Physics 1 (N=1,681). Students not receiving A grade, on average, showed declines in physics identity and perceived recognition. Even a B grade resulted in declines, and the declines were nonlinear across lower grades. Changes in perceived recognition fully mediated the changes in identity. Importantly, women showed significantly larger declines in identity and perceived recognition, compared to men, if they got less than A grade. The gender moderation was specifically localized to changes in perceived recognition, with no further gender effects on identity beyond the cascading effects on perceived recognition.
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Accelerator Physics
Phase synchronization recovery in energy-compressed LWFA electron beams for free-electron lasers via undulator tapering
Shan-You Teng, Wai-Keung Lau, Shih-Hung Chen et al. (+1 more)
Laser wakefield accelerators (LWFAs) are attractive compact drivers for free-electron
lasers (FELs) because they can generate femtosecond electron beams with high peak current over centimeter-scale acceleration distances. However, their relatively large energy spread remains a major obstacle to high-gain FEL operation. Although bunch energy compression can reduce the slice energy spread to a level suitable for FEL amplification, it also introduces a strong energy chirp. The energy chirp detunes the FEL resonance along the planar undulator, causing phase slippage between the electrons and the radiation field, reduced bunching efficiency, and degraded radiation power and spectral quality. Here we investigate a longitudinally tapered undulator for compensating the chirp-induced resonance mismatch in a self-amplified spontaneous-emission (SASE) FEL driven by an energy-compressed LWFA beam. Using three-dimensional unaveraged simulations, we show that an optimized taper profile restores electron-radiation phase synchronization and significantly improves both the saturation power and the spectral properties relative to the untapered case. We also assess the sensitivity of the scheme to shot-to-shot beam-energy fluctuations characteristic of LWFA operation. Our results show that undulator tapering is an effective method for mitigating chirp-induced performance degradation in compact
plasma-based FELs.
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All authors Shan-You Teng, Wai-Keung Lau, Shih-Hung Chen, Wei-Yuan Chiang
Atmospheric and Oceanic Physics
Generative climate downscaling enables high-resolution compound risk assessment by preserving multivariate dependencies
Takuro Kutsuna, Noriko N. Ishizaki, Norihiro Oyama et al. (+1 more)
Physics-based
climate projections using general circulation models are essential for assessing future risks, but their coarse resolution limits regional decision-making. Statistical downscaling can efficiently add detail, yet many methods treat variables independently, degrading inter-variable relationships that govern compound hazards such as heat stress, drought, and wildfire. Here we show that a
diffusion-based multivariate generative framework, combined with bias correction, recovers degraded inter-variable correlations even under a 50$\times$ increase in linear resolution. When applied to five meteorological variables over Japan, the framework reduces inter-variable correlation errors by more than fourfold relative to existing baselines while improving both univariate and spatial accuracy, leading to more accurate detection of severe drought. These results demonstrate that multivariate generative downscaling improves the reliability of compound risk assessment under large resolution gaps.
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All authors Takuro Kutsuna, Noriko N. Ishizaki, Norihiro Oyama, Hiroaki Yoshida
Optics
Non-orthogonal Transformations of Structured Light Using Ellipticity-Dependent Ince-Gaussian Modes
Dayver Daza-Salgado, Edgar Medina-Segura and Carmelo Rosales-Guzmán
The Ince-Gaussian modes form a complete set of solutions to the paraxial wave equation parametrized by an ellipticity parameter {\epsilon}, enabling a continuous transition between Laguerre-Gaussian and Hermite-Gaussian modes While each fixed {\epsilon} defines an orthogonal basis, modes associated with different ellipticities are not mutually orthogonal, and no explicit transformation between such bases has been reported. Here, we derive the first explicit finite analytical expression to transformation between Ince-Gaussian bases of arbitrary ellipticity, enabling direct and experimentally accessible mapping between non-orthogonal structured-light representations. We further demonstrate an experimental implementation using spatial light modulators to perform ellipticity-resolved modal decomposition. This framework introduces ellipticity as a controllable degree of freedom for structured light engineering, enabling new strategiesfor mode conversion, encoding, and high-dimensional optical information processing.
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Chemical Physics
One-Step Relativistic Driven Similarity Renormalization Group Multireference Perturbation Theory
Zijun Zhao and Francesco A. Evangelista
We present an efficient implementation of a one-step relativistic second-order multireference perturbation theory based on the multireference driven similarity renormalization group (MR-DSRG) using the exact two-component (X2C)
Hamiltonian, which we denote X2C-DSRG-MRPT2. We show that the X2C-DSRG-MRPT2 method can accurately capture
spin–orbit coupling (SOC) effects in the electronic structure of strongly correlated systems containing elements across the periodic table. We further demonstrate that the X2C-DSRG-MRPT2 method, through its variational treatment of SOC effects, can yield
spin–orbit splittings with mean absolute percentage errors consistently below 7% with respect to experimental values for systems containing up to sixth row elements. With its modest computational scaling (fifth power in system size) and high accuracy, X2C-DSRG-MRPT2 provides a promising avenue for the routine treatment of relativistic effects in strongly correlated molecular systems.
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Fluid Dynamics
Neural Refractive Index Primitives for Flame Field Reconstruction Using Background-Oriented Schlieren
Xinyi Lu, Wei Hu, Zizhou Liao et al. (+3 more)
An improved neural refractive-index-primitive method for background-oriented schlieren
tomography is presented, enabling continuous three-dimensional reconstruction of refractive-index fields using a compact multilayer perceptron. The method adopts the refractive-index field as the sole neural primitive and integrates multiresolution hash encoding, automatic-discrete gradient losses, and a three-dimensional mask to enable fast convergence and high-resolution, spatially coherent reconstructions. Tests on numerical combustion phantoms and real flame data demonstrate accurate recovery of both large-scale structures and fine-scale
turbulence, strong robustness to noise, and clear advantages over frequency-encoding-based and voxel-based reconstruction methods.
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All authors Xinyi Lu, Wei Hu, Zizhou Liao, Zheng Wang, Yue Zhang, Jingxuan Li
Applied Physics
Quantitative comparison of heat flow, guarded-heater and AC Harman methods for thermoelectric module efficiency
Kenjiro Okawa, Yasutaka Amagai, Norihiko Sakamoto et al. (+1 more)
The evaluation of thermoelectric conversion efficiency remains challenging owing to the lack of internationally standardized measurement protocols. Commonly used techniques -including the heat flow, guarded heater, and AC Harman methods-differ fundamentally in their operating principles and sensitivity to heat losses. In this study, we
benchmark three module-level efficiency measurement techniques -the heat-flow, guarded heater, and AC Harman methods- using commercial Bi2Te3-based modules with different module architectures. The conversion efficiencies obtained using the heat flow and guarded heater methods showed closely consistent central values and similar temperature-dependent trends over the investigated range. In contrast, the efficiency derived using the AC Harman method was systematically lower by approximately 16 % to 30 %, depending on the module architecture. Steady-state finite-element calculations of heat conduction and radiation indicated that the open thermal boundary condition used in the Harman configuration produces module-architecture-dependent internal temperature distributions and effective temperature differences, consistent with the experimentally observed trend. These results demonstrate that module-level efficiency estimated using the AC Harman method can be affected by nonideal thermal environments and emphasize the necessity of accounting for radiative and substrate-related heat losses. Nevertheless, the AC Harman method remains useful for rapid performance screening, provided that its module- and boundary-condition-dependent systematic bias is appropriately considered. Our results provide a quantitative
benchmark for major measurement techniques and support the development of best practices, method-selection guidelines, and future methodological standardization in module-level thermoelectric metrology.
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All authors Kenjiro Okawa, Yasutaka Amagai, Norihiko Sakamoto, Nobu-Hisa Kaneko