Atomic Physics · Cross-listed from cond-mat.quant-gas
Realizing multi-orbital Emery models with ultracold atoms
Conall McCabe, Jamie Boyd, Kaizhao Wang et al. (+5 more)
Strongly-correlated electrons in transition-metal
oxides give rise to intriguing emergent phenomena, including high-temperature superconductivity in cuprates. While simplified one-band Hubbard models capture some aspects, explicitly describing the interplay of copper and oxygen orbitals – as in the three-band Emery model – is essential to capture the full phenomenology of cuprates.
Quantum simulators based on ultracold atoms offer a promising route to study such systems in a controlled setting, but realizing realistic multi-orbital Hubbard models remains challenging. Here we propose an optical superlattice architecture that implements the three-band Emery model with ultracold
fermions. By combining
lattice beams with controllable interference, we engineer orbital degrees of freedom that reproduce key features of the cuprate band structure, while enabling independent control of orbital-dependent interactions and charge-transfer energy. We show that single-particle
quantum walks can
benchmark the resulting tight-binding model. Using determinant
quantum Monte Carlo, we further investigate thermodynamic properties in the undoped regime and find a finite-temperature metal-
insulator crossover accompanied by the onset of
antiferromagnetic correlations accessible in current experiments. Finally, we apply a
Hamiltonian learning protocol enabling to infer effective single-band Hubbard models from experimental realizations of Emery models. Our results provide a practical pathway to simulate multi-orbital Hubbard physics with
quantum gas microscopes.
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All authors Conall McCabe, Jamie Boyd, Kaizhao Wang, Martin Lebrat, Cindy Regal, Adam Kaufman, Ana Maria Rey, Lukas Homeier
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Chirality Transfer to the Magnetic Sublattice in the Hybrid Perovskite (R)-/(S)-3-Fluoropyrrolidinium Copper(II) Chloride
Zheng Zhang, Mingyu Xu, Jose L. Gonzalez Jimenez et al. (+4 more)
Incorporating
chiral organic cations into organic-inorganic hybrid materials has been shown to enable the inorganic sublattice to display chiroptical properties. We report a new two-dimensional
magnetic ($S=1/2$)
chiral metal halide perovskite, (R)- and (S)-$(C_4H_9FN)_2CuCl_4$ (where $(C_4H_9FN)^+$ is 3-fluoropyrrolidinium), which consists of Cu-Cl inorganic layers separated by $(C_4H_9FN)^+$ organic cations. The presence of the
chiral $(C_4H_9FN)^+$ organic cation induces formation of
chiral magnetic order, even though the inorganic sublattice itself is nearly structurally centrosymmetric. We also report the racemic variant, containing an equal amount of (R)- and (S)- cations, which shows no evidence of
chiral magnetic order. When the
magnetic susceptibility is measured perpendicular to inorganic Cu-Cl layer propagation direction, an
antiferromagnetic phase transition at Néel temperature $T_N = 2.23~K$ is observed in both the
chiral and racemic materials, and the existence of the
magnetic phase transition is supported by specific heat capacity measurements. Field-induced
magnetic chirality is observed through the existence of a second-order magnetoelectric effect in the
chiral variant, while no magnetoelectric signal is observed for the racemic material, indicating the absence of
magnetic chirality. Our findings demonstrate that materials exhibiting
chiral magnetic order can be created through the incorporation of a
chiral cation into an organic-inorganic hybrid
magnetic material, potentially allowing for the design of tailored materials that combine
chiral magnetism with other desirable optical and electronic properties that come from structural chirality.
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All authors Zheng Zhang, Mingyu Xu, Jose L. Gonzalez Jimenez, Stephen Zhang, Weiwei Xie, Xianghan Xu, Daniel B. Straus
Accelerator Physics
Controlling and Measuring the Degree of Coherence at CLS using X-ray Interferometry
Y. Y. Sigari, N. A. Simonson, N. Appathurai et al. (+6 more)
This paper investigates a case study on measuring and controlling the first-order degree of spatial coherence under different coupling adjustments in the storage ring. The experimental findings are consistent with the predicted inverse relationship between the visibility and the coupling factor. The degree of coherence was measured using X-ray double slit interferometry with synchrotron radiation at an energy of 7 keV on the Brockhouse X-Ray Diffraction and Scattering in-
vacuum undulator beamline. The vertical degree of coherence increases as the coupling factor in the storage ring is reduced. The Linear Optics for Closed Orbit (LOCO)
algorithm is used to model the linear terms of the storage ring optics in Accelerator Toolbox. The LOCO-tuned model provides insights into the variations in the vertical beam size at two different source points in the storage ring as a function of the coupling factor. The coupling factor is parameterized by the closest-tune approach with a bunch-by-bunch feedback system to confirm the trend in the changes of the vertical beam size and the visibility.
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All authors Y. Y. Sigari, N. A. Simonson, N. Appathurai, R. Castle, B. D. Moreno, S. Saadat, J. Wang, J. M. Vogt, M. J. Boland
Chemical Physics
Absence of demixing in 2D binary mixtures of alcohols
Lydia Chelli and Aurélien Perera
Binary mixtures of two-dimensional, site-based models of alcohols are investigated by computer simulations, focusing on ideal mixing, local clustering and miscibility trends. Four systems are considered: methanol-ethanol, butanol-pentanol, methanol-pentanol, and methanol-octanol, the first two being expected to be ideal mixtures because of the proximity of the molecules, while the last two are examples of mixing distant alcohols. The models retain chemical specificity of their 3D counterparts, thus allowing one to investigate dimensional constraints and non-trivial micro-structurations. It is found that mixtures of short and long alcohols remain miscible, in contrast with the corresponding macroscopic phase separation observed in three dimensions. This issue is analyzed through snapshots, site-site distribution functions, structure factors and Kirkwood-Buff integrals (KBI). It is found that the short range part features are dominated by charge ordering of the hydroxyl head groups, while the long range part develops persistent oscillatory features affecting the determination of the KBI, and suggesting the presence of anomalous domain-like concentration fluctuations. All these findings suggest a complex interplay between charge ordering of the hydrophilic head groups and the hydrophobic tail groups.
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Atmospheric and Oceanic Physics
The material life cycle of Koobor: separating coherent organization from potential-vorticity evolution in a wildfire-generated stratospheric vortex
F. Andrade-Canto and F.J. Beron-Vera
Pyro-cumulonimbus convection associated with extreme wildfires can generate long-lived stratospheric
vortices, yet their material coherence and life cycle remain poorly characterized. We apply geodesic
vortex detection to winds from reanalysis to identify objectively defined (observer-independent) material boundaries of Koobor, generated by the 2019–2020 Australian bushfires. These boundaries are closed material curves that undergo uniform finite-time tangential stretching and resist filamentation. We reconstruct their
evolution across isentropic levels. Material coherence develops upward from 590~K, reaches maximum persistence at 690~K, and becomes progressively shorter-lived at higher levels. At 690~K, the reconstructed birth-to-death interval is approximately 40~days, while overlapping detections across levels define a nearly 60-day envelope. Analysis of potential vorticity (PV) within and around these material boundaries reveals a distinct dynamical
evolution: the material boundary forms before strong PV isolation develops, a compact PV core emerges during the mature phase, and PV isolation weakens as material coherence approaches its demise. Strong PV isolation is concentrated at intermediate levels, whereas at 850~K material coherence occurs without a comparably well-defined PV core. These results provide an objective material description of the birth, vertical development, and decay of a wildfire-generated stratospheric
vortex and show that material organization precedes the development of its strongest PV signature, which subsequently intensifies and weakens over the lifetime of the coherent
vortex.
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Optics · Cross-listed from cond-mat.dis-nn
Delocalization transition for light in two dimensions
Sébastien Lucas, Christian Miniatura and Sergey E. Skipetrov
Common belief, confirmed by existing experiments, is that arbitrarily weak disorder should lead to spatial localization of eigenmodes of scalar wave equations when wave propagation is two-dimensional (2D). We predict that contrary to this belief, a localization-delocalization transition can take place for light scattered by two-level atoms placed at random positions in the middle plane of a parallel-plate 2D waveguide fed by its fundamental transverse-
magnetic (TM) mode (electric field polarized perpendicular to the waveguide and atomic planes). This transition, driven by near-field dipole-dipole interactions between atoms, occurs upon increasing the areal number density of atoms beyond some critical value. A finite-size scaling analysis of the transition yields an estimate of its critical exponent ${\nu}$ = 1.4 $\pm$ 0.2.
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Classical Physics
Electric potential of insulated conducting objects in presence of electric charges – some exact and approximate results
Karlo Filipan and Hrvoje Štefančić
Determination of the electric potential of insulated conducting objects is an important problem both theoretically and practically. For an insulated conducting object in the presence of external charges or charges distributed on the object surface, the problem of potential determination is reformulated using a newly introduced $J$ formalism. Using the $J$ formalism, it is shown how the electric potential can be calculated exactly for spherical objects and efficiently approximated for other object geometries using geometrical properties of the insulated conducting object. This approach does not require calculation of the surface charge distribution at the object surface of the calculation of the electric potential in the surrounding space. Properties and the performance of the approach are investigated numerically using the Robin Hood method. Possible applications of the approach based on the $J$ formalism are outlined for calculation of capacitance of conducting objects.
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Medical Physics
Fingertip Micro-Motion as a Source of Respiratory Information During Sleep Using Triaxial Accelerometers
Jeanne Lin, Lily Liu, Chih-Wei Hsu et al. (+1 more)
Objective: Triaxial accelerometers (TAAs) are widely used in home care medicine. This study investigates whether TAA signals recorded at the fingertip encode respiratory information, particularly instantaneous respiratory rate (IRR) and respiratory effort, during sleep. Method: We propose an antiderivative-based nonlinear transformation to convert TAA signals into a respiratory surrogate, termed TAA-resp. To quantify the embedded respiration-induced oscillation, a modern time-frequency analysis tool is applied to derive an index, referred to as the respiratory motion index (RMI). The proposed TAA-resp and RMI are validated on two
datasets comprising 39 Asians and 10 white or African Americans with full-night recordings from simultaneous polysomnography (PSG) and a fingertip TAA measurement. Criteria for labeling TAA-resp signal quality as good, moderate, or poor are established, and two experts' independent annotations with consensus are obtained. Result: On average, TAA-resp encodes high-quality respiratory information in over 21.25%$\pm$16.11% of full-night recordings, reaching up to 58.33% in some cases. TAA-resp shows stronger correlation with thoracic and abdominal motion than with airflow, indicating predominant capture of respiratory effort. High-quality TAA-resp segments offer an accurate IRR estimate with root mean square error $0.027\pm 0.022$ Hz. RMI is higher for high-quality segments and lower for poor-quality segments, and its distribution aligns with physiology, with higher values during REM, N2, and N3 sleep and in the absence of apnea or hypopnea events. In leave-one-subject-out cross-validation, RMI predicts quality labels with 0.84 sensitivity and 0.88 specificity. Conclusion: Fingertip-mounted TAAs encode meaningful respiratory information intermittently, and our method recycles underutilized respiratory information.
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All authors Jeanne Lin, Lily Liu, Chih-Wei Hsu, Hau-Tieng Wu
Computational Physics · Cross-listed from cs.LG
Predicting Wind Loads on Container Ships in Harbor Environments through Multi-Fidelity Modeling
Matilde Fiore, Andrea Bresciani, Miguel Alfonso Mendez et al. (+1 more)
Modern container ships face higher wind loads due to increased windage areas, making accurate predictions of wind loads essential for mooring design. Existing empirical models, largely developed for container ships with smaller windage areas and simpler geometrical configurations than those of modern large-scale vessels, often lack accuracy and do not account for the influence of nearby structures. This study proposes a multi-fidelity surrogate modelling framework for the prediction of wind-load coefficients, combining empirical correlations with simplified and detailed CFD models for ships in open-sea and harbor environments. The approach relies on recursive co-kriging to consistently fuse information across fidelity levels, enabling accurate predictions at a reduced computational cost. A sensitivity analysis is used to identify the most influential
geometric parameters, and the resulting reduced parameter space is explored through sequential sampling to efficiently construct the training database. The surrogate models are validated over a wide range of loading configurations and for two distinct harbor environments. The results demonstrate that the multi-fidelity approach significantly improves prediction accuracy compared to single-fidelity models, while substantially reducing the reliance on high-fidelity simulations. In particular, the proposed framework captures the dependence of wind loads on key
geometric parameters and consistently outperforms traditional empirical correlations, providing a robust and efficient tool for engineering applications.
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All authors Matilde Fiore, Andrea Bresciani, Miguel Alfonso Mendez, Jeroen van Beeck
Computational Physics · Cross-listed from math.NA
Craig-Bampton-based Quadratic Manifold for Nonlinear Substructuring
Alexander Saccani and Paolo Tiso
Component Mode Synthesis methods, such as the Craig-Bampton (CB) approach, are widely used in structural dynamics due to their modularity and compatibility with substructuring workflows. While highly effective for linear systems, extending these methods to geometrically nonlinear structures remains a significant challenge. In this work, we propose a nonlinear extension of the CB method tailored to such contexts. The approach is based on the construction of a quadratic reduction
manifold, derived via perturbation analysis, in which high-frequency fixed-interface modes are statically condensed onto a reduced set of low-frequency modes and interface coordinates. This formulation enables the representation of
geometric nonlinear effects without increasing the number of reduced degrees of freedom.The resulting Nonlinear Craig-Bampton (NL-CB) reduced-order model is obtained through Galerkin projection onto the tangent space of the
manifold and admits a
polynomial structure that is efficient for time integration. The formulation preserves the Lagrangian structure of the underlying finite element model, ensuring consistent energetic behavior and numerical stability.The proposed method is demonstrated on representative nonlinear structural systems of increasing complexity. The results show that the NL-CB model captures the essential nonlinear dynamic response while retaining the modularity and computational efficiency of classical substructuring approaches.
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Plasma Physics
Revisiting confinement scalings and fusion performance with a perspective optimized for extrapolation
Jalal Butt, Geert Verdoolaege, Stanley M. Kaye et al. (+1 more)
Recent advances in high-temperature-
superconductor technology have made substantially higher toroidal
magnetic fields technologically accessible, reopening the design space for compact, high-field tokamak reactors. Because reactor performance projections remain anchored to empirical confinement scalings, the recent update to the ITPA global H-mode confinement database raises an important question: what does the present experimental record and its uncertainty imply for the path to reactor-grade fusion performance? In this work, we revisit confinement extrapolation from an explicitly extrapolation-oriented perspective and, to complement its implications in terms of a direct reactor performance measure, present a cross-machine empirical scaling for fusion power. We systematically search for a minimally complex confinement scaling that optimizes the tradeoff between variance capture and extrapolative robustness. We find that low-order models centered near $N=3$ to $N=4$ optimize this tradeoff, with
plasma current, machine size, heating power, and elongation emerging as the dominant engineering levers, together with an empirically inferred confinement penalty associated with metallic walls. Recast in reactor-performance terms, the results indicate that both the fusion triple product and fusion power are governed primarily by
plasma current: the triple product scales approximately as $I_p^2$, and the empirical fusion power scaling exhibits a similarly near-quadratic dependence over a survey of the highest performing discharges across several machines. Projecting to reactors, these results suggest that high-field devices with metal walls may require higher
plasma current than standard IPB98$(y,2)$-based expectations imply, and that gigawatt-class tokamak performance likely demands operation at $I_p \gtrsim 20\mathrm{MA}$.
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All authors Jalal Butt, Geert Verdoolaege, Stanley M. Kaye, Egemen Kolemen
Atmospheric and Oceanic Physics
Spectral-Domain Local Statistics with Missing-Data Support for Cartesian and Polar Grids
Jairo M. Valdivia-Prado, William E. Chapman and Katja Friedrich
This paper presents a method for computing local mean, variance, standard deviation, and effective sample count on incomplete gridded data using boundary-aware spectral operators. The framework combines normalized convolution with explicit boundary-condition modeling: reflective Discrete Cosine Transform (DCT) for non-periodic Cartesian axes and periodic Real Fast
Fourier Transform (RFFT) for circular azimuth processing in polar geometry. Stability safeguards (denominator floor, prefill fallback, and variance clamp) are specified for under-supported regions. We evaluate the framework across three targeted scenarios: a Cartesian boundary-condition check demonstrating the mitigation of wrap-around artifacts, a synthetic 3D outlier-identification test, and a real-radar polar application. Results establish bounded, support-aware interpretation of local statistics while preserving a concise reproducibility path through the open-source 'dct\_toolkit' implementation.
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Classical Physics
How the Hahn-Banach Theorem Sheds Bright Light on Fundamental Questions in Classical Thermodynamics
Martin Feinberg and Richard B. Lavine
The Hahn-
Banach Theorem, a cornerstone of modern functional analysis, is a natural companion of the Second Law of Thermodynamics. From a Kelvin-Planck version of the Second Law, the Hahn-
Banach Theorem delivers, immediately and simultaneously,
entropy and thermodynamic-temperature functions of the local material state such that the Clausius-Duhem inequality is satisfied for every process a particular material might admit. For existence of such functions there is no need at all to require that their domain be restricted to states of
equilibrium. However, the Hahn-
Banach Theorem also indicates that for uniqueness of such a pair of functions across the entire state-space domain, every state must be visited by a reversible process. This review is intended to help make accessible to both thermodynamics scholars and mathematicians the remarkable interplay of the Hahn-
Banach Theorem and the Second Law.
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Medical Physics
OpenMRF: A Modular, Vendor-Neutral Open-Source Framework for Reproducible Magnetic Resonance Fingerprinting using Pulseq
Tom Griesler, Jannik Stebani, Sydney Kaplan et al. (+15 more)
Purpose: Widespread adoption and methodological advancement of
Magnetic Resonance Fingerprinting (MRF) are limited by the lack of unified, reproducible implementation frameworks and fragmented open-source tools. To address these barriers, we introduce OpenMRF - a comprehensive Pulseq-based solution - designed to enable consistent, reproducible, and transferable MRF research across vendors, sites, and field strengths. Methods: OpenMRF integrates modular Pulseq-based sequence design, Bloch-simulation-based dictionary creation directly from .seq files, and iterative low-rank subspace reconstruction. The framework was evaluated through digital phantom simulations, a multi-site ISMRM/NIST phantom study on Siemens MRI systems at 0.55 T, 1.5 T, and 3 T as well as GE and United Imaging 3 T platforms, and representative in vivo acquisitions in the liver (0.55 T), myocardium (1.5 T), and
brain (3 T). Results: Simulations demonstrated high mapping accuracy in an ISMRM/NIST-like digital phantom, with low-rank reconstruction yielding deviations of 0.03+/-0.32 % (T1) and 0.12+/-1.94 % (T2). The multi-site phantom study yielded relaxation times consistent with reference values at all field strengths, with mean deviations of -0.1+/-2.9 % (T1), -1.5+/-8.7 % (T2), and -4.0+/-7.2 % (T1rho). In vivo acquisitions produced high-quality parameter maps across platforms and field strengths. Conclusion: OpenMRF provides a robust, open-source, end-to-end Pulseq-based solution for MRF that enables reproducible sequence implementation, physics-accurate dictionary simulation, and advanced reconstruction across vendors and field strengths. By providing a unified platform for method development, comparison, and multi-site validation, OpenMRF aims to accelerate reproducible and harmonized quantitative MRI research within the community.
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All authors Tom Griesler, Jannik Stebani, Sydney Kaplan, Ivaylo Angelov, Petra Albert, Martin Blaimer, Tobias Wech, Xiang Wang, Qingping Chen, Maxim Zaitsev, Zhibo Zhu, Qi Liu, Peter Martin, Jon-Fredrik Nielsen, Jesse I Hamilton, Peter Nordbeck, Nicole Seiberlich, Maximilian Gram
Computational Physics · Cross-listed from quant-ph
Approaching the Limit of Quantum Clock Precision
Chad Nelmes, Emanuel Schwarzhans, Tony Apollaro et al. (+2 more)
Precise and autonomous clocks are of fundamental interest and central importance to both foundational studies and practical applications. Here, we construct a blueprint for a
quantum clock governed by time-independent interactions. By carefully-engineered coherent transport in dissipative
spin chains, we achieve a scaling exponent at the precision-resolution trade-off fundamental bound, bringing this within reach of physically realistic and experimentally accessible systems. We further introduce a sudden-quench protocol that enables repeated operation through a simple initialization and detachment mechanism. Remarkably, the protocol is robust to imprecise detachment timing, implying that high-precision timekeeping can be achieved even when driven by a clock with much lower precision.
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All authors Chad Nelmes, Emanuel Schwarzhans, Tony Apollaro, Timothy Spiller, Irene D'Amico
Chemical Physics
Pressure-Temperature Phase Diagram and $\lambda$-Transition in Liquid Sulfur
Sonia Salomoni, Frédéric Datchi, A. Marco Saitta et al. (+1 more)
Using molecular dynamics simulations driven by a machine-learned interatomic potential, we investigate at low to intermediate pressures the $\lambda$-transition of sulfur, a temperature-induced polymerization. At ambient pressure, we capture the melting of crystalline cyclo-octasulfur into a
liquid of molecular rings. Within this
liquid, the concentration of non-S$_8$ rings increases with temperature; we show that these molecules act as reactive centers, which eventually trigger polymerization. We reproduce key experimental signatures of the $\lambda$-transition, including the sharp increase in heat capacity and the pronounced dependence of the transition temperature on the heating rate. Building on this, we reconstruct a phase diagram of polymerization up to intermediate pressures. Our results reveal a moderate decrease of the polymerization temperature with pressure, culminating with its merging with the melting line at a critical point. Beyond this point, we provide direct evidence of polymerization emerging from the crystalline phase. By analyzing temperature-ramp trajectories, we observe the formation of non-S$_8$ rings, open chains, and extended polymeric structures which retain features of the crystalline arrangement; further heating the system leads to disorder taking over through melting. Polymerization is therefore initiated slightly before melting. Altogether, our findings provide a microscopic picture of the $\lambda$-transition throughout the sulfur phase diagram.
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All authors Sonia Salomoni, Frédéric Datchi, A. Marco Saitta, Arthur France-Lanord
Physics and Society
Self-Similarity in Online Networks During Social Movements
Manuel Suarez-Roman, M. Ángeles Serrano and Yérali Gandica
Online platforms provide an infrastructure for social movements, leaving digital traces that can be modelled as networks to quantify how information, participation, and coordination emerge during episodes of collective action and evolve over time. In this work, we unveil the emergence of scale-invariant online interaction patterns in social movements through network analysis of three geographically and sociopolitically distinct massive mobilisation events. By constructing co-occurrence networks from Twitter (now X) hashtag data and applying a degree-thresholding renormalisation procedure, we demonstrate that these highly correlated social phenomena exhibit clear signatures of self-similarity at peak mobilisation times. These critical points are characterised by modular-to-nested transitions, both in the co-occurrence networks and the bi-partite ones, maxima in user participation, and clustering spectrum collapse across multiple network scales. Despite their geographical and sociopolitical diversity, all three movements display remarkably analogous self-similar properties. Furthermore, the results hint at the emergence of a latent metric structure that supports successful
hyperbolic embedding, providing an estimate of effective social distance. Together, these findings suggest that self-similarity may constitute a universal organising principle of social movements during peak mobilisation phases, as it lays the groundwork for the rapid amplification of information across scales that is necessary for the successful coordination of collective action.
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Chemical Physics
Unveiling the Molecular Driving Forces of Pollutant Extraction by Hydrophobic Eutectic Solvents
S. Gomez, U. Ali, A. Muroni et al. (+3 more)
Hydrophobic eutectic solvents (HES) are emerging as sustainable alternatives to conventional organic solvents for the extraction of molecular pollutants from water. Yet, their selectivity remains poorly understood, hindering the predictive design of eutectic solvents beyond empirical success. Here, we present a multiscale strategy to rationalize and predict solute partitioning in HES. Focusing on bisphenol A (BPA) in trioctylphosphine
oxide (TOPO):menthol as a prototypical system, we combine monophasic and biphasic molecular dynamics with
quantum energy decomposition of dominant solvation motifs. Our methodology captures the experimentally measured BPA spontaneous migration and thermodynamic stabilization in the HES phase but also identifies the microscopic origin of selectivity: cooperative hydrogen bonding couples to strong dispersion and polarization in the hydrophobic eutectic microenvironment. The robustness of our workflow paves the way for the predictive in-silico screening and design of HES formulations for green and sustainable applications.
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All authors S. Gomez, U. Ali, A. Muroni, A. Mele, M. E. Di Pietro, T. Giovannini
Chemical Physics
DeepHartree: A Poisson-Coupled Neural Field for One-Shot Density Functional Theory
Jiankun Wu, Jinming Fan, Chao Qian et al. (+1 more)
Density functional theory (DFT) with linear combinations of atomic orbitals (LCAO) is costly because of Coulomb-
matrix construction and self-consistent-field (SCF) iterations. We introduce DeepHartree, a Poisson-coupled neural field that connects continuous real-space prediction to LCAO electronic structure. An E(3)-equivariant network predicts the Hartree potential, and the Poisson equation yields the electron density. Atom-centred Gaussian fields resolve near-
nuclear structure, and a molecular correction enforces the electron count. Analytical Gaussian integrals and numerical quadrature assemble the Kohn-Sham
matrix; one diagonalization yields orbital estimates and a density
matrix for energy evaluation and SCF initialization. Mean molecular weighted normalized mean absolute density errors (wNMAEs) are 0.110% for QM9 and 0.199% for VQM24 on PySCF level-0 grids, rising to 1.366% and 2.218% on level-3 grids. Models trained on def2-SVP densities transfer to def2-TZVP and def2-QZVP without retraining, retaining total-energy accuracy and occupied-subspace agreement. A Hybrid method combines finite differences, first-order automatic differentiation, analytical integrals, and multilevel quadrature for near-linear density-
matrix construction in alkanes and PEG chains. Excluding grid construction, the density-
matrix build for a 1004-atom PEG chain is 8.75-fold faster than full automatic differentiation and 7.34-fold faster than converged GPU4PySCF SCF. Without fine-tuning, the QM9 model achieves a total-energy MAE of 9.437 meV per atom on 1,000 larger OE62 molecules. DeepHartree initialization reduces mean QM9 SCF iterations by 15.3-15.6% across the three basis sets and total SCF time by 12.9% for a 620-atom organic cage, including initialization. These results support continuous electrostatic fields as an accurate, scalable interface between machine learning and LCAO DFT.
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All authors Jiankun Wu, Jinming Fan, Chao Qian, Shaodong Zhou
Medical Physics
A CMUT-Based Transcranial Focused Ultrasound Platform for Blood-Brain Barrier Opening in Small Animal Models
Sait Kilinc, Reza Pakdaman Zangabad, Victor Menezes et al. (+3 more)
Drug delivery to the
brain is limited by the blood-
brain barrier (BBB). We developed a capacitive micromachined ultrasonic transducer (CMUT)-based transcranial focused ultrasound system capable of both delivering therapy via BBB opening and monitoring microbubble activity across a broad frequency range. The performance of the geometrically focused half-ring array consisting of five transmitters and one receiving element was first assessed through simulations and in-vitro acoustic measurements with microbubbles. Use of phase-inversion (PI) during transmission effectively suppressed CMUT-generated harmonics and enhanced broadband detection of microbubble emissions. In rats, the same system achieved spatially localized BBB opening, confirmed by T1-weighted
magnetic resonance imaging. BBB permeability mapping using dynamic contrast-enhanced
magnetic resonance imaging (Ktrans) scaled with pressure. Time-resolved acoustic spectra captured microbubble arrival and decay kinetics, and 7-20dB enhancement in the effective dynamic range is observed with PI processing of acoustic emission signals. Together, these findings establish an integrated CMUT platform for combined therapeutic and sensing applications for BBB opening in small animal models, providing a foundation for future real-time, frequency-agile, closed-loop control of ultrasound-mediated drug delivery to the
brain.
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All authors Sait Kilinc, Reza Pakdaman Zangabad, Victor Menezes, Hohyun Lee, Costas Arvanitis, Levent Degertekin
Optics
Fully multiplexed photonic tensor computing
Aolong Sun, Junhao Zhao, Fangchen Hu et al. (+21 more)
Tensor operations dominate modern computational workloads, yet their further acceleration demands hardware platforms with greater parallelism. Although photonic computing provides a compelling route for parallel processing, fully exploiting all native multiplexing dimensions of optical fields is impeded by the challenges in routing and programming light in all dimensions simultaneously. Here we introduce FieldCore, a fully multiplexed photonic tensor core that jointly harnesses wavelength,
radio-frequency, guided-mode, time and space dimensions, thereby enabling parallelism to scale multiplicatively within a single optical field. Enabled by inverse-designed silicon photonics, FieldCore preserves a uniform programmed computation across all multiplexed channels in parallel. Experimentally, we validate and
benchmark its performance from ultra-high-baudrate arithmetic operations to high-fidelity image convolution and parallel handwritten-digit recognition. We further use FieldCore to unlock applications that naturally require high-dimensional data processing, such as high-dimensional hyperspectral classification and massively parallel mechanical fault diagnosis. Our FieldCore supports an estimated aggregate compute throughput of 69.12 tera operations per second (TOPS) and accommodates up to 1,800 parallel input streams within a single core, establishing a scalable paradigm for fully multiplexed photonic tensor computing and AI inference.
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All authors Aolong Sun, Junhao Zhao, Fangchen Hu, Sizhe Xing, Yuqin Yuan, Jialin He, Yongzhu Hu, Xuyu Deng, Yinjun Liu, Ouhan Huang, Baiheng Zhao, Hancheng Liu, Tian Dong, Jingkai Zhou, Haoyang Sun, Liang Chen, Chao Shen, Feng Bao, Ziwei Li, Jianyang Shi, Wei Chu, Bowei Dong, Nan Chi, Junwen Zhang
Instrumentation and Detectors
Beam test of a Pb/SciFi prototype for the Barrel Imaging Calorimeter at the Electron-Ion Collider
Hyungjun Lee, Changhui Lee, Jaehyeok Ryu et al. (+27 more)
A Lead-Scintillating Fiber (Pb/SciFi) prototype for the Barrel Imaging Calorimeter (BIC) at the Electron–Ion
Collider (EIC) was tested with electron beams at the CERN PS T10 beam line in August 2024. The prototype consisted of unit modules with a sampling structure of lead sheets and scintillating fibers, corresponding to a total depth of approximately $10.9\,X_{0}$. Beam tests were performed with electron momenta between 0.5 and 3~GeV/$c$ to evaluate the energy and timing performance of the prototype. This study characterizes the performance of a Pb/SciFi prototype and provides input for future beam tests, calibration and readout optimization, and the development of larger-scale prototypes.
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All authors Hyungjun Lee, Changhui Lee, Jaehyeok Ryu, Geunpil An, Joonsuk Bae, Yunseul Bae, Jeongsu Bok, Yun Eo, Wooseok Ham, Yoonha Hong, Manoj Jadhav, Seo Yun Jang, Jinryong Jeong, Hyon-Suk Jo, Sylvester Joosten, Beomkyu Kim, Bobae Kim, Chong Kim, Dongguk Kim, Minsuk Kim, Shin Hyung Kim, Wonjun Ko, Sehwook Lee, Sanghoon Lim, Jessica Metcalfe, Zisis Papandreou, Sangwoo Park, Junseop Shin, Hwidong Yoo, Maria Żurek
Optics
Enhanced Phase Sensitive SD-OCT for flow imaging using ultrasonically sculpted optical waveguides
Lloyd Lobo, Junze Liu, Hang Yang et al. (+3 more)
Phase sensitive detection in spectral domain optical coherence
tomography (SD-OCT) is a powerful method for functional imaging of biological events with high spatiotemporal resolution. The depth-dependent signal-to-noise ratio (SNR) is a limiting factor on the minimum detectable phase changes of phase in shot noise-limited SD-OCT systems. The SNR over a depth is constrained by the terminal optics, usually using a focusing lens to project light into the tissue and collect the backscattered light. In situ ultrasonically sculpted optical waveguides have been used to improve SNR roll-off over depth compared to conventional SD-OCT systems. In this paper, we extend this feature to demonstrate phase sensitive detection at depth using ultrasonically enhanced OCT (ue-OCT). Our experimental results show that ultrasonically sculpted optical waveguides are phase stable and follow near shot-noise limited behavior. We measured milk flow velocity changes to demonstrate a phase sensitivity of 5.25 mrad at 10 dB SNR and dynamic range of 0.8 mm/s to 14.7 cm/s using ue-OCT. Our results show flow detection with ue-OCT at extended depths (i.e., 3.5 mm) otherwise not possible with conventional SD-OCT systems with matched focal lengths. The results in this paper show the potential of ue-OCT for phase-sensitive flow measurement from the depth of tissue for a gamut of applications such as cerebral blood flow imaging as a proxy to neural activity mapping.
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All authors Lloyd Lobo, Junze Liu, Hang Yang, Yasin Karimi, B. Hyle Park, Maysamreza Chamanzar
Computational Physics · Cross-listed from quant-ph
The Exact Replica Threshold for Nonlinear Moments of Quantum States
Shuai Zeng
Joint measurements on multiple copies of a
quantum state provide access to nonlinear observables such as $\operatorname{tr}(\rho^t)$, but whether replica number marks a sharp information-theoretic resource boundary has remained unclear. For every fixed order $t\ge 3$, existing protocols show that $\lceil t/2\rceil$ replicas already suffice for
polynomial-sample estimation of $\operatorname{tr}(\rho^t)$, yet it has remained open whether one fewer replica must necessarily incur a sample-complexity barrier growing with the dimension. We prove that this is indeed the case in the sample/copy-access model with replica-limited joint measurements: any protocol restricted to $\lceil t/2\rceil-1$ replicas requires dimension-growing sample complexity, while $\lceil t/2\rceil$ replicas suffice by prior work. Thus the exact replica threshold for fixed-order pure moments is $\lceil t/2\rceil$. Equivalently, for fixed-order pure moments, one additional coherent replica is not merely useful but marks the exact threshold between
polynomial-sample estimation and a dimension-growing regime in the replica-limited model. We further show that the same threshold law extends to a broad family of observable-weighted moments $\operatorname{tr}(O\rho^t)$, including Pauli observables and other observables with bounded operator norm and macroscopic trace norm. Coherent replica number therefore acts as a genuinely discrete resource for nonlinear
quantum-state estimation.
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Optics
Memory in Integrated Photonic Neural Networks: From Physical Mechanisms to Neuromorphic Architectures
Alessandro Foradori, Ilya Auslender, Stefano Biasi et al. (+4 more)
The rapid scaling of artificial neural networks has exposed fundamental limitations of conventional von Neumann computing architectures. In these systems, the physical separation between
memory and processing creates a bottleneck, as computational capabilities outpace the ability of
memory and interconnects to supply and retrieve data. In contrast, biological neural systems inherently co-localize computation and
memory through distributed, dynamical processes. Neuromorphic computing seeks to emulate this paradigm by leveraging physical substrates whose intrinsic dynamics simultaneously encode and process information. Among emerging platforms, silicon photonics offers a compelling approach due to its high bandwidth, low-loss propagation, and inherent parallelism. This review examines the role of
memory in integrated photonic neuromorphic systems, with emphasis on the physical mechanisms that provide volatile and non-volatile
memory mechanisms, while distinguishing their retention properties from their temporal behaviour and computational role as state or parameter
memory in silicon-on-
insulator and hybrid silicon-on-
insulator platforms. Drawing inspiration from digital, biological, and photonic
memory architectures, we classify existing approaches based on their underlying physical principles. We cover implementations ranging from delay lines and slow-light structures to multistable dynamics and structural
memory based on charge trapping and phase-change materials. We then discuss how these mechanisms support photonic neural network architectures, and assess their relevance for time-dependent signal-processing tasks such as channel equalization in telecommunications. This review aims to establish a unified framework for understanding
memory and learning in neuromorphic photonics and outlines key challenges and opportunities for scalable, energy-efficient neuromorphic hardware.
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All authors Alessandro Foradori, Ilya Auslender, Stefano Biasi, Stefano Gretter, Alessio Lugnan, Emiliano Staffoli, Lorenzo Pavesi
Optics
Retrieving intrinsic polarization anisotropies of nanostructures using differential Mueller matrix polarimetry
Jeeban Kumar Nayak, Ebru Buhara and Olivier J.F. Martin
Accurate characterization of polarization dependent light matter interactions in nanostructured systems is paramount for the development of
chiral metasurfaces. It is also often challenging, because multiple anisotropic mechanisms, such as linear and circular diattenuation, birefringence, and depolarization can coexist and couple with one another. Conventional ellipsometric and chiro optical techniques typically assume isolated polarization effects and can therefore yield inaccurate estimates of the intrinsic polarization parameters. Here, we demonstrate that Mueller
matrix polarimetry combined with a differential Mueller
matrix decomposition provides a robust framework for retrieving the intrinsic polarization response of complex nanophotonic systems. Using plasmonic gammadion arrays and media with multiple polarization anisotropies as multi modal
chiral platforms, we show that simultaneous linear and circular anisotropies produce coupled signatures in the Mueller
matrix, leading to significant artifacts in conventional polarization observables. Through analytical modeling and experimental measurements, we quantify these artifacts and demonstrate that a differential decomposition accurately decouples and retrieves the underlying polarization parameters. The presented approach also successfully probes the polarization anisotropic effects in inhomogeneous media enabling a clear discrimination between the intrinsic
chiral optical response and
geometric phase effects arising from
spin orbit interaction of light in momentum resolved scattering. These results establish differential Mueller
matrix polarimetry as a powerful tool for rigorous characterization of polarization phenomena in nanostructured photonic systems and polarization engineered metasurfaces.
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Fluid Dynamics
A Surfactant Prediction Model for Rising Bubbles
Lim Chi Tung James, Ivo R. Peters and Swathi Krishna
Bubbles released from a needle show shape deformations that depend on the surfactant concentration of the surrounding
liquid. We develop a model that predicts the surfactant concentration based on experimental early-stage observations of these deformations. Using high-speed imaging, we examine bubbles within the first 144 ms of ascent, corresponding to a vertical rise distance of approximately 40 mm and extract the instantaneous aspect ratio (AR) and analyse its temporal
evolution. In clean conditions, bubbles exhibit pronounced shape oscillations resulting from the periodic exchange between surface and kinetic energy. The presence of surfactants leads to an immediate damping of these oscillations, characterised by reduced AR amplitudes and earlier peak deformations. This damping effect intensifies with increasing surfactant concentration until a near-saturation regime is reached, beyond which bubbles remain largely spherical and further increases in concentration produce indistinguishable AR profiles within the early-stage observation window. To develop the prediction model, an aspect-ratio-based analysis methodology is proposed, which yields an empirical relationship capable of estimating surfactant concentrations between 0 ppm and 2.9 ppm. We finally test the reliability of the model on unknown surfactant-laden bubbles. The model successfully detected the presence and relative extent of surfactant contamination as higher concentrations were introduced.
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Accelerator Physics · Cross-listed from cond-mat.supr-con
Resonance Frequency Shift Measurements of SRF Cavities at DESY
Rezvan Ghanbari, Thorsten Buettner, Wolfgang Hillert et al. (+10 more)
The variation of the resonance frequency and intrinsic quality factor of superconducting
radio-frequency cavities during the transition from the superconducting to the normal-conducting state provides essential insight into the fundamental superconducting properties of the cavity material. Investigating these transition dynamics is crucial for the continued advancement of niobium cavities whose near-surface regions are intentionally modified through the controlled introduction of interstitial atoms, such as oxygen and nitrogen, leading to the emergence of several novel behaviors whose underlying mechanisms are not yet fully understood. This work reports on the development and commissioning of a dedicated frequency-shift measurement setup. In its initial implementation, the system establishes a precise framework for determining the electron mean free path within both the superconducting penetration depth and the normal-conducting skin depth. It further enables investigation of an anomalous dip in the temperature dependence of the frequency shift near the critical temperature in cavities containing interstitial atoms in the near-surface
lattice, a novel phenomenon previously reported in the literature. A recent upgrade, currently in the final stage of validation, significantly improves measurement accuracy and reproducibility. The improved setup enables comprehensive studies of the frequency shift and quality factor over the full temperature range above 7 K, contributing to a deeper understanding of the superconducting properties.
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All authors Rezvan Ghanbari, Thorsten Buettner, Wolfgang Hillert, Karol Kasprzak, Tom Krokotsch, Ricardo Monroy-Villa, Detlef Reschke, Lea Steder, Alexey Sulimov, Hans Weise, Marc Wenskat, Mateusz Wiencek, Jonas Wolff
Plasma Physics
Scaling laws of multi-shock implosions toward the quasi-isentropic limit
M. Murakami
We present a unified theoretical and numerical framework for self-similar multi-shock implosions achieving ultrahigh compression in a uniform solid spherical target. Extending the classical Guderley model to N stacked, spherically converging shocks, we derive selfsimilar solutions and the scaling law for the final density. One dimensional Lagrangian hydrodynamic simulations confirm this relation over a broad range of parameters, from the weakly to the strongly nonlinear regime. The results show that cumulative compression increases systematically with the number of stacked shocks while
entropy generation is strongly suppressed, asymptotically approaching a quasi isentropic limit as N increases infinity. This volumetric scheme strongly suppresses the Rayleigh Taylor instability that plagues shell based implosions and thus provides a robust, largely instability-resistant compression pathway applicable to inertial confinement fusion and other high energy density systems. The framework bridges similarity theory with realistic multi-shock dynamics, guiding the design of advanced
laser-driven compression schemes.
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Applied Physics · Cross-listed from cond-mat.mes-hall
Pulse Shaping to Mitigate the Impact of Device Imperfections in Field-Free Switching Using Combined Spin-Orbit and Spin-Transfer Torques
Kuldeep Ray, Jérémie Vigier, Sylvain Martin et al. (+4 more)
Combining
spin-orbit (SOT) and
spin-transfer torques (STT) provides a practical approach for field-free switching in
spin-orbit torque
magnetic random-access
memory (SOT-MRAM), a prerequisite for industrial deployment, but can compromise reliability through phenomena such as backhopping, especially in top-pinned stacks commonly used for SOT-MRAM. We investigate the write error rate (WER) of combined SOT + STT switching in top-pinned devices that are not optimized for STT switching. Experiments reveal clear indications of STT-induced backhopping and a pronounced field-free SOT switching asymmetry between AP-to-P and P-to-AP transitions. Our macrospin model, using two coupled Landau Lifshitz Gilbert equations for the free and the reference layers, qualitatively reproduces this asymmetry and reveals an intermediate loss-of-determinism regime in addition to the well-known backhopping region. Based on these simulations, we propose mitigation strategies and experimentally demonstrate that STT pulse shaping reduces WER and improves switching robustness in the presence of device imperfections.
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All authors Kuldeep Ray, Jérémie Vigier, Sylvain Martin, Chloé Bouard, Nicolas Lefoulon, Marc Drouard, Gilles Gaudin