Atomic Physics · Cross-listed from quant-ph
Temporal Pulse Origins in Atom Interferometric Quantum Sensors
Jack Saywell, Nikolaos Dedes, Max Carey et al. (+2 more)
Quantum sensors based upon atom interferometry typically rely on
radio-frequency or optical pulses to coherently manipulate atomic states and make precise measurements of inertial and gravitational effects. An advantage of these sensors over their classical counterparts is often said to be that their measurement scale factor is precisely known and highly stable. However, in practice the finite pulse duration makes the sensor scale factor dependent upon the pulse shape and sensitive to variations in control field intensity, frequency, and atomic velocity. Here, we explore the concept of a temporal pulse origin in atom interferometry, where the inertial phase response of any pulse can be parameterized using a single point in time. We show that the temporal origin permits a simple determination of the measurement scale factor and its stability against environmental perturbations. Moreover, the temporal origin can be treated as a tunable parameter in the design of tailored sequences of shaped pulses to enhance scale factor stability and minimize systematic errors. We demonstrate through simulations that this approach to pulse design can reduce overall sequence durations while increasing robustness to realistic fluctuations in control field amplitude. Our results show that the temporal pulse origin explains a broad class of systematic errors in existing devices and enables the design of short, robust pulses which we expect will improve the performance of current and next-generation interferometric
quantum sensors.
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All authors Jack Saywell, Nikolaos Dedes, Max Carey, Brynle Barrett, Tim Freegarde
Medical Physics
Signal-to-noise and spatial resolution in in-line imaging. 3. Optimization using a simple model
T. E. Gureyev, D. M. Paganin and H. M. Quiney
The problem of optimization of propagation-based phase-contrast imaging setups is considered in the case of projection X-ray imaging and three-dimensional
tomography with phase
retrieval. For two-dimensional imaging, a simple model for a homogeneous edge feature embedded in a bulk sample is used to obtain analytical expressions for the image intensity. This model allows for explicit optimization of the geometrical parameters of the imaging setup and the choice of X-ray energy that maximizes the image contrast or the contrast-to-noise ratio. We also consider the question of optimization of the biomedical X-ray imaging quality characteristic which balances the contrast-to-noise against the spatial resolution and the radiation dose. In the three-dimensional case corresponding to propagation-based phase-contrast
tomography with phase
retrieval according to Paganin's method, the optimization of the imaging setup is studied with respect to the source size, the detector resolution, the geometrical magnification and the X-ray energy.
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Biological Physics · Cross-listed from quant-ph
Folding lattice proteins confined on minimal grids using a quantum-inspired encoding
Anders Irbäck, Lucas Knuthson and Sandipan Mohanty
Steric clashes pose a challenge when exploring dense
protein systems using conventional explicit-chain methods. A minimal example is a single
lattice protein confined on a minimal grid, with no free sites. Finding its minimum energy is a hard optimization problem, withsimilarities to scheduling problems. It can be recast as a quadratic unconstrained binary optimization (QUBO) problem amenable to classical and
quantum approaches. We show that this problem in its QUBO form can be swiftly and consistently solved for chain length 48, using either classical simulated annealing or hybrid
quantum-classical annealing on a D-Wave system. In fact, the latter computations required about 10 seconds. We also test linear and quadratic programming methods, which work well for a
lattice gas but struggle with chain constraints. All methods are benchmarked against exact results obtained from exhaustive structure enumeration, at a high computational cost.
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Instrumentation and Detectors · Cross-listed from astro-ph.IM
Cross-Polarization Reduction in Kinetic Inductance Detectors Based on Quasi-Lumped Resonators
Victor Rollano, Martino Calvo, Alejandro Pascual Laguna et al. (+7 more)
Kinetic Inductance Detectors (KIDs) have emerged as a leading technology for millimeter- and submillimeter-wave astronomy due to their high sensitivity, natural multiplexing capabilities and scalable fabrication. In polarization-sensitive applications-such as
Cosmic Microwave Background (CMB) studies-cross-polarization, or unintended response to the orthogonal polarization, poses a significant limitation to measurement fidelity. This work investigates the origin of cross-polarization in meandered Lumped Element KIDs (LEKIDs), with particular emphasis on the role of parasitic currents in the interdigitated capacitor. A comparative study between conventional LEKIDs and a quasi-lumped resonator design is presented, demonstrating that removing the capacitive element may improve cross-polarization discrimination, confirming the capacitor's contribution to polarization leakage.
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All authors Victor Rollano, Martino Calvo, Alejandro Pascual Laguna, David Rodriguez, Maria Teresa Magaz, Beatriz Aja, Luisa de la Fuente, Daniel Granados, Alessandro Monfardini, Alicia Gomez
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Enhancing the Efficiency of Time-Dependent Density Functional Theory Calculations of Dynamic Response Properties
Zhandos A. Moldabekov, Sebastian Schwalbe, Uwe Hernandez Acosta et al. (+4 more)
X-ray Thomson scattering (XRTS) constitutes an essential technique for diagnosing material properties under extreme conditions, such as high pressures and intense
laser heating. Time-dependent density functional theory (TDDFT) is one of the most accurate available ab initio methods for modeling XRTS spectra, as well as a host of other dynamic material properties. However, strong thermal excitations, along with the need to account for variations in temperature and density as well as the finite size of the detector significantly increase the computational cost of TDDFT simulations compared to ambient conditions. In this work, we present a broadly applicable method for optimizing and enhancing the efficiency of TDDFT calculations. Our approach is based on a one-to-one mapping between the dynamic structure factor and the imaginary time density–density correlation function, which naturally emerges in Feynman's path integral formulation of
quantum many-body theory. Specifically, we combine rigorous convergence tests in the imaginary time domain with a constraints-based attenuation of narrow-band fluctuations to improve the efficiency of TDDFT modeling without the introduction of any significant bias. As a result, we can report a speed-up by up to an order of magnitude, thus substantially reducing the burden of computational cost required for XRTS analysis.
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All authors Zhandos A. Moldabekov, Sebastian Schwalbe, Uwe Hernandez Acosta, Thomas Gawne, Jan Vorberger, Michele Pavanello, Tobias Dornheim
Biological Physics
In Situ Observation of Proton-Induced DNA Fragmentation in the Bragg Peak: Evidence for a Protective Role of Water
R.Liénard, P.Barberet, K.Chatzipapas et al. (+5 more)
We report in situ single-molecule measurements of
proton-induced double-strand breaks (DSBs) in DNA immersed in water, using real-time fluorescence tracking along the entire
proton path, including the Bragg peak region. By chemically suppressing radical-mediated processes, we isolate direct DNA damage mechanisms and determine DSB cross sections as a function of depth. Near the Bragg peak, we observe a tenfold reduction in DSB cross sections in aqueous DNA compared to dry DNA, providing quantitative evidence for the protective role of water. These findings highlight the importance of intermolecular energy dissipation in mitigating radiation-induced damage in condensed biological matter, with implications for radiobiology and
proton therapy modeling.
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All authors R.Liénard, P.Barberet, K.Chatzipapas, G.Devès, T.Dhôte, T.Guérin, H.Seznec, F.Gobet
Instrumentation and Detectors · Cross-listed from hep-ex
Machine Learning for Event Reconstruction in the CMS Phase-2 High Granularity Calorimeter Endcap
Théo Cuisset
The high-luminosity era of the LHC will offer greatly increased number of events for more precise Standard Model measurements and Beyond Standard Model searches, but will also pose unprecedented challenges to the detectors. To meet these challenges, the CMS detector will undergo several upgrades, including the replacement of the current endcap calorimeters with a novel High-Granularity Calorimeter (HGCAL). To make optimal use of this innovative detector, new and original
algorithms are being devised. A dedicated reconstruction framework, The Iterative Clustering (TICL), is being developed within the CMS Software (CMSSW). This new framework is designed to fully exploit the high spatial resolution and precise timing information provided by HGCAL. Several key ingredients of the object reconstruction chain already rely on Machine Learning (ML) techniques and their usage is expected to further develop in the future. The existing reconstruction strategies will be presented stressing the role played by ML techniques to exploit the information provided by the detector. The areas where ML techniques are expected to play a role in the future developments will be also discussed.
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Chemical Physics · Cross-listed from cond-mat.soft
Non-Gaussian Rotational Diffusion and Swing Motion of Dumbbell Probes in Two Dimensional Colloids
Jeongmin Kim, Taejin Kwon and Bong June Sung
Two dimensional (2D) colloids exhibit intriguing phase behaviors distinct from those in three dimensions, as well as dynamic heterogeneity reminiscent of glass-forming
liquids. Here, using discontinuous molecular dynamics simulations, we investigate the reporting dynamics of dicolloidal dumbbell probes in 2D colloids across the
liquid-hexatic phase transition, where hexagonal bond-orientational order (HBOO) extends to quasi-long-ranged one. The rotational dynamics of dumbbell probes faithfully capture the structural and dynamical features of the host: Brownian in the isotropic
liquid, and non-Gaussian in the hexatic and solid phases, reflecting both HBOO and dynamic heterogeneity of the medium. In the 2D hexatic and solid phases, probe rotation reflects heterogeneity as the dumbbells sample multiple dynamical domains of the host system: in mobile domains, they undergo rotational jumps of $\pi/3$ in accordance with HBOO, whereas in immobile domains they librate within cages formed by surrounding discs. Such non-Gaussianity disappears upon reentrant melting of the host medium driven by size polydispersity, highlighting a close connection between HBOO and probe dynamics. Furthermore, probe dynamics reveal both coupling (at a single particle level) and decoupling (at an ensemble-averaged level) between translation and rotation: swing motion emerges as their primary
diffusion mode, while the Debye-Stokes-Einstein relation breaks down regardless of how the rotational
diffusion coefficient is defined.
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Optics
Purcell-enhanced single-photon generation from CsPbBr$_3$ quantum dots in in-situ selected Laguerre-Gaussian modes
Virginia Oddi, Darius Urbonas, Etsuki Kobiyama et al. (+9 more)
Single
photons in Laguerre-Gaussian (LG) beams, which carry orbital angular momentum (OAM), could enable more robust and efficient photonic
quantum communication and information processing, as well as enhanced sensitivity in
quantum metrology and imaging. However, as most implementations are indirect or require additional mode-shaping elements, direct generation of single
photons with OAM has received growing interest. Colloidal lead halide perovskite
quantum dots (QDs) have recently emerged as a versatile material that can produce indistinguishable single
photons quasi-deterministically at high rate. Here, we integrate single CsPbBr$_3$ QDs into an open Fabry-Perot microcavity with a nanofabricated Gaussian-shaped deformation, demonstrating Purcell-enhanced single-
photon generation into individual cavity modes with up to 18.1 $\pm$ 0.2 times accelerated decay, down to tens of picoseconds. By in-situ tuning of the cavity resonance, we can selectively couple a single QD to different LG modes carrying OAM and observe the spatial patterns of the generated single-
photon beams emitted from the cavity. Our findings open the door to high
photon rate sources that directly generate single-
photon LG beams for advanced
quantum photonic applications.
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All authors Virginia Oddi, Darius Urbonas, Etsuki Kobiyama, Ioannis Georgakilas, Ihor Cherniukh, Kseniia Shcherbak, Chenglian Zhu, Maryna I. Bodnarchuk, Maksym V. Kovalenko, Rainer F. Mahrt, Gabriele Rainò, Thilo Stöferle
Instrumentation and Detectors
BabyMOSS stitched sensors: results of characterisation tests for ALICE ITS3 upgrade
Alessandro Sturniolo
During the Long Shutdown 3 (LS3, scheduled 2026-2030), the innermost 3 layers (Inner Barrel, or IB) of the present ALICE ITS2 will be replaced with large-area, flexible, stitched CMOS 65 nm sensors, arranged in 2 half-barrels of 3 half-layers each, in the framework of the ITS3 upgrade project. For the first time in a High Energy Physics experiment, such large-scale sensors will be bent into truly half-cylindrical shaped half-layers, requiring little mechanical support. This will also help lower the material budget: a reduction down to an average of 0.09% X$_{0}$ per layer is expected, benefitting ITS tracking and vertexing capabilities especially at low momenta. In the wafer yield and stitching assessment stage for ITS3 R&D, test devices from the Engineering Run 1 (ER1) submission were developed, including the MOnolithic Stiched Sensors (MOSS) and smaller variants of them (babyMOSS). In particular, babyMOSS is a single Repeated Sensor Unit (RSU) of a MOSS device: the chip is $\sim14\times30$ mm$^{2}$ in size, and consists of 8 digitally read out pixel
matrices (regions) arranged in 2 rows, i.e. half-units (HUs). BabyMOSS chip characterisation tests have been performed in laboratory and test beam environments. Laboratory tests include systematic functional scans to study the behaviour of front-end electronics over a range of different settings, whereas test beam measurements, under high-energy charged particle beams, were used to investigate the detection efficiency and spatial resolution. In this contribution, we will present the babyMOSS chip characterisation campaign, with a focus on recent test beam results. So far, babyMOSS test beam results have been consistent with full MOSS, and confirmed that babyMOSS devices meet the ITS3 requirements: a detection efficiency $>99\%$, fake hit rate $<10^{-6}$ hits per pixel and event, and a spatial resolution $<6$ $\mu$m.
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Optics
Topological Hall effect in nonlinear optics
Soumik Nandi, Arannya Ghosh, Ashok K Mohapatra et al. (+1 more)
We present an experimental evidence of topological
Hall-effect in an all-optical third-order nonlinear optical process via spatial
symmetry-breaking in pseudo-
spin textures created by a spatially-structured pump
laser beam. The experimental configuration consists of a moderately-focused pump
laser beam undergoing a parametric interaction with an organic solvent (toluene) and an off-resonant
laser beam probes the non-trivial spatial magnetization textures created by the pump beam. The phase-profile of the transmitted probe beam is extracted using phase-
retrieval algorithms for ascertaining the topological charge which is shown to be consistent with the estimation of Berry's
curvature that we obtain via paraxial approximation-based modeling of third-order nonlinear interaction.
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All authors Soumik Nandi, Arannya Ghosh, Ashok K Mohapatra, Ritwick Das
Accelerator Physics · Cross-listed from quant-ph
Three-Dimensional Niobium Coaxial Cavity with $\sim0.1\,$second Lifetime
Takaaki Takenaka, Takayuki Kubo, Imran Mahboob et al. (+4 more)
We report on the internal quality factor of a three-dimensional niobium quarter-wave coaxial cavity, with mid-temperature annealing, exhibiting $Q_{\rm int} \gtrsim 3\times10^9$ at the single-
photon level below 20\,mK, which corresponds to an internal
photon lifetime of $\tau_{\rm int}\sim90\,\mathrm{ms}$. Moreover, $Q_{\rm int}$ of the mid-temperature annealed cavities remains almost unchanged even after several cooldown cycles and air exposure. These results suggest that stable low-loss niobium
oxides might be formed by mid-temperature annealing on the surface of three-dimensional niobium cavity. This surface treatment could be applicable to the fabrication of 2D superconducting
circuits and help improve the lifetime of Nb-based superconducting
qubits.
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All authors Takaaki Takenaka, Takayuki Kubo, Imran Mahboob, Kosuke Mizuno, Hitoshi Inoue, Takayuki Saeki, Shiro Saito
Biological Physics · Cross-listed from q-bio.PE
Optimization of sequential therapies to maximize extinction of resistant bacteria through collateral sensitivity
Javier Molina-Hernández, José A. Cuesta, Beatriz Pascual-Escudero et al. (+2 more)
Antimicrobial resistance (AMR) threatens global health. A promising and underexplored strategy to tackle this problem is sequential therapies exploiting collateral sensitivity (CS), whereby resistance to one drug increases sensitivity to another. Here, we develop a four-genotype
stochastic birth-death model with two bacteriostatic antibiotics to identify switching periods that maximize bacterial extinction under subinhibitory concentrations. We show that extinction probability depends nonlinearly on switching period, with stepwise increases aligned to discrete switch events: fast sequential therapies are suboptimal as they do not allow for the
evolution of resistance, a key ingredient in these therapies. A
geometric distribution framework accurately predicts cumulative extinction probabilities, where the per-switch extinction probability rises with switching period. We further derive a heuristic approximation for the extinction probability based on times to fixation of single-resistant mutants. Sensitivity analyses reveal that strong reciprocal CS is required for this strategy to work, and we explore how increasing antibiotic doses and higher mutation rates modulate extinction in a nonmonotonic manner. Finally, we discuss how longer therapies maximize extinction but also cause higher resistance, leading to a Pareto front of optimal switching periods. Our results provide quantitative design principles for in vitro and clinical sequential antibiotic therapies, underscoring the potential of CS-guided regimens to suppress resistance
evolution and eradicate infections.
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All authors Javier Molina-Hernández, José A. Cuesta, Beatriz Pascual-Escudero, Saúl Ares, Pablo Catalán
Space Physics · Cross-listed from astro-ph.SR
PRESOL: a web-based computational setting for feature-based flare forecasting
Chiara Curletto, Paolo Massa, Valeria Tagliafico et al. (+4 more)
Solar flares are the most explosive phenomena in the
solar system and the main trigger of the events' chain that starts from Coronal Mass Ejections and leads to geomagnetic storms with possible impacts on the infrastructures at Earth. Data-driven
solar flare forecasting relies on either deep learning approaches, which are operationally promising but with a low explainability degree, or machine learning
algorithms, which can provide information on the physical descriptors that mostly impact the prediction. This paper describes a web-based technological platform for the execution of a computational pipeline of feature-based machine learning methods that provide predictions of the
flare occurrence, feature ranking information, and assessment of the prediction performances.
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All authors Chiara Curletto, Paolo Massa, Valeria Tagliafico, Cristina Campi, Federico Benvenuto, Michele Piana, Andrea Tacchino
Applied Physics · Cross-listed from stat.ME
Optimal smoothing parameter in Eilers-Whittaker smoother
Roberto Bernal-Arencibia, Karel Garcia Medina, Ernesto Estevez-Rams et al. (+1 more)
The Eilers-Whittaker method for data smoothing effectiveness depends on the choice of the regularisation parameter, and automatic selection is a necessity for large
datasets. Common methods, such as leave-one-out cross-validation, can perform poorly when serially correlated noise is present. We propose a novel procedure for selecting the control parameter based on the spectral
entropy of the residuals. We define an S-curve from the Euclidean distance between points in a plot of the spectral
entropy of the residuals versus that of the smoothed signal. The regularisation parameter corresponding to the absolute maximum of this S-curve is chosen as the optimal parameter. Using simulated data, we benchmarked our method against cross-validation and the V-curve. Validation was also performed on diverse experimental data. This robust and straightforward procedure can be a valuable addition to the available selection methods for the Eilers smoother.
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All authors Roberto Bernal-Arencibia, Karel Garcia Medina, Ernesto Estevez-Rams, Beatriz Aragon-Fernandez
Applied Physics
Experimental Investigation of Skew Wind Effects on Vortex-Induced Vibration of Typical Bridge Decks
Guangzhong Gao, Pengwei Zhang, Wenkai Du et al. (+3 more)
This study explores the skew wind effects on
vortex-induced vibration (VIV) of two typical bridge decks-a closed-box girder and a twin-edge girder-through spring-suspended oblique section model tests. Experiments were conducted at various wind yaw angles and angles of attack. Results indicate that VIV amplitudes and lock-in ranges exhibit a clear variation with yaw angles, rendering the Independence Principle (IP) unsuitable for these configurations. A heave-torsion coupling phenomenon was observed in both heaving and torsional VIV, attributed to the eccentricity of the center of
gravity due to asymmetric end segments. A novel numerical
algorithm was introduced to correct peak VIV amplitudes for variations in structural mass-damping parameters across yaw angles. The most unfavorable VIV responses occurred under skew wind conditions, with maximum amplitudes increasing by approximately 20.1 percent for heaving VIV and 179.8 percent for torsional VIV in the closed-box girder, and by 3.9 percent for heaving VIV in the twin-edge girder, relative to normal wind conditions.
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All authors Guangzhong Gao, Pengwei Zhang, Wenkai Du, Yonghui Xie, Pengjie Ren, Xiaofeng Xue
Optics
Doubling the field of view and eliminating the replica overlap problem in common-path shearing quantitative phase imaging
Mikołaj Rogalski, Piotr Zdańkowski, Matyas Heto et al. (+6 more)
Quantitative phase imaging (QPI) enables label-free, high-contrast visualization of transparent specimens, but its common implementation in off-axis digital
holographic microscopy (DHM) requires a separate reference beam, which increases system complexity and sensitivity to noise and vibrations. Common-path shearing DHMs overcome these drawbacks by eliminating the reference arm, yet they suffer from sheared object beam (replica) overlap, as both interfering sheared beams traverse the sample and generate superimposed phase images. This limits their use to sparse objects only. Here we introduce R2D-QPI, a method that numerically decouples object and replica fields of view through controlled shear scanning. The method analytically separates overlapped phase images and effectively doubles the imaged area, requiring only two measurements. We experimentally validate the approach on a phase resolution test target, yeast
cells, and human thyroid tissue slices, demonstrating accurate reconstruction even in highly confluent samples with strong object-replica overlap. The results establish R2D-QPI as a robust and versatile solution for common-path QPI, enabling wide-field, label-free phase imaging with minimal data acquisition and strong potential for applications in biological and medical microscopy.
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All authors Mikołaj Rogalski, Piotr Zdańkowski, Matyas Heto, Jolanta Mierzejewska, Małgorzata Lenarcik, Zhuoshi Li, Jiasong Sun, Chao Zuo, Maciej Trusiak
Optics · Cross-listed from cond-mat.mtrl-sci
Giant enhancement of terahertz high-harmonic generation by cavity engineering of a three-dimensional Dirac semimetal
Siyu Duan, Lili Shi, Patrick Pilch et al. (+7 more)
We report on time-resolved ultrafast terahertz high-harmonic generation of strong field driven-dynamics of many-body Dirac
fermions. We demonstrate an experimental realization of near saturation regime of the high-order nonlinear responses with a
giant enhancement of terahertz third- and fifth-order harmonic yields by cavity-engineering a three-dimensional Dirac semimetal Cd3As2. By fabricating a designed structure of metasurface microcavities on a nanometer Cd3As2 thin film, we significantly enhance the near-field intensity of a picosecond terahertz excitation pulse in resonance with the microcavity eigenmode. The strong terahertz field drives the far-from-
equilibrium Dirac
fermions deeply into a nonperturbative regime, leading to the observation of near-saturation high-harmonic emission. Our experimental results confirm the predictions by Boltzmann transport theory, and substantiate a field-driven kinetic description of the strong nonthermal nonlinearity at the terahertz frequencies.
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All authors Siyu Duan, Lili Shi, Patrick Pilch, Anneke Reinold, Sergey Kovalev, Renato M. A. Dantas, Yunkun Yang, Faxian Xiu, Miriam Serena Vitiello, Zhe Wang
Physics and Society · Cross-listed from cs.CY
Framing Unionization on Facebook: Communication around Representation Elections in the United States
Arianna Pera, Veronica Jude, Ceren Budak et al. (+1 more)
Digital media have become central to how labor unions communicate, organize, and sustain collective action. Yet little is known about how unions' online discourse relates to concrete outcomes such as representation elections. This study addresses the gap by combining National Labor Relations Board (NLRB) election data with 158k Facebook posts published by U.S. labor unions between 2015 and 2024. We focused on five discourse frames widely recognized in labor and social movement communication research: diagnostic (identifying problems), prognostic (proposing solutions), motivational (mobilizing action), community (emphasizing solidarity), and engagement (promoting social media interaction). Using a fine-tuned RoBERTa classifier, we systematically annotated unions' posts and analyzed patterns of frame usage around election events. Our findings showed that diagnostic and community frames dominated union communication overall, but that frame usage varied substantially across organizations. Greater use of diagnostic, prognostic, and community frames prior to an election was associated with higher odds of a successful outcome. After elections, framing patterns diverged depending on results: after wins, the use of prognostic and motivational frames decreased, whereas after losses, the use of prognostic and engagement frames increased. By examining variation in message-level framing, the study highlights how communication strategies correlate with organizational success, contributing open tools and data, and complementing prior research in understanding digital communication of unions and social movements.
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All authors Arianna Pera, Veronica Jude, Ceren Budak, Luca Maria Aiello
Optics
Towards Photonic Band Diagram Generation with Transformer-Latent Diffusion Models
Valentin Delchevalerie, Nicolas Roy, Arnaud Bougaham et al. (+3 more)
Photonic
crystals enable fine control over light propagation at the nanoscale, and thus play a central role in the development of photonic and
quantum technologies. Photonic band diagrams (BDs) are a key tool to investigate light propagation into such inhomogeneous structured materials. However, computing BDs requires solving Maxwell's equations across many configurations, making it numerically expensive, especially when embedded in optimization loops for inverse design techniques, for example. To address this challenge, we introduce the first approach for BD generation based on
diffusion models, with the capacity to later generalize and scale to arbitrary three dimensional structures. Our method couples a
transformer encoder, which extracts contextual
embeddings from the input structure, with a latent
diffusion model to generate the corresponding BD. In addition, we provide insights into why
transformers and
diffusion models are well suited to capture the complex interference and scattering phenomena inherent to photonics, paving the way for new surrogate modeling strategies in this domain.
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All authors Valentin Delchevalerie, Nicolas Roy, Arnaud Bougaham, Alexandre Mayer, Benoît Frénay, Michaël Lobet
Classical Physics
Multi-scale friction coefficient: From roughness to system computation using deep learning
Victor Lalleman, Pierre Gosselet, Cédric Hubert et al. (+2 more)
The presence of surface defects (roughness, surface imperfections, profiles, etc.) in a contact inevitably leads to the modification of its local properties, such as the coefficient of friction. In railway wheelsets, this surface condition is crucial as it dictates appropriate fatigue design for the final use. However, these local phenomena are not well understood and require a real step back. Therefore, the aim of this paper is to propose a multiscale numerical strategy to better understand these phenomena. The multiscale strategy is divided into two steps. Initially, an analysis by the Discrete Element Method (DEM) modelling the interaction of generated rough surfaces is carried out to determine the coefficient of friction. In a second step, the results of DEM are introduced into a structural calculation where the enrichment of the coefficient of friction is done on each finite element contact. Given the wide variety of potential surface defects (size, distribution, height, etc.), a large number of DEM simulations is performed. A specially developed deep learning program is then used to account for these dispersions. The application targeted in this paper is the fitting of a wheel on a railway axle.
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All authors Victor Lalleman, Pierre Gosselet, Cédric Hubert, Stéphane Salengro, Vincent Magnier
Geophysics
High-resolution velocity model estimation with neural operator and the time-shift imaging condition
Xiao Ma, Shaowen Wang and Tariq Alkhalifah
Extracting subsurface velocity information from seismic data is mainly an undetermined problem that requires injecting a priori information to constrain the inversion process. Machine learning has offered a platform to do so through the training process, as we formulate our training
dataset to inject as much prior knowledge as possible in the trained ML model. Here, we use a neural-operator-based framework for high-resolution seismic velocity model building, which integrates Neural Operators with time-lag reverse time migration imaging. Unlike conventional full waveform inversion (FWI) methods that rely on iterative forward and adjoint-state computations, our approach learns a direct mapping from initial velocity models and extended seismic images to high-resolution velocity estimates through supervised learning. The network architecture enables mesh-independent generalization by learning mappings in infinite-dimensional function spaces, while synthetic velocity models and time-lag reverse time migration (RTM) images provide complementary high-frequency information critical for recovering mid- and high-wavenumber velocity components. Synthetic experiments demonstrate that the proposed method accurately reconstructs fine-scale structures and complex geologies, including out-of-distribution features such as salt bodies. Applications to real seismic field data acquired offshore Australia further validate the method's robustness and resolution capability. The predicted models show enhanced structural details and improved consistency with well-log data, outperforming traditional multi-scale FWI in both accuracy and computational efficiency. The entire prediction process is completed within seconds, making the proposed approach highly suitable for rapid and scalable velocity model building in practical exploration scenarios.
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Optics · Cross-listed from quant-ph
Extracting the photon indistinguishability error from measurable quantum observables
Franciscus H. B. Somhorst, Jason Saied, Eleanor G. Rieffel et al. (+1 more)
We present a method to extract the
photon indistinguishability error from Hong-Ou-Mandel interference measurements, accounting for the combined effects of loss and multiphoton noise that contaminate the single-
photon Hilbert space. Our analysis resolves apparent inconsistencies in previous interpretations of such measurements. The reported method applies to a wide range of single-
photon sources, including
quantum dots.
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All authors Franciscus H. B. Somhorst, Jason Saied, Eleanor G. Rieffel, Jelmer J. Renema
Geophysics
On the inverse problem of the earthquake source and the three-phase relaxation mode of the source after the formation of a main rupture in it
A.V. Guglielmi
The fundamentals of the phenomenological theory of aftershocks are presented. The theory contains an original concept of the proper time of the earthquake source, the course of which, generally speaking, differs from the course of world time. Within the framework of the theory, a new method for processing and analyzing earthquakes has been developed. Analysis of the Tohoku earthquake demonstrated the effectiveness of the method. Three phases of relaxation of the source were discovered. In the initial phase, the deactivation coefficient, which characterizes the source as a dynamic system, is equal to zero. At the end of the initial phase, the deactivation coefficient suddenly acquires a positive value, which remains unchanged throughout the main relaxation phase. The transition from the main phase to the recovery phase is accompanied by a jump in the time derivative of the deactivation coefficient. The recovery phase differs from the initial and main phases by chaotic variations in the deactivation coefficient. Keywords: dynamic system, deactivation coefficient, proper time. synchronization, foreshocks, mainshock, aftershocks.
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Fluid Dynamics
Fluid Deformation in Random Unsteady Flow
Daniel Lester and Marco Dentz
Fluid deformation controls myriad processes in random flows including mixing and dispersion, stress development in complex fluids, colloid transport and deposition, droplet breakup and emulsification, fluid-structure interaction, chemical reactions and biological activity. Despite this, fundamental aspects are not well understood, including the link between the Lagrangian velocity gradient tensor $\boldsymbol\epsilon$ and deformation measures such as Lyapunov exponents ($\lambda_{\infty,i}$), their finite-time counterparts (FTLEs) and the right Cauchy-Green tensor $\mathbf{C}$. We address these knowledge gaps by developing an ab initio
stochastic model of fluid deformation in ergodic and stationary random unsteady flows. We show that although the Lagrangian velocity process is non-Markovian and non-Fickian, temporal decorrelation in unsteady random flows results in Fickian
evolution of $\boldsymbol\epsilon$. Application of an objective coordinate transform renders $\boldsymbol\epsilon^\prime$ upper triangular, the basis vectors of which exponentially converge to Lyapunov vectors. As such, the diagonal components of $\boldsymbol\epsilon^\prime$ correspond to increments of the Lyapunov spectra, while the off-diagonal components objectively quantify shear and vorticity. This leads to a
stochastic model of Lagrangian fluid deformation as a simple Brownian process that provides a direct link between $\boldsymbol\epsilon^\prime$ and fluid deformation. We develop closed-form expressions for the
evolution of $\mathbf{C}$ and the FTLEs, and apply the
stochastic model to numerical results for a model 2D unsteady flow and 3D forced homogeneous isotropic
turbulence, returning excellent agreement with direct calculations of deformation measures.
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Chemical Physics
Theoretical investigation of real-fluid effects on the oxidation of hydrogen and syngas in high-pressure flow reactors
Mingrui Wang, Tianzhou Jiang, Ting Zhang et al. (+5 more)
Investigating the high-pressure pyrolysis and oxidation of hydrogen and syngas is essential for developing accurate combustion models under real engine conditions. Accordingly, flow reactors have been increasingly used in these fundamental combustion research at high-pressure conditions to achieve chemical kinetic modeling. However, these previous chemical kinetic modeling for pyrolysis and oxidation has almost been completely conducted based on ideal gas assumption, which might fail at high-pressure conditions when real-fluid behaviors become pronounced. Elucidating whether this is the case is urgent given the high demand for high-pressure combustion and propulsion technologies. Toward this, this study establishes a first-of-its-kind real-fluid modelling framework for high-pressure flow reactors, where the physical molecular interactions in real fluids are represented via coupling ab initio intermolecular potentials with high-order Virial equation of state and further with real-fluid thermochemistry, real-fluid chemical
equilibrium, and real-fluid conservation laws of species, mass, and momentum. Using the developed framework, real-fluid effects in high-pressure flow reactors are quantified through case studies of hydrogen and syngas oxidation, covering pressure of 10-500 bar, temperature of 601-946 K, equivalence ratio of 0.0009-12.07, and dilution ratio of 5.9%-99.5%. The results reveal the strong real-fluid effects in high-pressure flow reactors, where ignoring them can lead to considerable errors in the simulated mole fractions, which are higher than typical levels of measurements uncertainty in flow reactors. These errors can lead to misinterpretation of the fundamental oxidation chemistry in high-pressure flow reactors and pose significant errors in the developed chemistry models, which should be adequately accounted for in future high-pressure flow reactor studies.
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All authors Mingrui Wang, Tianzhou Jiang, Ting Zhang, Hongjie Zhang, Hongqing Wu, Rongpei Jiang, Yang Li, Song Cheng
Applied Physics
Tensegrity structures and data-driven analysis for 3d cell mechanics
Ziran Zhou, Jacinto Ulloa, Guruswami Ravichandran et al. (+1 more)
The cytoskeleton (CSK) plays an important role in many
cell functions. Given the similarities between the mechanical behavior of tensegrity structures and the CSK, many studies have proposed different tensegrity-based models for simulating
cell mechanics. However, the low
symmetry of most tensegrity units has hindered the analysis of realistic 3D structures. As a result, tensegrity-based modeling in
cell mechanics has been mainly focused on single
cells or monolayers. In this paper, we propose a 3D tensegrity model based on the finite element method for simulating 3D
cell mechanics. We show that the proposed model not only captures the nonlinearity of a single
cell in an indentation test and a monolayer in stretch test but also the non-uniform stress distribution in multicellular spheroids upon non-uniform prestress design. Furthermore, we introduce a multiscale data-driven framework for cellular mechanics to optimize the computation, thus paving the way for modeling the mechanobiology of large cellular assemblies such as organs.
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All authors Ziran Zhou, Jacinto Ulloa, Guruswami Ravichandran, Jose E. Andrade
Data Analysis and Statistics · Cross-listed from cs.LG
Securing generative artificial intelligence with parallel magnetic tunnel junction true randomness
Youwei Bao, Shuhan Yang and Hyunsoo Yang
Deterministic pseudo random number generators (PRNGs) used in generative artificial intelligence (GAI) models produce predictable patterns vulnerable to exploitation by attackers. Conventional defences against the vulnerabilities often come with significant energy and latency overhead. Here, we embed hardware-generated true random bits from
spin-transfer torque
magnetic tunnel junctions (STT-MTJs) to address the challenges. A highly parallel, FPGA-assisted prototype computing system delivers megabit-per-second true random numbers, passing NIST randomness tests after in-situ operations with minimal overhead. Integrating the hardware random bits into a generative
adversarial network (GAN) trained on CIFAR-10 reduces insecure outputs by up to 18.6 times compared to the low-quality random number generators (RNG) baseline. With nanosecond switching speed, high energy efficiency, and established scalability, our STT-MTJ-based system holds the potential to scale beyond 106 parallel
cells, achieving gigabit-per-second throughput suitable for large
language model sampling. This advancement highlights spintronic RNGs as practical security components for next-generation GAI systems.
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Optics
Broadband entangled-photon omni-resonance in a planar optical cavity
Bryan L. Turo, Layton A. Hall, Bahaa E. A. Saleh et al. (+1 more)
Resonant field enhancement in an optical cavity is a promising pathway towards realizing optical nonlinearities at the few-
photon level. This quest is hampered by inevitable narrowing of the resonant linewidth as the cavity finesse is increased, which necessitates striking a compromise between the magnitude of the field enhancement and the bandwidth over which it is harnessed. This difficulty is exacerbated for broadband entangled-
photon pairs, which are typically frequency-anticorrelated, so that the two
photons cannot be simultaneously admitted to a cavity except when the degenerate wavelength coincides with a cavity resonance. Here we show that introducing judicious angular dispersion into single-
photon and entangled-
photon states before incidence on a planar Fabry-Pérot (FP) cavity renders these non-classical fields omni-resonant: the entire spectrum is coupled to a single longitudinal cavity mode. Making use of a planar FP cavity of finesse $\approx100$, resonant linewidth $\approx0.3$~nm, and free spectral range $\approx22$~nm in the near-infrared, we couple single-
photon states and frequency-anticorrelated entangled-
photon states of 20-nm bandwidth to a broadband achromatic resonance associated with a single underlying narrowband longitudinal FP-cavity mode – thereby preserving the entangled spectral structure. In general, pre-conditioning the optical field by introducing angular dispersion enables coupling non-classical states of light to a single longitudinal cavity mode, even if the field bandwidth far exceeds the resonant linewidth, or even exceeds the cavity free-spectral-range. These results pave the way to broadband resonant interactions with non-classical states of light in
photon-starved applications.
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All authors Bryan L. Turo, Layton A. Hall, Bahaa E. A. Saleh, Ayman F. Abouraddy
Plasma Physics
Suppression of inverse magnetic energy transfer in collisionless marginally magnetized plasmas
Zhuo Liu, Muni Zhou and Nuno F.G. Loureiro
We investigate the inverse cascade of
magnetic energy in decaying, collisionless
plasmas with moderate to high-$\beta$ values via first-principles numerical simulations and analytical theory. We find that pressure-anisotropy-driven instabilities, in particular the firehose instability, suppress reconnection-driven coalescence of
magnetic structures (i.e., inverse transfer) by nullifying
magnetic tension. This suppression leaves such structures elongated and confined to scales comparable to the Larmor radius of the particles. The presence of a
magnetic guide field of sufficient strength, or a greater scale separation between the initial size of the
magnetic structures and the Larmor radius, restores the system's ability to inverse transfer
magnetic energy. These results reveal that inverse energy transfer in collisionless
plasmas is not guaranteed, but instead sensitively depends on magnetization. In the astrophysical context, this identifies a kinetic mechanism by which Weibel-generated seed fields may fail to merge consistently, potentially limiting their role in
cosmic magnetogenesis.
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