Biological Physics · Cross-listed from q-bio.QM
Quantum Generative Modeling of Single-Cell transcriptomes: Capturing Gene-Gene and Cell-Cell Interactions
Selim Romero, Vignesh S. Kumar, Robert S. Chapkin et al. (+1 more)
Single-
cell RNA sequencing (scRNA-seq) data simulation is limited by classical methods relying on linear correlations, failing to capture nonlinear dependencies. No existing simulator jointly models gene-gene regulatory interactions and
cell-
cell communication. We introduce qSimCells, a
quantum computing-based simulator that uses
entanglement to model intra- and inter-cellular interactions, generating realistic single-
cell transcriptomic data from heterogeneous
cell populations. Its
quantum kernel uses a parameterized
circuit with CNOT gates to encode gene regulatory networks (GRNs) and
cell-
cell communication
topologies. By programming the
entanglement architecture, the simulator establishes a known generative ground truth for both regulatory and communication pathways. The resulting synthetic data exhibits dependencies arising from the joint probability structure of the
quantum circuit. Notably, standard correlation-based analyses (Pearson and Spearman) fail to recover the programmed causal relationships and instead report spurious associations driven by high baseline gene-expression probabilities. Applying
cell-
cell communication detection serves as an internal consistency check: CellChat correctly identifies the true ligand-receptor pairs when inter-state
entanglement is active, revealing a robust, up to ~98-fold relative increase in inferred communication probability. These results demonstrate that the
quantum kernel produces high-fidelity
benchmark datasets with known ground truth, highlighting the limitations of correlation-based inference and the need for approaches capable of capturing complex structural dependencies underlying gene regulation and
cell-
cell communication.
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All authors Selim Romero, Vignesh S. Kumar, Robert S. Chapkin, James J. Cai
Computational Physics · Cross-listed from cond-mat.mes-hall
plasmonX: an Open-Source Code for Nanoplasmonics
Tommaso Giovannini, Pablo Grobas Illobre, Piero Lafiosca et al. (+4 more)
We present the first public release of plasmonX, a novel open-source code for simulating the plasmonic response of complex nanostructures. The code supports both fully atomistic and implicit descriptions of nanomaterials. In particular, it employs the frequency-dependent fluctuating charges ($\omega$FQ) and dipoles ($\omega$FQF$\mu$) models to describe the response properties of atomistic structures, including simple and $d$-metals,
graphene-based structures, and multi-metal nanostructures. For implicit representations, the Boundary Element Method is implemented in both the dielectric polarizable continuum model (DPCM) and integral equation formalism (IEF-PCM) variants. The distribution also includes a post-processing module that enables analysis of electric field-induced properties such as charge density and electric field patterns.
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All authors Tommaso Giovannini, Pablo Grobas Illobre, Piero Lafiosca, Luca Nicoli, Luca Bonatti, Stefano Corni, Chiara Cappelli
Medical Physics
Artificial intelligence for simplified patient-centered dosimetry in radiopharmaceutical therapies
Alejandro Lopez-Montes, Fereshteh Yousefirizi, Yizhou Chen et al. (+8 more)
KEY WORDS: Artificial Intelligence (AI), Theranostics, Dosimetry, Radiopharmaceutical Therapy (RPT), Patient-friendly dosimetry KEY POINTS - The rapid
evolution of radiopharmaceutical therapy (RPT) highlights the growing need for personalized and patient-centered dosimetry. - Artificial Intelligence (AI) offers solutions to the key limitations in current dosimetry calculations. - The main advances on AI for simplified dosimetry toward patient-friendly RPT are reviewed. - Future directions on the role of AI in RPT dosimetry are discussed.
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All authors Alejandro Lopez-Montes, Fereshteh Yousefirizi, Yizhou Chen, Yazdan Salimi, Robert Seifert, Ali Afshar-Oromieh, Carlos Uribe, Axel Rominger, Habib Zaidi, Arman Rahmim, Kuangyu Shi
Optics
Supercontinuum Generation in 1-decanol
Nathan G. Drouillard and TJ Hammond
Although solids have been recently used in ultrafast experiments for spectral broadening due to their relatively high nonlinearity, their sensitivity to damage limits their long-term stability.
Liquids are a possible alternative to solids as a nonlinear medium because of their comparable nonlinearity and resistance to permanent damage. We generate a supercontinuum in 1-decanol that spans more than an octave from the visible to the near-infrared regime. We measure the nonlinear index of refraction of 1-decanol and find a significant $n_4$ contribution. This contribution leads to a nonlinearity comparable to CS$_2$ (a frequent reference for nonlinear optics) in high-intensity regimes while being significantly less volatile and toxic. We find this supercontinuum spectrum to be stable for at least 30 minutes.
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Physics and Society
Modeling Epidemics on Multiplex Networks: Epidemic Threshold and Basic Reproduction Number
Eric Alejandro Rozan, Mario Ignacio Simoy, Sebastian Bouzat et al. (+1 more)
Accurate epidemic
forecasting requires models that account for the layered and heterogeneous nature of real social interactions. The basic reproduction number $\mathcal R_0$, as calculated from models that assume homogeneous mixing or single-layer contact structures, has limited applicability to complex social systems. Here, we derive an expression for $\mathcal R_0$ in the context of multiplex networks, enabling the analysis of disease transmission across multiple social layers. We adapt the Degree-Based Mean-Field (DBMF) SIR model for single-layer complex networks to the multiplex setting, where each layer is characterized by its own degree distribution and infection rate. Using the Next Generation
Matrix method, we derive an analytical expression for the basic reproduction number $\mathcal R_0$. Numerical integration of the multiplex DBMF equations shows that $\mathcal R_0=1$ marks the epidemic threshold and governs the behavior of key outbreak indicators as expected. In addition to the exact expression for $\mathcal R_0$, we introduce an approximation, denoted by $\tau$, which is simpler to compute and admits a more transparent interpretation in terms of the epidemiological and topological parameters of the system.
Stochastic agent-based simulations support these findings, demonstrating a direct correspondence between $\tau$ and the average number of secondary infections generated during the early stages of an outbreak, consistent with the epidemiological interpretation of $\mathcal R_0$. This work provides a robust generalization of $\mathcal R_0$ for layered contact structures, offering a more realistic basis for epidemic
forecasting and the design of intervention strategies.
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All authors Eric Alejandro Rozan, Mario Ignacio Simoy, Sebastian Bouzat, Marcelo Nestor Kuperman
Medical Physics
Quasi-static in vivo elastography from internal displacement information only
David G.J. Heesterbeek, Max H.C. van Riel, Ray S.S. Sheombarsing et al. (+4 more)
As disease often alters the structural properties of soft tissue, noninvasive elastography techniques have emerged to quantitatively assess in vivo mechanical properties.
Magnetic Resonance Elastography (MRE) based on dynamic deformations is the standard technique for imaging mechanical properties, but the viscoelastic nature of soft tissue makes the results dependent on the actuation frequency, which can be limiting. In this proof-of-principle study we propose a noise robust framework for reconstructing relative stiffness properties from quasi-static in vivo displacement fields captured on a physiological time scale. The acquisition is performed using a pneumatic pressure cuff to induce tissue deformation in a controlled manner. The reconstruction does not require boundary information which is generally hard to access in vivo nor spatial derivatives of displacement fields that are known to amplify noise. The validity of our framework is corroborated with in silico experiments on a numerical phantom. In vivo experiments on the thigh of a volunteer demonstrate the repeatability of the method. As an application, the quantitative change in muscle stiffness during isometric knee flexion is investigated which yielded physiologically meaningful results.
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All authors David G.J. Heesterbeek, Max H.C. van Riel, Ray S.S. Sheombarsing, Tristan van Leeuwen, Martijn Froeling, Cornelis A.T. van den Berg, Alessandro Sbrizzi
Fluid Dynamics
Pressure drop-flow rate nonlinearity in bubble trains through a capillary bundle
Paolo Botticini, Davide Picchi, Santanu Sinha et al. (+1 more)
We investigate the effective rheology of a train of elongated bubbles of negligible viscosity flowing in capillary tubes. Building upon the classical Bretherton theory for a single bubble, we extend the analysis to a train of bubbles in a single capillary tube and finally to an array of parallel, noninteracting capillary tubes, i.e., a capillary bundle. Our goal is to characterize the nonlinear pressure drop-flow rate relation of this simplified two-phase system by incorporating the thin-film hydrodynamics at small capillary numbers. We model the structural heterogeneity of the bundle by assuming that the tube radii follow a truncated power-law distribution and examine deviations of the system from the Darcy law in terms of both its statistical properties and the parameters characterizing the bubble train (i.e., the tube slenderness ratio, the volume fraction, and the number of bubbles). The main result is that two-phase flow alters the effective rheology, leading to deviations from Darcy-type behavior across the entire parameter space investigated. Specifically, for a limited number of bubbles, the flow exhibits a smooth transition from the Bretherton regime, where the pressure drop scales with the flow rate to the power of 2/3, to weaker sublinear regimes with exponents between 2/3 and unity. Interestingly, increasing the number of bubbles or narrowing the pore-size distribution leads to only minor deviations from the Bretherton regime. The resulting pressure drop-flow rate exponents are qualitatively similar to those reported in the literature for immiscible two-phase flow in porous media, despite the inherent simplicity of the capillary bundle model.
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All authors Paolo Botticini, Davide Picchi, Santanu Sinha, Alex Hansen
Biological Physics · Cross-listed from q-bio.MN
ECMSim: A high-performance interactive web application for real-time spatiotemporal simulation of cardiac ECM signaling and diffusion
Hasi Hays and William J. Richardson
Extracellular
matrix (ECM) remodeling is central to a wide variety of healthy and diseased tissue processes. Unfortunately, predicting ECM remodeling under various chemical and mechanical conditions has proven to be excessively challenging, due in part to its complex regulation by intracellular and extracellular molecular reaction networks that are spatially and temporally dynamic. We introduce ECMSim, which is a highly interactive, real-time, and web application designed to simulate heterogeneous
matrix remodeling. The current model simulates cardiac scar tissue with configurable input conditions using a large-scale model of the cardiac fibroblast signaling network. Cardiac fibrosis is a major component of many forms of heart failure. ECMSim solves 1.37 million coupled ordinary differential equations (ODEs) and executes approximately 4.84 million operations per time step in real time, encompassing 137 molecular species and 259 regulatory interactions per
cell across a 100x100 spatial array (10,000
cells), which accounts for inputs, receptors, intracellular signaling cascades, ECM production, feedback loops, and molecular
diffusion. The
algorithm is represented by a set of ODEs that are coupled with ECM molecular
diffusion. The equations are solved on demand using compiled C++ and the WebAssembly standard. The software enables the investigation of pathological or experimental conditions, hypothetical scenarios,
matrix remodeling, or the testing of the effects of an experimental drug(s) with a target receptor.
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Fluid Dynamics
Low Reynolds number flow in a packed bed of rotated bars
Wojciech Sadowski, Christin Velten, Maximilian Brömmer et al. (+5 more)
The present study focuses on the gas flow through an experiment-scale modular packed bed reactor consisting of square bars, arranged in layers. Each layer is rotated by $30^\circ$ resulting in a complex shape of the void spaces between the bars. Particle Image Velocimetry measurement results inside and on top of the studied system are presented for particle-based Reynolds numbers of 100 and 200, and used as validation data for two sets of particle-resolved numerical simulations, using boundary conforming meshing strategy and treating the solid boundaries via the blocked-off method. The flow inside the bed is largely independent from the Reynolds number and seems to be determined by the geometry of the void spaces. The flow in the freeboard is dominated by the presence of slowly dissipating jets downstream of the bed, which are characterized by unsteady oscillations at the higher Reynolds number. The numerical results obtained with both methods are in good agreement with the measurements, both inside and above the bed. However, stronger deviations between the results can be observed in the freeboard and can be traced to numerical properties of the current simulation approaches.
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All authors Wojciech Sadowski, Christin Velten, Maximilian Brömmer, Hakan Demir, Kerstin Hülz, Francesca di Mare, Katharina Zähringer, Viktor Scherer
Applied Physics
Monitoring of Fluid Transport in Low Temperature Water Electrolyzers and Fuel Cells: Emerging Technologies and Future Prospects
Zehua Dou, Laura Tropf, Tobias Lappan et al. (+7 more)
Low temperature water electrolyzers (LTWEs) and low temperature hydrogen fuel
cells (LTFCs) present a promising technological strategy for the productions and usages of green hydrogen energy towards a net-zero world. However, the interactions of gas/
liquid (fluid) transport and the intrinsic reaction kinetics in LTWEs/LTFCs present one of the key hurdles hindering high production rate and high energy conversion efficiency. Addressing these limitations requires analytical tools that are capable of resolving fluid transport across the heterogeneous, multiscale structures of operating LTWE and LTFC systems. This review provides a comprehensive overview of recent advancements in measurement technologies for investigating fluid transport. We first outline the technical requirements of such analytical systems, and assess the capabilities and limitations of established optical, X-rays and
neutrons based imaging systems. We emphasis on emerging strategies that utilize integrated miniaturized sensors, ultrasound, and other alternative physical principles to achieve operando, high-resolution, and scalable measurements towards applications at device and system levels. Finally, we outline future directions in this highly interdisciplinary field, emphasizing the importance of next-generation sensing concepts to overcome the fluid transport hurdle, towards accelerating the deployment of green hydrogen technologies.
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All authors Zehua Dou, Laura Tropf, Tobias Lappan, Hannes Rox, Xuegeng Yang, Lars Buettner, David Weik, Harry Hoster, Kerstin Eckert, Juergen Czarske
Applied Physics · Cross-listed from cs.RO
Vision-Based Tactile Sensing for the Perception of the Object's Compliance and Hardness
Muxing Huang, Zibin Chen, Weiliang Xu et al. (+5 more)
Object compliance perception enables the identification of soft materials, supporting tasks such as fruit detection and assisted medical palpation. Compliance perception requires sensing an object's deformation and contact forces. Existing
vision-based tactile sensing for compliance perception usually depends only on force or deformation. However, deformation-based approaches cannot reliably quantify object compliance, while force-based methods are overly sensitive to
geometric variations. To address these limitations, this paper presents a framework that fuses temporal force sequences and deformation field information. Specifically, time-varying contact forces are inferred from tactile image sequences via a neural network, while deformation characteristics are encoded using depth maps. Crucially, the temporal force sequence is used as a dynamic force-response feature for compliance recognition. In standard experiments, the force prediction error reaches 0.06 N within a measurement range of 12 N. The proposed method achieves a 98.0% Shore-hardness classification accuracy for samples ranging from 10 HA to 80 HA. In practical scenarios, including abnormal fruit detection and soft matter, the overall accuracy exceeds 98.5%. This method improves the compliance perception ability of artificial tactile systems and facilitates their deployment in
embodied perception applications.
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All authors Muxing Huang, Zibin Chen, Weiliang Xu, Zilan Li, Yuanzhi Zhou, Guoyuan Zhou, Wenjing Chen, Xinming Li
Space Physics · Cross-listed from astro-ph.SR
A 50-min coronal kink oscillation and its possible photospheric counterpart
Sihui Zhong, Valery M. Nakariakov and Dmitrii Y. Kolotkov
A coronal loop of 290~Mm length, observed at 171~Å\ with SDO/AIA on February 6th 2024 near AR 13571, is found to oscillate with two significantly different oscillation periods, $48.8 \pm 6.1$~min and $4.8\pm 0.3$~min. The oscillations occur in the time intervals without detected
flares or eruptions. Simultaneously, near the Northern footpoint of the oscillating loop, we detect a $49.6 \pm 5.0$-min periodic variation of the average projected photospheric
magnetic field observed with SDO/HMI. The shorter-period decayless oscillation is attributed to the eigen-mode, standing kink oscillation of the loop, while the longer-period oscillation may be the oscillatory motion caused by the periodic footpoint driver. The photospheric long-period process can also drive the short-period, eigen oscillation of the loop via the self-oscillatory, \lq\lq violin\rq\rq\, mechanism, in which a transverse oscillation is excited by an external quasi-steady flow. This finding indicates that the most powerful, lower-frequency spectral components of photospheric motions, which are well below the Alfvénic/kink cutoff, can reach the corona.
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Geophysics · Cross-listed from nlin.CD
Chaotic variability in a model of coupled ice streams
Kolja Kypke, Peter Ashwin and Peter Ditlevsen
Regions of fast-flowing ice in ice sheets, known as ice streams, have been theorized to be able to exhibit build-up/surge oscillatory variability due to thermomechanical coupling at the base of the ice. A simple model of three coupled ice streams is constructed to replicate the spatial configuration of a single ice stream being bisected into two termini. The model is constructed to mimic existing branching ice streams in northern Greenland. This model is shown to exhibit both steady-flow and build-up/surge oscillations. Further, the variability can be chaotic due to the nonlinear coupling of three incommensurate frequencies. This provides a mode of chaotic internal variability for ice sheets that contain these types of ice streams.
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Medical Physics
Trading robustness: a scenario-free approach to robust Multi-Criteria Optimization for Treatment Planning
Remo Cristoforetti, Philipp Süss, Tobias Becher et al. (+1 more)
Treatment planning in radiotherapy is inherently a multi-criteria optimization (MCO) problem. Traditionally, the treatment's robustness is not formulated as a part of this decision making problem, but dealt with separately through margins or robust optimization. This work facilitates integration of robustness into multi-criteria optimization using a recently proposed efficient scenario-free (s-f) robust optimization approach: The s-f approach relies on the fast evaluation of the expected dose distribution and mean variance during optimization. This is achieved by precomputation of probabilistic quantities, which can then be used for repeated solving of subproblems in the two explored MCO approaches: Lexicographic Ordering (LO) and Pareto Front (PF) approximation. Different prioritization strategies within the LO approach are used to assess the impact of variance reduction while a 3-objective PF approximation, including a variance reduction objective, is generated to visualize and analyze trade-offs between the competing objectives. The robust optimization is performed including 100 scenarios modeling setup and range errors, as well as organ motion, on 3D- and 4DCT lung cancer patient
datasets. Robustness analysis is performed to assess and explore the efficacy of all optimization strategies. The s-f approach enabled robust optimization in MCO with computational times comparable to nominal MCO. Both MCO strategies highlighted the interplay between dosimetric and variance reduction objectives. The LO approach showed how prioritization affects plan quality and robustness, while the PF analysis revealed a clear trade-off between robustness and organ-at-risk sparing. The reported analysis highlighted the conflicting trade-off nature of plan robustness and dosimetric quality, demonstrating how robust MCO supports a more informed and flexible decision-making process in treatment planning.
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All authors Remo Cristoforetti, Philipp Süss, Tobias Becher, Niklas Wahl
Fluid Dynamics
Migration and spreading of a droplet driven by a chemical step
Zhuo Long and Peng Gao
The chemical step is an elementary pattern in chemically heterogeneous substrates, featuring two regions of different wettability separated by a sharp border. Within the framework of lubrication theory, we investigate droplet motion and the contact-line dynamics driven by a chemical step, with the contact-line singularity addressed by the Navier slip condition. For both two-dimensional (2D) and three-dimensional (3D) droplets, two successive stages are identified: the migration stage, when the droplet traverses both regions, and the asymmetric spreading stage, when the droplet spreads on the hydrophilic region while being constrained by the border. For 2D droplets, we present a matched asymptotic analysis which agrees with numerical solutions. In the migration stage, a 2D droplet can exhibit translational motion with a constant speed. In the asymmetric spreading stage, the contact line at the droplet rear is pinned at the border. We show that a boundary layer still exists near the pinned contact line, across which the slope is approximately constant, whereas the
curvature would diverge in the absence of slip. For 3D droplets, our numerical simulations show that the
evolution is qualitatively analogous to the 2D case, while being significantly affected by the lateral flow. At early times, the contact line on the hydrophilic region advances linearly and spreads transversely according to a power law $t^{1/2}$. The droplet length and width exhibit non-monotonic variations due to the lateral flow. Eventually, the droplet detaches from the border and reaches
equilibrium at the hydrophilic substrate.
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Optics · Cross-listed from cond-mat.mes-hall
Green's function expansion for multiple coupled optical resonators with finite retardation using quasinormal modes
Robert Meiners Fuchs, Juanjuan Ren, Stephen Hughes et al. (+1 more)
The electromagnetic Green's function is a crucial ingredient for the theoretical study of modern photonic
quantum devices, but is often difficult or even impossible to calculate directly. We present a numerically efficient framework for calculating the scattered electromagnetic Green's function of a multi-cavity system with spatially separated open cavities (with arbitrary shape, dispersion and loss) and finite retardation times. The framework is based on a Dyson scattering equation that enables the construction of the Green's function from the quasinormal modes of the individual resonators within a few-mode approximation and a finite number of iteration steps without requiring nested integrals. The approach shows excellent agreement with the full numerical Green's function for the example of two coupled dipoles located in the gaps of two metal dimers serving as quasinormal mode cavities, and is easily extended to arbitrarily large separations and multiple cavities.
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All authors Robert Meiners Fuchs, Juanjuan Ren, Stephen Hughes, Marten Richter
Fluid Dynamics
Hydrodynamic Ratchet for Tracer Transport in a Soft Microchannel: A Detailed Analysis
Aakash Anand and A. Bhattacharyay
Understanding surface-driven transport is of paramount importance from the perspective of biological applications and the synthesis of microfluidic devices. In this work, we develop an analysis of a local inversion
symmetry broken fluid flow model through an undulating microchannel. Surface undulations of a few tens of Hertz in a soft microchannel keep the fluid flow in a low Reynolds number regime, allowing the advantage of a perturbation analysis of fluid flow. Using this, we develop a detailed analysis of the relationship between the fluid velocity and surface undulations, which is crucial for the subsequent numerical analysis of tracer motion. We used this information to study the dynamics of a tracer particle in the velocity field of an undulating microchannel. We show that the tracer particle can undergo ratcheting (which we call the hydrodynamics ratchet effect) in very specific, physically meaningful circumstances. We observe a ratcheting velocity of $\sim 0.15 \;\mu$m/sec for a micrometre-sized particle at room temperature in water when the undulations wavelength is of the order of 1 $\mu$m.
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Chemical Physics
Investigation of Cathode Electrolyte Interphase Formation via Coupling Liquid Electrochemical TEM and GC/MS
Kevyn Gallegos-Moncayo, Josephine Rezkallah, Justine Jean et al. (+3 more)
A deeper understanding of the cathode electrolyte interphase (CEI) formation mechanism is essential to elucidate battery degradation. Here, we combine
Liquid Electrochemical Transmission Electron Microscopy (ec-TEM) with Gas Chromatography/Mass Spectrometry (GC/MS) to monitor CEI
evolution in a realistic electrochemical environment, focusing on electrolyte behavior under high voltages. The correlation between the electrochemical response, gas and
liquid analysis after cycling, and the observation of deposited species on the working electrode (WE) reveals the processes governing CEI formation, stability, and composition. Cycling between 4 and 6 V vs Li leads to dispersed particles instead of a continuous film. These are partly composed of LiF and an amorphous phase that prevents dissolution at high potential. When cycled between 2.5 and 5.5 V, an anodic current peak indicates the formation of a 36 nm amorphous thin film without crystalline LiF, attributed to EC oxidation producing HF and subsequent LiF at a higher potential. LiF dissolution appears to follow a two-step pathway: electrolyte oxidation forms soluble intermediates, which are later reduced at lower potential to yield species capable of dissolving LiF. These results provide new insights into CEI formation and dissolution mechanisms, underscoring the need for further studies across different potential windows and with non carbonate electrolytes to validate these findings.
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All authors Kevyn Gallegos-Moncayo, Josephine Rezkallah, Justine Jean, Arash Jamali, Grégory Gachot, Arnaud Demortière
Atomic Physics
First GNSS-deployed optical clock for local time scale upgrade
Yi Yuan, Jian Cao, Jinbo Yuan et al. (+14 more)
Precise time scale is the universal base for all measurements. Here we report the deployment of a compact and transportable optical clock to a timekeeping institution and steering an active hydrogen maser to generate an optical time scale, realizing the upgrade of the local time scale in the Global
Navigation Satellite System. The optical clock was transported over 1200 km by express delivery and resume work as normal promptly, and its extremely high uptime of 93.6% in the half-year enabled us to precisely correct the frequency drift of hydrogen maser, ultimately achieving an unprecedented monthly instability of 4E-17. This steering experiment with a deployable optical clock marks a significant advancement, demonstrating that a timing accuracy below 100 ps per month can be achieved feasibly in various timekeeping institutions where hydrogen masers are typically employed as the primary contributor to timekeeping. In the future, mobile optical time scale based on such transportable optical clock can be deployed flexibly and rapidly, which is particularly important in scenarios lacking International Atomic Time reference.
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All authors Yi Yuan, Jian Cao, Jinbo Yuan, Dehao Wang, Pengcheng Fang, Qunfeng Chen, Shiying Cao, Xuanjian Wang, Sijia Chao, Hualin Shu, Guojun Li, Jinfeng Xu, Guitao Fu, Yuting Yang, Run Zhao, Fengfeng Shi, Xueren Huang
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Self-attention enabled quantum path analysis of high-harmonic generation in solids
Cong Zhao and Xiaozhou Zou
High-harmonic generation (HHG) in solids provides a powerful platform to probe ultrafast electron dynamics and interband–intraband coupling. However, disentangling the complex many-body contributions in the HHG spectrum remains challenging. Here we introduce a machine-learning approach based on a
Transformer encoder to analyze and reconstruct HHG signals computed from a one-dimensional Kronig–Penney model. The self-
attention mechanism inherently highlights correlations between temporal dipole dynamics and high-frequency spectral components, allowing us to identify signatures of nonadiabatic band coupling that are otherwise obscured in standard
Fourier analysis. By combining
attention maps with Gabor time–frequency analysis, we extract and amplify weak coupling channels that contribute to even-order harmonics and anomalous spectral features. Our results demonstrate that multi-head self-
attention acts as a selective filter for strong-coupling events in the time domain, enabling a physics-informed interpretation of high-dimensional
quantum dynamics. This work establishes
Transformer-based
attention as a versatile tool for solid-state strong-field physics, opening new possibilities for interpretable machine learning in attosecond spectroscopy and nonlinear photonics.
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Chemical Physics
Kinetic modelling of the CO2 capture and utilisation on NiRu-Ca/Al dual function material via parameter estimation
Meshkat Dolat, Andrew David Wright, Soudabeh Bahrami Gharamaleki et al. (+3 more)
This study presents a detailed, open-source kinetic modelling computational framework for CO2 capture and utilisation using a newly formulated dual-function material (DFM) comprising 15 wt% Ni, 1 wt% Ru, and 10 wt% CaO supported on spherical alumina. A finite difference reactor model was developed to simulate the cyclic adsorption, purge, and hydrogenation stages. The model incorporates experimentally-derived rate expressions, accounts for system delay via a second-order response function, and was fitted to time-resolved concentration laboratory data using
Bayesian optimisation. A combined parameter estimation strategy was employed to ensure mass continuity across stages and improve the robustness of purge kinetics. The kinetic parameters extracted reveal that carbonate decomposition, not methanation, is the rate-limiting step during hydrogenation. Temperature-dependent simulations confirm a trade-off between reaction kinetics and CO2 storage capacity, with methane yield maximised at 300C when compared with the other temperature sets. By offering transparent methodology and reproducible code, this work provides a robust platform for researchers and practitioners to study, validate, and optimise DFM systems.
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All authors Meshkat Dolat, Andrew David Wright, Soudabeh Bahrami Gharamaleki, Loukia-Pantzechroula Merkouri, Melis S. Duyar, Michael Short
Optics
Quasi Normal Modes in Dispersive Photonic Time-Crystals
Calvin M. Hooper, Ian R. Hooper and Simon A.R. Horsley
Quasinormal modes characterise the transient response of static optical cavities. Here, we introduce the notion of a Floquet quasinormal mode to describe transient responses in photonic time
crystals. Contrasting their static counterparts, exceptional points associated with
symmetry transitions are an inherent feature, as modes spontaneously and non-perturbatively lock their phase to the oscillations of the material. We further investigate the limiting behaviour of the Floquet quasinormal modes in large cavities. Distinct non-perturbative behaviour arises in time-modulated systems as increasingly large time-
crystal cavities come closer to achieving the maximum gain predicted from a bulk wavenumber bandgap.
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Plasma Physics
Comparison of MHD and gyrokinetic simulations of linear instabilities at the q = 1 surface
F. N. Antlitz, X. Wang, M. Hoelzl et al. (+10 more)
Accurate modeling of core instabilities in tokamak
plasmas is essential to understand the underlying physical mechanisms and their impact on
plasma confinement. The ideal stability of the internal kink mode and the m = 1 collisionless tearing mode are analyzed numerically both with gyrokinetic and MHD codes. We compare the different models implemented in the codes and show that the gyrokinetic equations without collisions inherently contain the ideal MHD limit. The simulation results show that the stability of the internal kink mode strongly depends on the choice of several setup parameters like the inclusion of parallel
magnetic field fluctuations, the tokamak aspect ratio, the drift- or gyrokinetic treatment of the ions and the electron mass. Furthermore, we demonstrate the stabilization of the instabilities by diamagnetic effects. Our results indicate that gyrokinetic and MHD models can be reconciled in the description of the internal kink mode by careful consideration of the simulation setup and model assumptions, but instabilities like the collisionless tearing mode require a more advanced treatment beyond MHD.
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All authors F. N. Antlitz, X. Wang, M. Hoelzl, G. T. A. Huijsmans, H. Zhang, J. Puchmayr, Ph. Lauber, T. Hayward-Schneider, B. F. McMillan, A. Mishchenko, E. Poli, Z.X. Lu, JOREK team
Accelerator Physics
Intense and Tunable Multi-color Terahertz Radiation from Laser-Shaped Electron Beams
Yin Kang, Weiyi Yin, Xianzhe Li et al. (+5 more)
High-power multi-color terahertz (THz) radiation exhibits extraordinary scientific application prospects at various scientific frontiers, for its capacity to deliver THz excitation at multiple frequencies simultaneously. However, the generation of high-power multi-color THz radiation with tunable frequencies remains a challenge for existing techniques. Here, a technique by combining the multi-
laser pulses frequency beating and coherent undulator amplification is proposed for generating high-power multi-color THz radiation with tunable frequency. Numerical simulations indicate that the proposed technique can produce multi-color THz radiation with three to six distinguished colors and a peak power up to hundreds of MW, and the temporally separated two-color pulses can also be produced by employing undulators with different resonance. Due to the intrinsic properties of the proposed technique, the THz frequencies, the color number and the frequency interval can be effectively controlled by simply adjusting the beating
laser. This method paves the way for advanced application of THz pump-THz probe experiments for selective excitation of atomic multi-level systems and molecular fingerprint recognition.
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All authors Yin Kang, Weiyi Yin, Xianzhe Li, Yixuan Liu, Yue Wang, Yuan Ma, Kaiqing Zhang, Chao Feng
Optics
Brillouin-Mandelstam Scattering-based Cooling of Traveling Acoustic Waves from Cryogenic Temperatures
Lisa Fischer, Laura Blázquez Martínez, Robin Chenivière et al. (+2 more)
Thermal
phonons are a major source of decoherence in
quantum mechanical systems. Operating in the
quantum ground state is therefore often an experimental prerequisite. Additionally to passive cooling in a cryogenic environment, active
laser cooling enables the reduction of
phonons at specific acoustic frequencies. Brillouin cooling has been used to show efficient reduction of the thermal
phonon population in waveguides at GHz frequencies down to 74 K. In this letter, we demonstrate cooling of a 7.608 GHz acoustic mode by combining Brillouin active cooling with precooling from 77 K using
liquid nitrogen. We show a 69 % reduction in the
phonon population, resulting in a final temperature of 24.3 K, 50 K lower than previously reported.
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All authors Lisa Fischer, Laura Blázquez Martínez, Robin Chenivière, Johann Troles, Birgit Stiller
Physics and Society
Large cities lose their growth advantage as countries urbanize
Andrea Musso, Diego Rybski, Dirk Helbing et al. (+1 more)
The share of the world population living in cities with more than one million people rose from 11% in 1975 to 24% in 2025 (our estimates). Will this trend towards greater concentration in large cities continue or level off? We introduce two new city population
datasets that use consistent city definitions across countries and over time. The first covers the world between 1975 and 2025, using satellite imagery. The second covers the U.S. between 1850 and 2020, using census microdata. We find that urban growth follows a characteristic life cycle. In the early stages of a country's urbanization process, large cities grow faster than smaller ones. At later stages, growth rates equalize across sizes. We use this life cycle to project future population concentration in large cities. Our projections suggest that 38% of the world population will be living in cities with more than one million people by 2100. This estimate is higher than the 33% implied by the well-known theory of proportional growth, but lower than the 42% obtained by extrapolating current trends.
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All authors Andrea Musso, Diego Rybski, Dirk Helbing, Frank Neffke
Physics and Society
Do Railway Commuters Exhibit Consistent Route Choice Rationality Across Different Contexts and Time? Evidence from Tokyo metropolitan Commutes
Yixuan Y Zheng, Hideki Takayasu and Misako Takayasu
In urban railway systems, if every commuter were perfectly rational, concentrated demand on optimal routes would undermine system performance. Understanding the actual degree of collective route choice determinism, and whether it remains stable over time, is essential for transportation policy. Smartphone GPS data offers both the scale and complete trajectory coverage that survey data and smart card data individually lack, yet its coarse spatial accuracy has limited its adoption for railway route identification. To overcome this, we develop a methodology to identify railway commuting routes from one year of GPS data covering over one million daily users in the Tokyo metropolitan area. We apply a multinomial logit (MNL) framework, utilizing a standardization convention to extract a comparative measure of collective determinism alongside relative attribute preferences. We find that collective route choices in Tokyo are strongly cost-sensitive but non-deterministic. Both components remain stable across all twelve months of 2023, confirming that this determinism represents a structural consistency of the commuting system. Leveraging the
dataset's scale, we further estimate parameters for each origin-destination (OD) pair individually, revealing systematic heterogeneity driven by departure time and transport complexity that smaller
datasets treat as unobserved.
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Chemical Physics
Time-resolved solvation dynamics of Li$^+$, Na$^+$ and K$^+$ ions in liquid helium nanodroplets
Jeppe K. Christensen, Simon H. Albrechtsen, Christian E. Petersen et al. (+7 more)
In 2023, ultrafast pump-probe spectrocopy was used to record the solvation dynamics of a single Na$^+$ ion in a
liquid helium droplet, atom-by-atom and with femtosecond time resolution [Albrechtsen et al., Nature, 2023, 623, 319]. Subsequently, theoretical studies showed that other alkali ions solvate in a similar manner but no experimental results were reported so far. Here, we extend the previous measurement on Na$^+$ to Li$^+$ and K$^+$ ions. A pump pulse selectively ionizes an alkali atom, initially residing at the droplet surface, and the ensuing solvation dynamics of the formed alkali cation, Ak$^+$, is followed by ionizing a Xe atom, located in the droplet interior, and recording the yields of Ak$^+$He$_n$ ions expelled from the droplet as a function of the pump-probe pulse delay. We find that Li$^+$, Na$^+$ and K$^+$ ions solvate with a binding rate of 1.8 $\pm$ 0.1, 1.8 $\pm$ 0.1 and 1.7 $\pm$ 0.1 He per ps, respectively. Furthermore, by comparing the number distribution of the Ak$^+$He$_n$ ion yields to the evaporation energies of these ion–He complexes, obtained by Path Integral Monte Carlo calculations, we identify signatures of the first solvation shells of Li$^+$, Na$^+$ and K$^+$. Lastly, we determine the time-dependent dissipation of the solvation energy from the vicinity of the three alkali ion species and find that the rate is highest (lowest) for Li$^+$ (K$^+$)
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All authors Jeppe K. Christensen, Simon H. Albrechtsen, Christian E. Petersen, Constant A. Schouder, Iker Sánchez-Pérez, Pedro Javier Carchi-Villalta, Massimiliano Bartolomei, Fernando Pirani, Tomás González-Lezana, Henrik Stapelfeldt
Computational Physics · Cross-listed from cs.LG
General Fourier Feature Physics-Informed Extreme Learning Machine (GFF-PIELM) for High-Frequency PDEs
Fei Ren, Sifan Wang, Pei-Zhi Zhuang et al. (+2 more)
Conventional physics-informed extreme learning machine (PIELM) often faces challenges in solving partial differential equations (PDEs) involving high-frequency and variable-frequency behaviors. To address these challenges, we propose a general
Fourier feature physics-informed extreme learning machine (GFF-PIELM). We demonstrate that directly concatenating multiple
Fourier feature mappings (FFMs) and an extreme learning machine (ELM) network makes it difficult to determine frequency-related hyperparameters. Fortunately, we find an alternative to establish the GFF-PIELM in three main steps. First, we integrate a variation of FFM into ELM as the
Fourier-based activation function, so there is still one hidden layer in the GFF-PIELM framework. Second, we assign a set of frequency coefficients to the hidden
neurons, which enables ELM network to capture diverse frequency components of target solutions. Finally, we develop an innovative, straightforward initialization method for these hyperparameters by monitoring the distribution of ELM output weights. GFF-PIELM not only retains the high accuracy, efficiency, and simplicity of the PIELM framework but also inherits the ability of FFMs to effectively handle high-frequency problems. We carry out five case studies with a total of ten numerical examples to highlight the feasibility and validity of the proposed GFF-PIELM, involving high frequency, variable frequency, multi-scale behaviour, irregular boundary and inverse problems. Compared to conventional PIELM, the GFF-PIELM approach significantly improves predictive accuracy without additional cost in training time and architecture complexity. Our results confirm that that PIELM can be extended to solve high-frequency and variable-frequency PDEs with high accuracy, and our initialization strategy may further inspire advances in other physics-informed machine learning (PIML) frameworks.
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All authors Fei Ren, Sifan Wang, Pei-Zhi Zhuang, Hai-Sui Yu, He Yang
Chemical Physics · Cross-listed from math-ph
Reduced Density Matrix Functional Theory And A Reduced Formulation Of Density Functional Theory
Håkon R. Fredheim and Simen Kvaal
A mathematical framework for reduced density
matrix functional theory (RDMFT) is proposed. The work is inspired by and generalizes the work by E.H.~Lieb [E.H. Lieb, Int. J. Quant. Chem. 24(1983), pp.243–277] on density-functional theory (DFT). We introduce a
Banach space for density
matrices with finite kinetic energy. The dual space is a rich class of single-particle potentials, i.e., Hermitian forms. The ground state energy of an $N$-
fermion system with external forces given by any such Hermitian form is expressed as the Legendre–Fenchel transform of a convex and lower semicontinuous “universal” reduced density
matrix functional. The formalism is employed to provide a mathematical framework for density-functional theory (DFT). The main tool here is a rigorous definition of diagonals of reduced density
matrices. The result is a refinement of Lieb's results on DFT applicable to a wide variety of models.
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