Accelerator Physics
Active interrogation of underground piezoelectric fabrics using high energy muon beams propagating across seismogenic faults
L. Serafini, A. Bacci, L. Bandiera et al. (+12 more)
In this paper we extend a previous analysis of a newly conceived technique based on active interrogation of tectonic stress
evolution in regions hosting active seismogenic faults. The aim is to monitor and detect stable and reliable precursor signals on an adequate time scale, well before an earthquake event, that can play a crucial role in activating alarms for civil protection systems. The precursor signal relies on continuous measurements of the time
evolution of tectonic stress, obtained by interrogating underground, with a high energy collimated
muon beam, the piezoelectric fabrics present in quartz rich granite like rocks surrounding a known seismogenic fault in the Earth crust. Beam propagation through the rock across the active fault conveys to a detector at the exit of the traversal information on the amplitude of the piezoelectric field, which scales with the tectonic stress applied to quartz
crystals embedded in the rock. The system, named ERMES (Earthquake Reconnaissance using
Muon beam
Evolution in Silicon dioxide), differs from other techniques under study detecting electromagnetic signals generated by piezoelectricity outside the Earth crust, as it probes piezoelectric effects directly inside the source region of the associated electromagnetic field, namely the near field within quartz
crystals rather than the far field in open space. We present a focused analysis of
muon beam manipulation after rock traversal and before detection using a newly conceived muonic lens, and we explore the maximum rock penetration capability of a high energy
muon beam, reaching about 3 km of rock thickness for a 10 TeV beam. Owing to the peculiarity of
muon propagation through such kilometer scale targets, we cross checked previous FLUKA Monte Carlo simulations with Geant4 to clarify the secondary
muons role generated by primary
muon interactions in solid matter over long propagation lengths.
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All authors L. Serafini, A. Bacci, L. Bandiera, F. Broggi, I. Drebot, A. Frazzitta, A. M. Marotta, G. Muttoni, G. Paternò, V. Petrillo, M. Rossetti Conti, A. R. Rossi, S. Samsam, M. Voltolini, M. Zucali
Optics
Observation of Light-Driven Levitation Near Epsilon-Near-Zero Surfaces
Maria Grazia Donato, Michael Hinczewski, Theodore Letsou et al. (+6 more)
Optical manipulation of micro- and nanoparticles near surfaces is fundamental for applications in sensing and microfluidics, yet controlling particle-surface interactions remains challenging. Here we experimentally investigate light-induced forces on dielectric particles near epsilon-near-zero (ENZ) metamaterial surfaces using photonic force microscopy. By illuminating trapped particles with tunable visible light, we observe a wavelength-dependent repulsive force unique to ENZ surfaces, contrasting with the attractive forces near dielectric or metallic substrates. This repulsion peaks near the ENZ frequency and may be attributed to combined optical ENZ effects and thermophoretic forces. Our findings demonstrate that ENZ metamaterials can induce stable levitation of particles via light-driven forces, offering a novel mechanism for contactless manipulation in microfluidic environments. This work advances understanding of light-matter interactions at ENZ interfaces and suggests potential for ENZ-based optical control of micro- and nanoscale objects, with potential applications in micro- and nanofluidic environments.
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All authors Maria Grazia Donato, Michael Hinczewski, Theodore Letsou, Mohamed ElKabbash, Rosalba Saija, Pietro G. Gucciardi, Nader Engheta, Giuseppe Strangi, Onofrio M. Marago
Atomic Physics · Cross-listed from cond-mat.quant-gas
Cloud parameter estimation for interacting BEC after time-of-flight
Rasmus Malthe Fiil Andersen, Stine Frederiksen, Laurits Stokholm et al. (+4 more)
Experiments on Bose-Einstein condensates at finite temperature typically extract the system parameters, such as temperature, atom number, and condensed fraction from time-of-flight images taken after a free expansion time. This paper systematically examines the effect of repulsive interactions between the condensed and thermal atoms in partially condensed clouds on the expansion profile of the thermal cloud. An analytical expression for the expansion can be obtained only if the interactions between the Bose-Einstein condensate and thermal atoms are neglected, resulting in a Bose-enhanced distribution for the thermal component. Here, the deformation of the cloud due to interactions and the effects on estimated parameters are investigated by simulating the expansion using a ballistic approximation. By fitting the simulated expansion profiles with a Bose-enhanced distribution, the errors of using such a fit are estimated, and the results are explained phenomenologically. The simulation was also used as a fitting function for experimental data, showing better agreement of the extracted condensed fraction with the semi-ideal model than results from a Bose-enhanced fit.
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All authors Rasmus Malthe Fiil Andersen, Stine Frederiksen, Laurits Stokholm, Ilja Zebergs, Mick Kristensen, Carrie Weidner, Jan Joachim Arlt
Applied Physics · Cross-listed from hep-ex
A comparison of simulation tools for Muon-Induced X-ray Emission (MIXE) in thin films: a study case with lithium batteries
Maxime Lamotte, Michael W. Heiss, Thomas Prokscha et al. (+1 more)
We present a comparative study of three Monte Carlo simulation frameworks -SRIM, GEANT4, and PHITS- for modeling the transport, stopping, and atomic cascade of negative
muons in micrometer-scale, multilayer systems relevant to
Muon-Induced X-ray Emission (MIXE) experiments at the Paul Scherrer Institute (PSI). Using a lithium-ion battery as a
benchmark target, simulated implantation profiles are compared with experimental data from the
GIANT spectrometer. All three codes reproduce the overall
muon depth distributions with good consistency, even across sharp density contrasts. SRIM provides reliable implantation estimates for compact geometries, whereas PHITS reproduces GEANT4 results with comparable accuracy and additionally generates muonic X-ray spectra. These spectra, however, exhibit a systematic energy offset in the K-line transitions of medium- and high-Z elements relative to theoretical and experimental values. Despite this bias, PHITS accurately captures relative intensities and spectral shapes, enabling element-specific line identification. The results demonstrate that SRIM and PHITS constitute practical tools for rapid estimation of
muon implantation and stopping profiles, and that PHITS holds strong potential for predictive MIXE spectroscopy once its transition-energy bias is corrected.
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All authors Maxime Lamotte, Michael W. Heiss, Thomas Prokscha, Alex Amato
Fluid Dynamics
Wilson-Fisher renormalization of discrete gravity-capillary wave turbulence in viscous fluids
José A. Santiago, Mikheil Kharbedia, Basilio J. García et al. (+1 more)
We report an experimental realization of Wilson-Fisher renormalization in driven surface-wave
turbulence across Newtonian fluids spanning nearly six decades in Raynolds number. Discrete capillary and
gravity turbulence define two universality classes selected by interaction
topology: triadic resonances for capillary waves and effectively tetradic scattering for
gravity waves. Navier-Stokes viscosity is the relevant perturbation that renormalizes spectral transfer and terminates the cascade. The resulting framework predicts the Kolmogorov cutoff from the balance of nonlinear transfer and viscous damping, and Reynolds scaling of the integrated inertial spectral weight.
Laser Doppler Vibrometry quantitatively confirms these renormalized scaling laws, establishing discrete
gravity-capillary
turbulence as a tunable laboratory for nonequilibrium crossoever criticality.
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All authors José A. Santiago, Mikheil Kharbedia, Basilio J. García, Francisco Monroy
Fluid Dynamics
Scale Collapse of Vortices at Porous-Fluid Interfaces
Justin Courter, Vishal Srikanth, Thibaut Kemayo et al. (+1 more)
The interaction between externally generated
turbulence and porous media is central to many engineering and environmental flows, yet the fate of macroscale vortical structures at a porous/fluid interface remains uncharacterized. By numerically simulating the turbulent flow using a two-dimensional (2D) direct numerical simulation (DNS), we investigate the penetration, breakdown, and turbulent kinetic energy (TKE) transport of macroscale
vortices impinging on porous
matrices with high porosities $\phi$ = 0.80-0.95. For all porosities considered, macroscale
vortices collapse abruptly at the porous interface and do not persist within the
matrix, supporting the pore-scale prevalence of
turbulence even under strong external forcing. Although
vortex impingement injects TKE into the porous medium through turbulent transport at the interface, this supplied TKE is rapidly redistributed and dissipated as the flow reorganizes to satisfy pore-scale
geometric constraints. Deeper within the porous layer,
turbulence is sustained primarily by local shear production associated with pore-scale velocity gradients, and the internal flow becomes increasingly independent of upstream conditions. Variations in porosity modulate the balance between production and dissipation of TKE by altering
geometric confinement and the local flow conditions within the pores although the dominant turbulent length scale within the porous
matrix remains set by the pore size. These results demonstrate that porous media act as a robust
geometric filter that enforces pore-scale-dominated
turbulence regardless of the external forcing.
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All authors Justin Courter, Vishal Srikanth, Thibaut Kemayo, Andrey V. Kuznetsov
Chemical Physics
The Direct-Product Decomposition Approach for Symmetry Exploitation in Many-Body Methods in Case of Non-Abelian Point Groups
Malte Hellmann and Jürgen Gauss
We demonstrate for the specific case of $C_{3v}$ how the direct-product decomposition scheme for the treatment of
symmetry in coupled-cluster (CC) calculations can be extended to non-Abelian point groups. We show that for the two-electron integrals and CC amplitudes a block structure can be obtained by resolving the reducible products of two irreducible representations into their irreducible representations. To deal with the necessary resorts of the ordering of the two-electron integrals and amplitudes,
spin-adaptation, and the O(M$^5$) contractions (with M as the number of basis functions) of a CC calculation, we suggest a strategy that uses both the reduced and non-reduced representation of the corresponding quantities and switches back and forth between them. While the reduced representations are the ones used in the O(M$^6$) contractions, the other steps are better carried out in the non-reduced representation. Our pilot implementation of the CC singles and doubles method confirms in test calculations for NH$_3$ and PH$_3$ using different basis sets that significant savings (of more than 20 compared to treatments without
symmetry and about 5 compared to treatments using $C_s$
symmetry) are possible and suggest that the exploitation of non-Abelian
symmetry would render CC computations on large highly symmetric molecules possible
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Fluid Dynamics · Cross-listed from cond-mat.soft
Capillary Slinky: Equilibrium and Dynamics of Droplets in a Soft Spring
Bidisha Bhatt and Andreas Carlson
Springs can be found in many applications and biological systems, and when these are soft, they easily deform. At small scales, capillarity can induce a force leading to spring deformations when the elastocapillary number is small. We demonstrate through experiments the non-trivial
equilibrium shape
liquid droplets adopt in these soft springs, which form an annulus, Eruciform, and spherical shapes. When these droplets are set in motion, they display different flow regimes with significant dissipation generated by the internal rotational flow. The static and dynamics of droplets in such a capillary slinky is also used to demonstrate how surface tension can actuate springs by stretching/compression, while providing a way for active flow control in soft springs.
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Instrumentation and Detectors
A compact Optical Liquid Argon Facility at Roma Tre
Hexi Shi, Valerio D'Andrea, Giuseppe Salamanna et al. (+2 more)
In this paper we present a compact test facility for the measurement of optical properties of
liquid argon as scintillator. The setup is under preparation at Roma Tre and it has a volume of 40 L
liquid argon, which is liquefied from argon gas with a purity of $\ge 99.9999\%$ vol. To readout the scintillation
photons from
liquid argon with the highest intensity near 127 nm, we use the
vacuum ultraviolet silicon photomultipliers from Hamamatsu. By submerging the
photon detectors directly inside the
liquid argon, we can eliminate the systematics from the wavelength shifter and light guides which have been commonly used to detect the scintillation
photons of
liquid argon.
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All authors Hexi Shi, Valerio D'Andrea, Giuseppe Salamanna, Krzysztof Szczepaniec, Diego Tagnani
Atomic Physics · Cross-listed from cond-mat.quant-gas
Enhanced multi-parameter metrology in dissipative Rydberg atom time crystals
Bang Liu, Jun-Rong Chen, Yu Ma et al. (+10 more)
The pursuit of unprecedented sensitivity in
quantum enhanced metrology has spurred interest in non-
equilibrium quantum phases of matter and their
symmetry breaking. In particular, criticality-enhanced metrology through time-translation
symmetry breaking in many-body systems, a distinct paradigm compared to spatial
symmetry breaking, is a field still in its infancy. Here, we have investigated the enhanced sensing at the boundary of a continuous time-
crystal (CTC) phase in a driven Rydberg atomic gas. By mapping the full phase diagram, we identify the parameter-dependent phase boundary where the time-translation
symmetry is broken. This allows us to use a single setup for measuring multiple parameters, in particular frequency and amplitude of a microwave field. By increasing the microwave field amplitude, we first observe a phase transition from a thermal phase to a CTC phase, followed by a second transition into a distinct CTC state, characterized by a different oscillation frequency. Furthermore, we reveal the precise relationship between the CTC phase boundary and the scanning rate, displaying enhanced precision beyond the Standard
Quantum Limit. This work not only provides a promising paradigm rooted in the critical properties of time
crystals, but also advances a method for multi-parameter sensing in non-
equilibrium quantum phases.
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All authors Bang Liu, Jun-Rong Chen, Yu Ma, Qi-Feng Wang, Tian-Yu Han, Hao Tian, Yu-Hua Qian, Guang-Can Guo, Li-Hua Zhang, Bin-Bin Wei, Abolfazl Bayat, Dong-Sheng Ding, Bao-Sen Shi
Geophysics
Joint Bayesian inference of Earth's magnetic field and core surface flow on millennial timescales
Andreas Nilsson, Neil Suttie, Marie Troyano et al. (+3 more)
Understanding Earth's core dynamics over millennial timescales requires models that jointly describe the
evolution of the geomagnetic field and core surface flow, while accommodating the sparse, irregular, and uncertain nature of archaeomagnetic and palaeomagnetic data. We present a new
Bayesian core field and core flow modelling framework that utilises archaeo/palaeomagnetic data directly, combining a reduced
stochastic representation of core surface dynamics derived from numerical geodynamo statistics with a probabilistic treatment of observational and chronological uncertainties. A key innovation is an efficient discrete marginalisation of age uncertainties, which avoids the convergence difficulties associated with co-estimating ages in high-dimensional
Hamiltonian Monte Carlo inversions. The framework aims to reconstruct the coupled
evolution of the geomagnetic field and core surface flow over the past 9000 years while preserving dynamical correlations implied by the prior geodynamo time series. Tests using synthetic data generated from an Earth-like geodynamo demonstrate that the method reliably recovers large-scale geomagnetic field variations and key aspects of core dynamics, including long-term westward drift and the
evolution of planetary-scale eccentric gyres. These results show that, when combined with physically informed priors, archaeo/palaeomagnetic data can constrain millennial-scale core flow, paving the way for reconstructions based on real data.
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All authors Andreas Nilsson, Neil Suttie, Marie Troyano, Nicolas Gillet, Julien Aubert, Anders Irbäck
Medical Physics
Radiation Shielding Performance of Different Concrete Materials: A Systematic Review
Christiana Subaar, Ziem Samuel Aanoneda, Sylivia Boateng et al. (+2 more)
Background: Concrete is one of the most-used material today in
nuclear, medical, and industrial applications for radiation shielding due to its economic advantages and availability together with its structural performance. However, differences in the use of aggregates, density, and other additives affect radiation attenuation efficiency. It is therefore necessary to understand and compare shielding properties of various concrete formulations for the optimization of safety and performance in radiation-prone environments. Methods: Using Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, a literature search was performed across PubMed, Scopus, ScienceDirect, and Google Scholar. 17 peer-reviewed studies published between 2010 and 2025 were analysed systematically. Data was extracted based on material composition, density, radiation type, energy range, attenuation coefficients, and shielding efficiency. The obtained results were compared to find the trend in performance and optimization of the considered materials. Conclusion: Radiation shielding efficiency of concrete is dependent on its density, microstructural characteristics and type of aggregate. For superior performance in a mixed radiation field, Heavy and boron-rich additives can be added. Newly developed UHPCs and nano-engineered concretes are lightweight, durable, and environmentally friendly options for shielding materials compared to traditional ones. Further studies are needed to focus on the standardization of test methods, validation of long-term stability, and coupling computational modelling with experimental data in order to guide material design for applications featuring enhanced radiation shielding.
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All authors Christiana Subaar, Ziem Samuel Aanoneda, Sylivia Boateng, Emmanuella Konadu Amaniampong, Philimon Adjei
Optics
Neural-network-based high-speed and high-definition full-field dynamic optical coherence tomography
Suzuyo Komeda, Nobuhisa Tateno, Yusong Liu et al. (+7 more)
A neural-network (NN)-based method for high-speed, high-definition dynamic optical coherence
tomography (DOCT) using full-field swept-source optical coherence microscopy (FF-SS-OCM) is demonstrated. FF-SS-OCM provides high-definition OCT images, but, particularly in DOCT imaging, it results in a significant enlargement of the data size and subsequently long data streaming and processing time, which prevents high-throughput imaging. We address this issue by introducing an NN-based DOCT method that generates high-definition logarithmic intensity variance (LIV) -based DOCT images from only four OCT volumes, whereas the conventional method required 32 volumes. The NN model successfully generates an LIV image that is qualitatively and quantitatively similar to the LIV image computed from 32 volumes. This approach significantly reduces data size, transfer time, and processing time for DOCT imaging by a factor of eight. Specifically, these were reduced from 42 GB to 5.3 GB, 7 min to 55 s, and 4 hours to 30 min, respectively.
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All authors Suzuyo Komeda, Nobuhisa Tateno, Yusong Liu, Rion Morishita, Xibo Wang, Ibrahim Abd El-Sadek, Atsuko Furukawa, Satoshi Matsusaka, Shuichi Makita, Yoshiaki Yasuno
Chemical Physics
Molecular electrostatic potentials from machine learning models for dipole and quadrupole predictions
Kadri Muuga, Lisanne Knijff and Chao Zhang
The molecular electrostatic potential (MEP) is a key quantity for describing and predicting intermolecular and ion-molecule interactions. Here, we assess the ability of machine-learning (ML) models to infer the MEP, based on the equivariant graph-convolutional neural network architecture PiNet2 and trained on dipole and quadrupole moments. For the established QM9
dataset, we find that including the quadrupole contribution in the ML models substantially improves their ability to recover the MEP compared to dipole-only models. This trend is confirmed on the SPICE
dataset, which spans a much broader region of organic chemical space. Together, this study underscores the central role of the quadrupole moment as a fitting target for ML models aiming at rapid access to the MEP.
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Accelerator Physics
Design, Fabrication and Testing of a D-Shaped High Temperature Superconducting Magnet
Upendra Prasad, Mahesh Ghate, Piyush Raj et al. (+14 more)
High-temperature technical
superconductors are potential candidates for compact and high-field tokamak magnets. The demand for higher fusion power can be met with an on-axis high
magnetic field due to toroidal magnets. An R&D activity has been initiated at the Institute for
Plasma Research, India, to develop a compact D-shaped superconducting magnet utilizing REBCO high-temperature superconducting tapes. Under this initiative, a toroidal configuration with a major radius of 0.42 m, consisting of eight D-shaped, four poloidal field, and a central solenoid high-temperature superconducting magnets producing an on-axis toroidal
magnetic field of 0.23 T has been conceptualized. The fabrication feasibility of a D-shaped coil for this toroidal configuration also envisaged using stacked high-temperature superconducting cable. In this paper, we report the design of a compact D-shaped coil, the fabrication of a long length HTS cable, a winding pack, and its integration with a cryogenic casing and
vacuum enclosure. The winding pack terminations, joints, its interfacing with the power supply, and performance testing are also reported in this paper.
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All authors Upendra Prasad, Mahesh Ghate, Piyush Raj, Deven Kanabar, Pankaj Varmora, Swati Roy, Arun Panchal, Dhaval Bhavsar, Anees Bano, Nitish Kumar, Bhadresh Parghi, Akhilesh Yadav, Mohd.Umer, Vijay Vasava, Raton Mandal, Rajkumar Ahirwar, Megha Thaker
Plasma Physics
Updated electrical design of the Diagnostic Neutral Beam Injector in RFX-mod2
Marco Barbisan, Bruno Laterza, Luca Cinnirella et al. (+4 more)
The Diagnostic Neutral Beam Injector (DNBI) of the RFX-mod2 experiment (Consorzio RFX, Padova) is expected to provide novel and significant information about the Reversed Field Pinch confinement of fusion
plasmas. The present DNBI, built by the Budker Institute of
Plasma Physics, features an arc discharge H+ source, coupled to a 4-grid 50 keV acceleration system, to produce a 50 ms, 5 A ion beam. This contribution presents the latest upgrades of the DNBI. The High Voltage Deck (HVD) was completely restructured, and the power transfer was simplified to a single phase insulation
transformer. The 50 kV distribution
circuit was modernized and made safer against breakdowns. Several custom power supplies in the HVD were designed and procured; their electronic boards were developed to be multipurpose in the DNBI, simplifying the system and improving its maintainability. The features of the
magnetic insulation power supply and gas valve power supplies are presented in detail. Finally, the new PLC control system was improved for better protection of the CPU against overvoltages and for better scalability and maintainability of the system.
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All authors Marco Barbisan, Bruno Laterza, Luca Cinnirella, Lionello Marrelli, Federico Molon, Simone Peruzzo, Enrico Zampiva
Optics
Quantum bianisotropy in light-matter interaction
E. O. Kamenetskii
Quantum bianisotropy and chirality are fundamental concepts in light matter interaction that describe how materials with broken
symmetries respond to electromagnetic fields at the level of macroscopic
quantum electrodynamics. In
quantum bianisotropy, magnetoelectric (ME) energy plays a critical role in mediating and enhancing light matter interactions. This concept is essential for bridging the gap between classical electromagnetics (where bianisotropy often involves field nonlocality) and
quantum mechanics in metamaterials. The precise manipulation of a
quantum emitter's properties at a subwavelength scale is due to near fields, which effectively function as a tunable environment. We show that the ME near field, interpreted as a structure combining the effect of bianisotropy (chirality) with a
quantum atmosphere, is a nonMaxwellian field with spacetime
symmetry breaking.
Quantum ME fields arise from the dynamic modulation and topological coupling of magnetization and electric polarization within ME meta atoms, specific subwavelength structural elements with
magnetic and dielectric subsystems in
magnetic insulators.
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Geophysics
Model-Driven GPR Inversion Network With Surrogate Forward Solver
Huilin Zhou, Xin Liu, Kexiang Wang et al. (+1 more)
Data-driven deep learning is considered a promising solution for ground-penetrating radar (GPR) full-waveform inversion (FWI), while its generalization ability is limited due to the heavy reliance on abundant labeled samples. In contrast, Deep unfolding network (DUN) usually exhibits better generalization by integrating model-driven and data-driven approaches, yet its application to GPR FWI remains challenging due to the high computational cost associated with forward simulations. In this paper, we integrate a deep learning-based (DL-based) forward solver within an unfolding framework to form a fully neural-network-based architecture, UA-Net, for GPR FWI. The forward solver rapidly predicts B-scans given permittivity and conductivity models and enables automatic differentiation to compute gradients for inversion. In the inversion stage, an optimization process based on the Alternating Direction Method of Multipliers (ADMM) is unfolded into a multi-stage network with three interconnected modules: data fitting, regularization, and multiplier update. Specifically, the regularization module is trained end-to-end for adaptive learning of sparse target features. Experimental results demonstrate that UA-Net outperforms classical FWI and data-driven methods in reconstruction accuracy. Moreover, by employing transfer learning to fine-tune the network, UA-Net can be effectively applied to field data and produce reliable results.
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All authors Huilin Zhou, Xin Liu, Kexiang Wang, Shufan Hu
Chemical Physics
Nonadiabatic couplings drive ultrafast, mode-selective intramolecular vibrational energy redistribution in flavins
Daniel Timmer, Krishan Kumar, Jan P. Götze et al. (+3 more)
Flavins are the chromophores in several blue-light-sensitive photoreceptor
proteins and act as redox cofactors in many enzymes relevant for biological processes. Despite their biological relevance and numerous, detailed optical investigations of their photophysical properties, the ultrafast nonequilibrium dynamics of their elementary optical excitations are not yet fully known. Here, we use ultrafast coherent vibrational spectroscopy with 10-fs time resolution in the 450-nm spectral range to study their excited state coherent vibrational dynamics. We observe that coherent wavepacket motion along high-frequency C-C stretching modes with ~ 20-fs period is rapidly damped on a 20-fs timescale. In contrast, coherent motion along several low-frequency modes persists much longer. We attribute this to a mode-selective intramolecular vibrational energy redistribution driven by nonadiabatic couplings between the optical bright state and a close-lying dark electronic state, in accordance with model calculations. Our results may be of relevance for the formation of long-lived radical pair states in
magnetic-field sensitive
proteins.
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All authors Daniel Timmer, Krishan Kumar, Jan P. Götze, Peter Saalfrank, Antonietta De Sio, Christoph Lienau
Optics
Pulse thermal imaging of FUHAO bronze artifact
Li Wang, Ning Tao, Wei Liu et al. (+5 more)
The accurate identification of historical restoration traces and material degradation is essential for the scientific preservation of ancient bronzes. In this study, the prestigious FUHAO bronze artifact (late Shang period, 13th-11th century BCE) was non-destructively examined using pulsed thermal imaging (PT). By combining single- and double-layer heat conduction models with Thermal
Tomography (TT), this approach allowed for precise spatial localization of repair crevices, patches, and filler materials, while also distinguishing restorative interventions from the original bronze substrate. The artifact was revealed to have been assembled from multiple fragments, exhibiting uneven surface corrosion and clear evidence of prior conservation. The results not only provide direct insights for conservation strategy and historical interpretation but also demonstrate the capability of pulsed thermal imaging as an effective diagnostic tool for the integrated surface and subsurface assessment of cultural heritage objects.
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All authors Li Wang, Ning Tao, Wei Liu, Xiaoli Li, Yi He, Xue Yang, Jiangang Sun, Cunlin Zhang
Optics
An Exact Energy Conservation Law for Magneto-Optical Nanoparticles
Jorge Olmos-Trigo
Energy conservation imposes fundamental bounds on the polarizabilities of nanoparticles (NPs). While such bounds are well established for isotropic and bianisotropic NPs, they remain unexplored for magneto-optical NPs. Here, we derive the exact energy-conservation law governing the electric and
magnetic dipolar response of axially symmetric magneto-optical NPs under general illumination conditions and arbitrary external
magnetic fields. Two central results follow from energy conservation: (i) purely magneto-optical scattering, where the non-
magnetic polarizability vanishes, is fundamentally forbidden, and (ii) strong magneto-optical scattering regimes, in which the magneto-optical polarizability dominates, are intriguingly allowed.
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Fluid Dynamics
Volume penalization method for simulating flows around a rotating solid with multiple reference frame and sliding mesh
Ming Liu and Yosuke Hasegawa
Despite the significant role of turbomachinery in fluid-based energy transfer, precise simulation of rotating solid objects with complex geometry is a challenging task. In the present study, the volume penalization method (VPM) is combined with multiple reference frame (MRF) and sliding mesh (SLM), respectively, so as to develop immersed-boundary approaches for simulating flows around a rotating solid. The level-set function is adopted to represent arbitrary geometries embedded in Cartesian grids. The VPM body-forcing terms in the momentum equation are proposed for MRF and SLM, respectively, so as to build unified governing equations for both fluid and solid regions. The flows around a rotating cuboid under various rotating speeds are simulated by the present schemes, namely, VPM with MRF, and VPM with SLM, and compared to corresponding simulations by the body-fitted method (BFM). The results suggest the relative deviations of predicted pressure drop and torque between the present VPM and BFM are around 5%, demonstrating the validity of the present VPM.
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Physics and Society · Cross-listed from econ.GN
The hidden structure of innovation networks
Lorenzo Emer, Anna Gallo, Mattia Marzi et al. (+3 more)
Innovation emerges from complex collaboration patterns - among inventors, firms, or institutions. However, not much is known about the overall mesoscopic structure around which inventive activity self-organizes. Here, we tackle this problem by employing patent data to analyze both individual (co-inventorship) and organization (co-ownership) networks in three strategic domains (artificial intelligence, biotechnology and
semiconductors). We characterize the mesoscale structure (in terms of clusters) of each domain by comparing two alternative methods: a standard baseline - modularity maximization - and one based on the minimization of the
Bayesian Information Criterion, within the
Stochastic Block Model and its degree-corrected variant. We find that, across sectors, inventor networks are denser and more clustered than organization ones - consistently with the presence of small recurrent teams embedded into broader institutional hierarchies - whereas organization networks have a neater role-based structures, with few bridging firms coordinating the most peripheral ones; still, both are characterized by the presence of local core-periphery structures. We also find that the discovered meso-structures are connected to innovation output. In particular, Lorenz curves of forward citations show a pervasive inequality in technological influence: across sectors and methods, both inventor (especially) and organization networks consistently show high levels of concentration of citations in a few of the discovered clusters. Our results demonstrate that the baseline modularity-based method may not be capable of fully capturing the way collaborations drive the spreading of inventive impact across technological domains. This is due to the presence of local hierarchies that call for the more refined tools of
Bayesian inference.
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All authors Lorenzo Emer, Anna Gallo, Mattia Marzi, Andrea Mina, Tiziano Squartini, Andrea Vandin
Physics Education
Systemically Designed Degrees for Real-World Challenges: A case study on Physics curriculum design at Loughborough University
M. J. Everitt, M. T. Greenaway, S. L. Bugby et al. (+1 more)
We present a ground-up redesign of the undergraduate physics degree at Loughborough University, driven by the principle of authenticity in academic and industrial practice. Departing from conventional incremental reforms, we adopt a systems-engineering approach to programme-level curriculum design, treating the degree as an integrated system with verifiable performance. This methodology aligns stakeholder-derived requirements with vertically-integrated threads in theory, computation, laboratory practice, and professional skills. We demonstrate that this approach enables students to achieve levels of disciplinary and cross-disciplinary competence beyond those typically expected at undergraduate level. Outcomes are supported by graduate destinations, enhanced student performance, and positive external evaluations, including national accreditation. Our results suggest that rigorous, system-level curriculum design can yield transformational gains in both capability and confidence.
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All authors M. J. Everitt, M. T. Greenaway, S. L. Bugby, S. N. A. Duffus
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Physically Unclonable Functions Based on Single-Walled Carbon Nanotubes: A Scalable and Inexpensive Method toward Unique Identifiers
Enrique Burzurí, Daniel Granados and Emilio M. Pérez
A physically un-clonable function (PUF) is a physical system that cannot be reproduced or predicted and therefore is a good basis to build security and anti-counterfeiting applications. The unclonability of PUFs typically stems from the randmoness induced in a system during sophisticated fabrication methods. It is precisely this built-in complexity the bottleneck hindering scalability and increasing costs. Here, we produce in a simple manner PUFs based on arrays of carbon nanotubes junctions simultaneously assembled by dielectrophoresis. We demonstrate that the intrinsic inhomogeneity of carbon nanotubes at the nanoscale, combined with the unpredictability introduced by
liquid phase-based fabrication methods results in unique electronic profiles of easily scalable devices. This approach could be extrapolated to generate PUFs based on other nanoscale materials
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Chemical Physics · Cross-listed from quant-ph
Autonomous Quantum Simulation through Large Language Model Agents
Weitang Li, Jiajun Ren, Lixue Cheng et al. (+1 more)
We demonstrate that large
language model (LLM)
agents can autonomously perform tensor network simulations of
quantum many-body systems, achieving approximately 90% success rate across representative
benchmark tasks. Tensor network methods are powerful tools for
quantum simulation, but their effective use requires expertise typically acquired through years of graduate training. By combining in-context learning with curated documentation and multi-
agent decomposition, we create autonomous AI
agents that can be trained in specialized computational domains within minutes. We
benchmark three configurations (baseline, single-
agent with in-context learning, and multi-
agent with in-context learning) on problems spanning
quantum phase transitions, open
quantum system dynamics, and photochemical reactions. Systematic evaluation using DeepSeek-V3.2, Gemini 2.5 Pro, and Claude Opus 4.5 demonstrates that both in-context learning and multi-
agent architecture are essential. Analysis of failure modes reveals characteristic patterns across models, with the multi-
agent configuration substantially reducing implementation errors and
hallucinations compared to simpler architectures.
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All authors Weitang Li, Jiajun Ren, Lixue Cheng, Cunxi Gong
Classical Physics
Discrete versus continuous – linear lattice models and their exact continuous counterparts
Lorenzo Fusi, Oliver Křenek, Vít Průša et al. (+3 more)
We review and study the correspondence between discrete linear
lattice/chain models of interacting particles and their continuous counterparts represented by linear partial differential equations. In particular, we study the correspondence problem for linear nearest neighbour interaction
lattice models as well as for linear multiple-neighbour interaction
lattice models, while we gradually proceed from infinite
lattices to periodic
lattices and finally to finite
lattices with fixed ends/zero Dirichlet boundary conditions. The whole study is framed as a systematic specialisation of
Fourier analysis tools from the continuous to the discrete setting and vice versa, and the correspondence between the discrete and continuous models is examined primarily with regard to the dispersion relation.
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All authors Lorenzo Fusi, Oliver Křenek, Vít Průša, Casey Rodriguez, Rebecca Tozzi, Martin Vejvoda
Computational Physics · Cross-listed from quant-ph
Computing Statistical Properties of Velocity Fields on Current Quantum Hardware
Miriam Goldack, Yosi Atia, Ori Alberton et al. (+1 more)
Quantum algorithms are gaining
attention in Computational Fluid Dynamics (CFD) for their favorable scaling, as encoding physical fields into
quantum probability amplitudes enables representation of two to the power of n spatial points with only n
qubits. A key challenge in
Quantum CFD is the efficient readout of simulation results, a topic that has received limited
attention in literature. This work presents methods to extract statistical properties of spatial velocity fields, such as central moments and structure functions, directly from parameterized ansatz
circuits, avoiding full
quantum state
tomography. As a proof of concept, we implement our approach for 1D velocity fields, encoding 16 spatial points with 4
qubits, and analyze both a sine wave signal and four snapshots from Burgers' equation
evolution. Using Qedma's error mitigation software QESEM, we demonstrate that such computations achieve high accuracy on current
quantum devices, specifically IBMQ's Heron2 system ibm_fez.
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All authors Miriam Goldack, Yosi Atia, Ori Alberton, Karl Jansen
Instrumentation and Detectors
Effect of hole pitch reduction on electron transport and diffusion: A comparative simulation study of Triple GEM detectors
Rajiv Gupta, Sunidhi Saxena and Ajay Kumar
Advances in fabrication techniques and high-performance electronics have facilitated the development of fine-pitch Gas Electron Multipliers (GEMs). Earlier experimental and simulation findings suggest that these reduced-pitch GEMs can outperform the standard configuration in terms of effective gain, collection efficiency, and position resolution. However, a noticeable fraction of avalanche electrons is lost within the GEM systems, resulting in a degradation of charge collection efficiency. Therefore, a comprehensive simulation-based study is essential to provide deeper insights into the extent of degradation and its contributing factors. In this context, we employ ANSYS and Garfield++ to model the Triple GEM detectors with reduced pitch sizes of 90 and 60 $\mu$m, and perform a comparative performance analysis with the standard configuration (pitch size: 140 $\mu$m). At first, the simulation framework is validated by comparing the results of the standard configuration with available experimental data and previously reported simulation outcomes. Despite the characteristic gain offset, the framework remains physically consistent and reliable in capturing microscopic avalanche dynamics, reproducing the experimental trend. Following validation, we investigate electron losses at the metal electrodes and within the Kapton holes, electron transmission through the transfer and induction regions, electron
diffusion on the induction electrode, and the overall collection efficiency. These parameters are analyzed as functions of GEM potential, outer hole diameter, inner hole diameter, Kapton thickness, metal thickness, and gas composition, thereby offering insights for designing efficient GEM detectors.
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Computational Physics
A volume penalization method for solving conjugate scalar transport with interfacial jump conditions
Ming Liu and Yosuke Hasegawa
Conjugate scalar transport with interfacial jump conditions on complex interfacial geometries is common in thermal and chemical processes, while its accurate and efficient simulations are still quite challenging. In the present study, a novel treatment of a two-phase interface in the volume penalization method, a kind of immersed boundary method, for solving conjugate scalar transport with general interfacial boundary conditions is developed. We first propose an interfacial treatment for solving an advection-
diffusion equation with a Neumann boundary condition, and then extend it to general conjugate scalar transport with both interfacial flux and scalar jumps. A one-dimensional
diffusion problem is solved to verify the present scheme and demonstrate the advantage of the present scheme in improving accuracy and unifying the governing equations in the two phases with an additional source term representing the local jump condition of the interfacial scalar flux. Then, the present scheme is further applied to fluid-solid coupled scalar
diffusion and advection-
diffusion problems with the scalar and its flux jumps across the interface. The simulation results of the present scheme generally show good agreement with reference results obtained by body-fitted mesh simulations with average relative deviations less than 3.0%.
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