Computational Physics
Load balancing for adaptive-precision interatomic potentials in materials science
David Immel and Godehard Sutmann
For atomistic molecular dynamics simulations, we consider a recently developed hybrid coupling between the highly accurate machine learning (ML)-based atomic cluster expansion (ACE) interaction model and a less precise (but about 1-2 orders faster) EAM potential, in order to leverage the performance bottleneck of pure ML potentials in a parallel computing environment. This spatial-temporal adaptivity has the potential for a speedup of more than an order of magnitude, that would be lost without a dynamic load-balancing strategy that becomes critical due to fluctuating potential contributions. We compare the load-balancing strategies of LAMMPS with load-balancing methods provided by the library ALL in adaptive-precision EAM-ACE simulations of a copper nanoindentation. For a regular-grid domain decomposition, the modified tensor method of the ALL library, which conserves the simplicity and transferability of the tensor method, significantly reduces the imbalance factor of the force calculation from 3.0 to 1.7 compared to the native load-balancing method of LAMMPS. A nearly perfectly balanced system with an imbalance factor close to 1.0 can be reached by load balancing an irregular grid of domains with the recursive bisectioning method of LAMMPS and with ALL's histogram method for a staggered grid of domains. Load balancing a staggered grid with ALL is found to be significantly faster than load balancing an irregular grid with the bisectioning method of LAMMPS, but the communication costs during a regular timestep are lower for the irregular grid of domains, as a lower surface-by-volume ratio of the domains is reached. Furthermore, we suggest a strategy to find the ideal load-balancing frequency for adaptive-precision simulations.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Nonempirical Time-Dependent Density Functional Theory Framework for Nonlocal Exchange–Correlation Potentials
Zhandos A. Moldabekov, Michele Pavanello, Thomas D. Gawne et al. (+2 more)
Advanced, orbital-dependent exchange–correlation (XC) functionals can significantly improve the description of electronic structural properties, but they substantially worsen spectral properties that are computed within standard linear-response time-dependent density functional theory frameworks. This is not a failure of the underlying Kohn-Sham states, but due to a formal inconsistency in the treatment of the dynamic density response when the non-locality of the XC potential is not taken into account consistently on the level of the full off-diagonal density
matrix. To avoid these complexities, we present a non-empirical additive correction $\Delta f_\textnormal{xc}(\mathbf{q},\omega)$ to the dynamic XC kernel that re-enforces the exact f-sum rule of the non-local KS
Hamiltonian within TDDFT. Comparing our new results against a representative set of accurate experimental measurements (ambient aluminum, silicon and carbon, as well as heated and compressed aluminum) reveals a dramatic improvement in all cases without any additional computational cost. The corresponding extension to the open-source GPAW code is made freely available online. We further investigate the implications of non-local pseudopotentials and show that the non-locality has an important, physically motivated effect that is indispensable to capture the correct plasmon dispersion in lieu of full all-electron simulations. In addition to being important for the estimation of a plethora of dynamic and spectral properties, our work constitutes an important step towards a universal XC functional that can be used to estimate all kinds of observables with high accuracy. Finally, we outline the potential utility of our framework for the development of advanced non-local XC functionals, and suggest a new way to rigorously verify non-local pseudopotentials against experimental measurements of collective excitations.
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All authors Zhandos A. Moldabekov, Michele Pavanello, Thomas D. Gawne, Jan Vorberger, Tobias Dornheim
Optics · Cross-listed from quant-ph
Filter-Free Indistinguishable Photon Generation from Continuous-Wave-Driven Integrated Microresonators
Ruiyang Chen, Sicheng Zeng, Yuan Chen et al. (+6 more)
Quantum networks require scalable
photon sources combining narrow linewidth, high efficiency, and high indistinguishability. Microresonator
photon-pair sources are promising candidates, yet a source-only description based on the joint spectral amplitude (JSA) predicts near-zero Hong-Ou-Mandel (HOM) interference visibility between
photons generated by independent, CW-driven microresonators. In this work, we show that the observed HOM interference is not determined by the JSA alone. By combining finite-time detection with cavity-enhanced spontaneous four-wave mixing, we characterize a detector-conditioned heralded state governed by the idler-
photon detection window. We further demonstrate that independently optimizing the idler and signal detection windows allows both heralded-
photon indistinguishability and intrinsic heralding efficiency to approach unity, without spectral filtering or complex source engineering. Utilizing integrated high-$Q$ silicon nitride microresonators, we achieve HOM visibilities of 0.992(8) and 0.942(12), without background subtraction, at fourfold count rates of 4.5(3) and 12.2(6) Hz, respectively. Our work establishes CW-driven high-$Q$ microresonators as a robust and scalable platform for
quantum-network primitives.
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All authors Ruiyang Chen, Sicheng Zeng, Yuan Chen, Sanli Huang, Zeying Zhong, Zhen Chen, Xue Bai, Yi-Han Luo, Junqiu Liu
Instrumentation and Detectors
Terahertz Radar Inversion for Range-Resolved Solids Concentration Profiling in Gas–Solid Flows
Philip Kjaer Jepsen, Albert Monteith, Diana Carolina Guío-Pérez et al. (+4 more)
A stable inversion method is developed to reconstruct millimeter-scale solids-concentration profiles in particulate suspensions from monostatic sub-terahertz frequency-modulated continuous-wave (FMCW) radar measurements. In industrial particulate flows, cumulative attenuation renders the direct inversion of the path-integrated volume-scattering radar equation ill-conditioned. The method resolves this by an ensemble-averaged Mie-scattering closure coupled to a stable backward-integration scheme, yielding an analytical solution for the range-resolved solids concentration without case-specific parameter fitting against reference concentration measurements. The required range-dependent system response is determined by absolute near- and far-field calibration via external substitution with an electrically large metallic sphere. The method was evaluated against solids-volume-fraction estimates derived from differential-pressure measurements in a 3.1 m-tall circulating fluidized-bed riser operated with ambient air and copper powder (median diameter 32.6 $\mu$m, density 8920 kg m$^{-3}$). The radar-derived and pressure-derived profiles agreed well across three superficial gas velocities producing distinct axial solids distributions, and the radar indicates sensitivity down to solids volume fractions of order $10^{-6}$.
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All authors Philip Kjaer Jepsen, Albert Monteith, Diana Carolina Guío-Pérez, Lars Ulander, Tomas Bryllert, Henrik Ström, David Pallarès
Atmospheric and Oceanic Physics
Disentangled Fingerprints suggest no historical weakening of Atlantic Overturning and Subpolar Gyre
Bahar Emirzade, Jade Ajagun-Brauns, Maya Ben-Yami et al. (+4 more)
The AMOC and the Subpolar Gyre are key components of the Earth's
climate system, both potentially prone to destabilization and abrupt shifts under anthropogenic forcing.Given the strong influence of the AMOC and the SPG on global
climate, detecting changes in their stability is of high importance, yet is hindered by the limited length of observational records.In the absence of long-term direct AMOC observations, several observation-based fingerprints of the AMOC have been proposed.However, existing fingerprints do not clearly distinguish between SPG and AMOC variability, instead reflecting an opaque mixture of dynamics from both systems.Here, we assess the performance of widely used AMOC fingerprints across CMIP6 models and compare them with statistically optimal fingerprints that we derive from sea surface temperature and salinity.We show that traditional AMOC fingerprints exhibit weak correlations with both AMOC and SPG strength.In contrast, our statistically optimal fingerprints, trained on pre-industrial control simulations, consistently outperform existing approaches across independent segments of piControl simulations and historical experiments.These fingerprints accurately reconstruct AMOC and SPG variability while minimizing overlap, enabling a clear separation between the two systems.Our results provide the first tailored observational fingerprints that robustly distinguish AMOC and SPG, demonstrating the potential of statistically optimized approaches to improve detection and attribution of changes in Atlantic circulation, including precursor signals of potential tipping behavior.Applying our approach to sea surface temperature observations, we find that our optimized fingerprints do not confirm the substantial AMOC weakening in the recent decades as suggested by traditional fingerprints, but also do not rule out a loss of stability.
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All authors Bahar Emirzade, Jade Ajagun-Brauns, Maya Ben-Yami, Sebastian Bathiany, Yechul Shin, Jong-Seong Kug, Niklas Boers
Optics · Cross-listed from quant-ph
Giant-atom-mediated photon blockade
C. Cui, W. Y. Hu, Y. Q. Ji et al. (+3 more)
Photon blockade is a phenomenon where the presence of system nonlinearity causes the output to consist of single
photons, which has been extensively studied in point atom systems, but it is barely explored in giant atom ones. In this paper, we propose giant atom-mediated
photon blockade scheme based on two cavities and three cavities systems with driving field applied to the first cavity. We show that simultaneous unconventional
photon blockades (UPBs) can not occur in the point atom system (the atom coupling only to the leftmost cavity) due to there always existing a cavity to have a single path. In contrast, the spatially extended nature of giant atom enables coupling to multiple cavities and allows for the introduction of a phase and coupling strength. Consequently, simultaneous UPBs in multiple cavities can be obtained due to the multipath destructive interference. Moreover, by manipulating the detuning, we observe simultaneous conventional
photon blockades (CPBs) in multiple cavities. Finally, we study simultaneous two-
photon blockades (2PBs) in point atom multiple cavities system.
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All authors C. Cui, W. Y. Hu, Y. Q. Ji, H. T. Cui, Yan-Hui Zhou, H. Z. Shen
Computational Physics
Braided endovascular implants for intracranial aneurysms: mechanics, hemodynamics, and clinical translation
Ratnadeep Pramanik, Duygu Dengiz, Mariya S. Pravdivtseva et al. (+9 more)
Endovascular implants prevent intracranial aneurysm rupture by altering the mechanical and hemodynamic environment at the aneurysm neck. Yet many in silico workflows prescribe or reconstruct the post-deployment geometry before computing flow, leaving unresolved the mechanics that create the clinically relevant interface. Here we review braided intraluminal flow diverters, intrasaccular devices, and emerging flow-disruption concepts across deployment mechanics, inter-wire and wire-wall contact, superelasticity, wall apposition, pore geometry, computational fluid dynamics, and fluid-structure interaction. We connect these modeling choices to neck coverage, malapposition, migration, deformation, and durability, and distinguish established evidence from mechanistic inference and prospective hypotheses. We argue that model fidelity should match the clinical question: prescribed or fast placement may support screening, whereas questions of coverage, apposition, compaction, and migration benefit from mechanically plausible deployment states. An interface-resolved mechanics-to-flow framework, supported by measurable validation targets and standardized reporting, could improve device design and enable more reliable patient-specific treatment planning.
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All authors Ratnadeep Pramanik, Duygu Dengiz, Mariya S. Pravdivtseva, Martin Frank, Ivo Steinbrecher, Prasanth Velvaluri, Matthias Mayr, Philipp Berg, Sylvia Saalfeld, Naomi Larsen, Olav Jansen, Alexander Popp
Atmospheric and Oceanic Physics
How Much Hyperspectral Information Does Chlorophyll Retrieval Really Need?
Abed Hammoud, Xuerong Sun, Bianca Champenois et al. (+1 more)
Satellite ocean color
algorithms translate water-leaving radiance into ecological information at spatial and temporal scales that cannot be achieved by field sampling alone. One important variable derived from water-leaving radiance is chlorophyll-a concentration ($\mathrm{CHL\text{-}a}$), a widely used indicator of phytoplankton biomass and physiology. Empirical
retrieval algorithms are commonly used for $\mathrm{CHL\text{-}a}$ estimation, but their performance can vary across sensors and optically diverse waters. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission provides unprecedented spectral resolution, expanding the visible spectral information available for ocean color
retrievals and raising a practical
algorithm design question: how can this fine resolution spectrum be used to derive the next generation of interpretable $\mathrm{CHL\text{-}a}$
retrieval algorithms? We use symbolic regression to identify sparse equations that estimate $\log_{10}(\mathrm{CHL\text{-}a})$ from multi- and hyperspectral remote sensing reflectances. The analysis first tests the standard multispectral ocean color
algorithm (OC3–OC6) inputs to ask whether symbolic regression recovers standard band ratio structure, then extends the search to hyperspectral PACE-like reflectances. The best expression discovered achieved a held out root mean square deviation of 0.253 in log$_{10}$ $\mathrm{CHL\text{-}a}$, compared with 0.307 for a fitted OC6
polynomial on the same split. Ablations showed that the predictive skill of hyperspectral models is almost 12% better than the best standard ocean color
retrieval models in root mean squared deviation against held out data. When evaluated by environmental regime, differences were larger for high-chlorophyll samples, which often represent turbid water conditions.
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All authors Abed Hammoud, Xuerong Sun, Bianca Champenois, Robert J.W. Brewin
Accelerator Physics
Heavy ion driven plasma wakefield acceleration with drift-like phase-shift acceleration scheme
Li Jiangdong, Xia Guoxing, Liu Jie et al. (+2 more)
Traditional
plasma density modulation schemes can extend the dephasing length but suffer from wakefield degradation as
plasma density increases. To address this limitation, a drift-like phase-shift acceleration scheme is proposed, introducing drift sections between
plasma cavities to enable controlled phase shifting and avoid dephasing. Idealized simulation results show that electrons are accelerated from 16 MeV to 700 MeV within 1.65 m with an energy spread of 5%. Furthermore, segmented simulations introducing realistic active
plasma lenses verify the practical feasibility of this scheme, electrons are accelerated up to 720.5 MeV with a reduced energy spread of 3.3% within 1.67 m. The
plasma wakefield maintains a robust amplitude throughout the propagation, suggesting the potential for continued acceleration beyond the simulated region. This scheme demonstrates a promising way to enable the witness beam to gain energy continuously from the tail to the head of the driver beam and provides a new approach for generating high-energy, high-quality beams in heavy ion driven
plasma wakefield acceleration.
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All authors Li Jiangdong, Xia Guoxing, Liu Jie, Li Guangxian, Yang Jiancheng
Chemical Physics
On-Water Surface Catalysis: From Hydrogen Bonding to Charge-Transfer Activation
M. Alaraby Salem and Thomas D. Kühne
On-water catalysis accelerates reactions between poorly soluble organic substrates in aqueous suspensions, but its molecular origin remains debated. This Account argues that hydrogen bonding and
proton transfer can both enhance charge-transfer stabilization between the organic reactants. Hydrogen bonds from surface water polarize the reacting complex, whereas protonation can perturb the same donor-acceptor interaction more strongly without requiring identical reaction pathways. We connect simulations of the water/vapor interface, finite-temperature cycloaddition studies, and energy decomposition analysis based on absolutely localized molecular orbitals. Dangling OH groups establish reactive contacts, but an increased transition-state hydrogen-bond count alone does not explain activation. Electronic analysis instead identified hydration-enhanced charge-transfer stabilization between organic partners by approximately 30%. Comparisons of related dienophiles, a protonated limiting model, and oxygen/sulfur substitution link substrate-dependent electronic response to hydration and bond formation. A hydration-induced charge-transfer response metric provides a testable molecular hypothesis, not a standalone measure of catalytic acceleration. Activation depends on differential stabilization of reactant and transition-state ensembles. Increasing the accessible reactive interface can amplify this local mechanism without requiring exceptionally strong additional electric fields, connecting conventional on-water chemistry with selected microdroplet reactions while distinguishing adsorption, concentration, and intrinsic molecular activation.
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Classical Physics
Impact of Phase Unwrapping on Multitarget Acoustic Lenses for Transcranial Holography
D. Attali, T. Tiennot, M. Tanter et al. (+1 more)
Acoustic lenses have been introduced recently to compensate for the phase distortions induced by the propagation across a human skull for ultrasonic deep-
brain stimulation in humans. In this study, we present bifocal lenses that compensate for human skull aberrations and allow simultaneous targeting of multiple structures deep in the
brain. We investigated the impact of phase unwrapping in the design of the lenses and how this process improves the distribution of pressure produced in N=5 human skulls for two different spatial arrangements of the targets. The results show that unwrapping the phase computed during the design increases the fidelity of the pressure field generated across the human skulls. The spatial precision is on average improved by 73%, and out of target energy deposition is on average reduced by 58%. The results presented in this study highlight the importance of phase unwrapping to optimize the safety and efficacy of future transcranial ultrasound stimulations targeting multiple regions.
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All authors D. Attali, T. Tiennot, M. Tanter, Jean-Francois Aubry
Atmospheric and Oceanic Physics
Butterfly Effect and the Kinetic Energy Cascade in Probabilistic Machine Learning Weather Prediction Models
Jiakai Chen, Joel Oskarsson, Simon Driscoll et al. (+1 more)
This study analyses kinetic energy (KE) spectra, difference kinetic energy (DKE) spectra, and signatures of KE transfer across spatial scales in four state-of-the-art probabilistic machine learning weather prediction (MLWP) models: NeuralGCM-ENS, FourCastNet 3, AIFS-ENS, and GenCast. Results are compared with those from the physics-based numerical weather prediction model IFS-ENS. While NeuralGCM-ENS successfully reproduces the expected upscale transfer of KE, noise injection at its encoder stage underestimates mesoscale KE. Conversely, AIFS-ENS, GenCast, and FourCastNet 3 produce realistic KE spectral magnitudes but do not capture the expected upscale transfer of KE. In particular, AIFS-ENS and GenCast, which employ spatially uncorrelated
stochastic perturbations, exhibit enhanced accumulation of KE at high wavenumbers. All examined models exhibit upscale error growth, reflected by the progressive shift of the DKE spectral peak toward larger wavelengths over time. However, the MLWP models struggle to reproduce the rapid initial growth of ensemble spread at small spatial scales associated with the butterfly effect. The results show that MLWP models can misrepresent the known scale transfer of kinetic energy despite producing skilful weather forecasts.
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All authors Jiakai Chen, Joel Oskarsson, Simon Driscoll, Sebastian Schemm
Optics
350-GHz-Band 4 by 4 RTD Monostatic Radar Array for Sequential Multidirectional Ranging
Li Yi, Ryoma Nakamura, Shota Ito et al. (+6 more)
Terahertz (THz) sensing offers significant potential for nondestructive evaluation, imaging, and metrology, but the cost and complexity of existing systems remain barriers to practical deployment. This letter presents a compact 4 by 4 monostatic radar array based on a single-RTD-per-pixel architecture, in which each resonant tunneling diode (RTD) functions as both a bias-tunable oscillator and a self-mixing detector. The RTD elements are sequentially addressed through a low-frequency switching network and share the same baseband control and readout electronics. A shared 3D-printed dielectric lens maps the RTD elements to spatially separated sensing directions. We experimentally verify the operation of all array elements and demonstrate sequential multidirectional ranging using four selected elements, followed by preliminary 16-pixel THz imaging. By combining self-mixing at each pixel with low-frequency selection and shared optics, the array avoids a separate THz receiver chain for each pixel and provides a compact architecture for electronically addressable THz sensing and imaging.
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All authors Li Yi, Ryoma Nakamura, Shota Ito, Yousuke Nishida, Koji Terumoto, Toshihisa Maeda, Bryce Chung, Yunbin Jiang, Daniel Headland
Atomic Physics
Improved systematic uncertainty evaluation of the $^{171}$Yb optical lattice clock NMIJ-Yb1 with uncertainty of $2.6\times10^{-17}$
Takumi Kobayashi, Akiko Nishiyama, Ikuhiko Saito et al. (+4 more)
We report a systematic uncertainty evaluation of the $^{171}$Yb optical
lattice clock NMIJ-Yb1 (NMIJ: National Metrology Institute of Japan) with a fractional frequency uncertainty of $2.6\times10^{-17}$, improved by a factor of 3.8 compared with our previous uncertainty. The uncertainty of the
lattice light shift is reduced to $1.6\times10^{-17}$ by preparing axially sideband-cooled atoms in a shallow optical
lattice. Different models to calculate the
lattice light shift are compared, taking account of possible model-dependent biases due to the treatment of the radial motion of atoms trapped in the optical
lattice. The uncertainty of the blackbody radiation shift reaches $7.0\times10^{-18}$ by measuring the radiative temperature at the position of atoms with an in-
vacuum temperature sensor. We also demonstrate the nearly continuous operation of NMIJ-Yb1 with an uptime of 91.3 $\%$ for 10 days, showing the potential for future improvement of the calibration uncertainty of International Atomic Time.
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All authors Takumi Kobayashi, Akiko Nishiyama, Ikuhiko Saito, Daisuke Akamatsu, Akio Kawasaki, Shintaro Nagase, Masami Yasuda
Fluid Dynamics
Thicker Is Better: How Surfactant Viscosity Governs Uniform Surfactant Lung Delivery
Tristan Beuzelin, Matthieu Labousse and Marcel Filoche
Surfactant Replacement Therapy (SRT) is a well-established intervention for Neonatal Respiratory Distress Syndrome, yet its translation to adults with Acute Respiratory Distress Syndrome (ARDS) has yielded inconsistent results in clinical trials. Using a three-dimensional, zero-dimensional biomechanical model of surfactant bolus transport through the pulmonary airway tree, we demonstrate that, while the tree-like branching architecture of the lung gives rise to discrete flow regimes that result in spatially heterogeneous and inefficient drug delivery, surfactant viscosity is a key determinant of delivery homogeneity: below an analytically derived critical viscosity,
gravity causes complete surfactant exclusion from entire lung subregions regardless of dose volume. A clinically compatible tenfold to thirtyfold increase in viscosity above current formulations drives all bifurcation splitting factors toward the ideal even-split value of 0.5, enabling near-complete and spatially uniform coverage of terminal bronchioles in both infant and adult lung models. Principal component analysis across approximately 24 million simulations confirms that viscosity exerts the strongest positive influence on delivery homogeneity among all injection parameters, with dose volume being the primary determinant of efficiency. These findings provide a mechanistic rationale for reformulating exogenous surfactants with higher viscosity to improve SRT outcomes in adults.
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Physics and Society
Topological Uncertainty and Higher-Order Interactions in Spatial Networks
Domenico Pomarico, Alessandro Fania, Gabriel Ramirez Sanchez et al. (+16 more)
Environmental systems are characterized by complex spatial interactions that cannot be fully described through pairwise relationships or local uncertainty measures. We propose a unified framework combining higher-order information theory and topological data analysis to characterize the organization and uncertainty of environmental networks. Spatial entities, represented by monitoring stations or municipalities, are embedded into a Delaunay simplicial complex, and O-information is used to quantify redundancy and synergy among neighboring triplets. The resulting field of higher-order interactions is analyzed through persistent homology, enabling the identification of topological structures that remain stable across interaction scales. The methodology is applied to both an air-quality monitoring network based on weekly \(\mathrm{NO_2}\) and \(\mathrm{O_3}\) observations and a multi-hazard territorial assessment. We show that regions exhibiting strong O-information and persistent topological structures correspond to robust environmental patterns, whereas areas characterized by heterogeneous regimes and rapidly varying interactions display increased uncertainty. Building on these results, we introduce a topological uncertainty framework that integrates simplex divergence, higher-order interactions, and topological uncertainty. Our results demonstrate that uncertainty can be interpreted not only as statistical variability but also as the instability of the underlying information
topology. By integrating O-information and persistent homology within a common spatial framework, the proposed approach provides a new methodology for detecting robust higher-order structures and topologically uncertain regions in environmental and multi-hazard systems.
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All authors Domenico Pomarico, Alessandro Fania, Gabriel Ramirez Sanchez, Loredana Bellantuono, Domenico Capolongo, Roberto Cilli, Alessandra Costantino, Davide D' Alo, Mario Elia, Francesco Giordano, Niloofar Kheirkhahan, Raffaele Lafortezza, Raffaele Nutricato, Ester Pantaleo, Sabina Tangaro, Roberto Bellotti, Sebastiano Stramaglia, Alfonso Monaco, Nicola Amoroso
Chemical Physics
Attosecond Charge Migration Induced by Core-Level Ionization: A Relativistic Real-Time Time-Dependent Density Functional Theory Perspective
Torsha Moitra, Lukas Konecny and Michal Repisky
Core-ionization induced charge migration in molecular systems has been widely studied, but the influence of relativistic effects on such dynamics remains relatively unexplored from a relativistic theory perspective. This issue is particularly important because core orbitals exhibit strong scalar-relativistic and
spin-orbit imprints, and these effects are further enhanced in heavy-element systems, where relativistic signatures also alter the valence orbitals. To address this, we formulate four-component Dirac-Coulomb and two-component atomic mean-field exact two-component (and non-relativistic)
Hamiltonian approaches for studying charge migration within real-time time-dependent density functional theory. The time-dependent induced electric dipole moment is used as a marker of the characteristic charge-migration time scales. We apply the method to nitrosobenzene (N $1s$ electron removal), iodoacetylene (I $2p$ electron removal) and interhalogen series (I $2p$, Cl $2p$ electron removal). For iodoacetylene, the charge migration timescale is relatively insensitive to the choice of
Hamiltonian but they show weak relativistic phase and amplitude modifications. However, it would be misleading to conclude that relativistic effects are generally unimportant. In interhalogen systems, we observe significant deviations between relativistic and non-relativistic dynamics. These results demonstrate that relativistic signatures in core-ionization-induced charge migration are not determined by heavy-atom core ionization alone, but by the relativistic sensitivity of the valence orbital
manifold that drives core-hole screening and charge redistribution. Moreover, consistently across all systems, we observe a delay in the emergence of the relativistic imprints.
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Geophysics
A New Way for Determining Earthquake Magnitude Based on Electromagnetic Radiation
Manana Kachakhidze, Nino Kachakhidze-Murphy, Badri Khvitia et al. (+2 more)
The article proposes the possibility of determining the magnitude of a future earthquake with high accuracy, based on the frequency data of VLF/LF electromagnetic emissions, as a diagnostic precursor that existed before an earthquake. Such magnitude will contribute to significantly improving the research of various fundamental issues in seismology in the future.
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All authors Manana Kachakhidze, Nino Kachakhidze-Murphy, Badri Khvitia, Giorgi Ramishvili, Vaso Kukhianidze
Plasma Physics
X-Ray Spectroscopy for Characterizing Stimulated Raman Scattering in Inertial Confinement Fusion
Tianluo Luo, Zeyang Li, Yunping Wang et al. (+4 more)
Accurate characterization of stimulated Raman scattering (SRS) remains a critical challenge in inertial confinement fusion (ICF), as SRS not only scatters
laser energy but also generates suprathermal electrons that preheat the fuel and degrade implosion performance. Conventional backscatter diagnostics provide direct measurements of SRS but cannot collect the entire scattered-light signal, limiting the accurate characterization of SRS strength. Using a non-local thermodynamic
equilibrium collisional-radiative model with a double-Maxwellian electron distribution, we systematically investigate how suprathermal electrons modify the titanium K-shell x-ray emission spectra. The spectra exhibit high sensitivity to the suprathermal-electron fraction at relatively low bulk electron temperatures, making them particularly suitable for diagnosing suprathermal electrons during the early stage of ICF, when even a small suprathermal-electron population can compromise fuel compression. The calculated spectra reproduce experimental measurements from the Nova
Laser Facility with good agreement, and the inferred suprathermal-electron fractions show improved consistency with independently measured SRS losses compared with the original spectral analysis by Glenzer~\href{https://doi.org/10.1103/PhysRevLett.81.365} {\text{[S. H. Glenzer et al., Phys. Rev. Lett. 81, 365(1998)]}}. These results demonstrate that K-shell spectroscopy, combined with accurate NLTE collisional-radiative modeling, provides a reliable probe of SRS strength in
laser-produced
plasmas. Hence, this approach may be extended to spatially resolved diagnosis of SRS strength, offering a promising complement to conventional backscatter diagnostics.
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All authors Tianluo Luo, Zeyang Li, Yunping Wang, Zhihao Yang, Zhencen He, Dong Yang, Zhimin Hu
Fluid Dynamics
Shape considerations in wave-driven propulsion
Daire O'Donovan and Graham P. Benham
At the fluid surface, an asymmetric wave field generated by an oscillating body produces thrust in what is known as wave-driven propulsion (WDP). Although this thrust is directed forward, the vertical oscillations inevitably produce waves radiating outwards in all directions. The effect of these side waves is not accounted for in simplified models focused on the fore–aft wave field. In this work, we take a two-dimensional shallow water approach, deriving thrust and power expressions that account for surface waves emitted in any direction. Supported by an analytically driven approach, we pose a numerical optimisation problem to maximise thrust, imposing appropriate Sommerfeld boundary conditions across subcritical and supercritical velocity regimes. The two-dimensional set-up allows us to understand how the side waves emitted by the body contribute to thrust and efficiency. Furthermore, we explore how maximal thrust depends on the shape of the body beginning with a square followed by ellipses of varying aspect ratios. Using these learnings, we include the shape of the body as a control variable to demonstrate how an optimised shape can lead to further thrust and efficiency gains.
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Computational Physics · Cross-listed from math.NA
Constrained weak identification of Allen–Cahn free energies with surface-tension calibration
Soobeen Jung and Hyunju Kim
Phase-field trajectories governed by the Allen–Cahn equation determine the effective force $G=F'/\eps^2$, but not the free-energy potential $F$ and interfacial scale $\eps$ separately. We introduce surface-tension-calibrated Allen–Cahn identification (STAC), a two-step method that resolves this ambiguity using an independently supplied surface tension. First, space–time weak moments produce a linear inverse problem without differentiating the measured field. A Bernstein representation with positive coefficients enforces two stable pure phases and a single central energy maximum. Second, the surface tension fixes the remaining scale algebraically. We prove scale equivalence of the forward model, uniqueness of the calibrated pair within this class, and finite perturbation bounds that remain valid when the potential vanishes at the pure phases. Experiments with resolved synthetic phase fields separate the effects of the structural constraint, ridge regularization, and constitutive approximation error. Across 80 shared noisy records, unconstrained degree-five regression produces six potentials with an incorrect well structure. Positivity combined with ridge regularization eliminates these violations and reduces the mean force error from 8.70% to 5.66%. Lower-degree models are nevertheless more accurate in some tests, and an admissible law outside the positive Bernstein family shows how the constraint can introduce approximation bias. STAC thus recovers a structurally admissible, physically scaled potential while making explicit which information comes from the observed dynamics and which comes from the independent surface-tension datum.
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Fluid Dynamics
Vertical transport and confinement of weakly buoyant particles in a convective ocean mixed-layer model
Luz Andrea Silva-Torres, Enrico Calzavarini and Stefano Berti
Understanding how particles such as microplastics and plankton spread, or accumulate in localized regions below the ocean surface is crucial both for the development of sea pollutant control strategies and for marine ecology. Yet the role of vertically inhomogeneous
turbulence, due to the vertical structure of density stratification in the ocean, remains poorly understood. We study, by means of direct numerical simulations, the dynamics of weakly inertial, quasi-neutrally buoyant particles in an idealized two-layer fluid model aimed to represent the ocean convective mixed layer and the more stably stratified upper thermocline beneath. We find that particles eventually rise at the surface if their density matches the mean value of the fluid at a selected depth within the mixed layer. Interestingly, however, for all other values of density, they accumulate around their neutral-buoyancy depth within the thermocline, where stratification hinders vertical transport. Our analysis shows that the thickness of the accumulation layer results from the competition between buoyancy-driven confinement, internal-wave motions, and turbulent fluctuations penetrating from the mixed layer. Smaller particles, which respond more rapidly to flow fluctuations, form broader layers; layers also broaden as their
equilibrium depth approaches the mixed layer. We then derive a reduced
stochastic model that explains the dependence on particle inertia and reference depth of such spreading around the
equilibrium position. These results show how the coupled action of stratification and decaying mixed-layer
turbulence controls subsurface particle-layer formation, which may be relevant to ocean-biology oriented studies and to improve the sampling of plastic pollution in the sea.
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Computational Physics
Moment-informed force rescaling for random-batch Langevin dynamics
Xingguo Wu, Yangshuai Wang and Zhenli Xu
Random-batch methods accelerate molecular dynamics by replacing full interaction sums with
stochastic force
estimators. In Langevin simulations, however, random-batch force errors can cause artificial heating and distort
equilibrium and dynamical observables, especially for small batch sizes or under weak thermostat coupling. Moreover, the magnitude of these errors can vary across particles. We introduce moment-informed force rescaling for random-batch list (Mi-RBL) and random-batch Ewald (Mi-RBE) methods. A lagged average of each particle's sampled-force intensity sets an isotropic gain before the current batch is sampled, changing the random-batch force magnitude without changing its direction. The formal finite-time analysis quantifies the bias–variance tradeoff, and an estimate of the steady-state kinetic-temperature error predicts the scaling of the kinetic error with time step and thermostat friction. In the coexistence, binary-mixture, and electrolyte tests, Mi-RBL and Mi-RBE reduce kinetic errors and more closely reproduce the mean-square displacement, radial distribution function, and charge density profiles of the reference solutions. Mi-RBE also reduces the growth rate of the kinetic error with the time step by more than half and retains the predicted dependence on thermostat friction. The tested rescaling strength decreases with increasing batch size, and the particlewise update retains $O(N)$ complexity for fixed batch size.
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Instrumentation and Detectors
On the importance of cosmic-ray background in the Atomki anomaly
Hicham Benmansour, Gianluigi Boca, Gianluca Cavoto et al. (+8 more)
We report Geant4-based simulations of
cosmic-ray
muon backgrounds in models reproducing the geometries of the five-arm and six-arm e+e- pair spectrometers operated by the Atomki group at Debrecen. Full detector geometries are implemented for both setups, including position-sensitive detectors and plastic scintillators. In both configurations,
cosmic muons generating two-arm coincidences produce statistically significant excesses in the opening-angle distribution whose positions are determined by the discrete azimuthal arrangement of detector arms and the plastic scintillators dimensions: in the six-arm spectrometer a peak appears near 140 degrees when the scintillator energy sum is selected in the 8Be transition window (16-20 MeV) and is suppressed for energy-asymmetric pairs, while a distinct peak near 120 degrees emerges in the 4He window (18-22 MeV), with no comparable enhancement in the respective background energy region. These angles, asymmetry dependences, and background characteristics show behaviours similar to those reported by the Atomki group as evidence for a 17 MeV
boson. For the five-arm setup, a 140-degree excess is also reproduced at 8Be energies, and normalizing internal pair conversion events and
cosmic coincidences to typical Atomki running conditions yields a
cosmic-to-IPC ratio above unity in the signal window, indicating that the
cosmic background is a leading contribution to the event rate at the energies and angles of interest. While they do not settle the question of the origin of the Atomki excesses, these results highlight the critical importance of a robust
cosmic-ray treatment in this type of measurements, and call for a detailed description of the beam-off studies supporting the search for anomalies in the opening-angle vs. energy-sum distribution around the signal region.
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All authors Hicham Benmansour, Gianluigi Boca, Gianluca Cavoto, Marco Chiappini, Elia G. Grandoni, Luca Galli, Giovanni Gallucci, Angela Papa, Francesco Renga, Antoine Venturini, Cecilia Voena
Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Every Fixed Metric Has a Blind Spot: A Learned Atmospheric Critic for Scoring Forecast Realism
Younes Elberkennou, Dmitri Demler, Thierry Meier et al. (+3 more)
Despite their high accuracy on point-wise metrics, machine learning weather forecasting models can exhibit different failure modes such as blurring, periodic irregularities, and other unphysical spatial artifacts. This has motivated a variety of metrics to detect known failure cases. Existing metrics fix a representation or transformation in advance, and that choice limits the artifacts they can detect. We propose to train a discriminator for separating reference data from the model's output, and using its output logit to obtain a divergence-like realism score. The discriminator learns whatever separates the model's fields from real weather, adapting to whichever failure mode that model exhibits. We compare our learned atmospheric critic to existing metrics using various synthetic corruptions applied to ERA5 reanalysis data. Our method successfully identifies the corruptions and ranks their severity, while existing metrics fail on at least one corruption. Additionally, we evaluate forecasts from real weather models, and find that the realism score degrades with longer lead times and the metric generally assigns higher realism to numerical models than to machine learning models.
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All authors Younes Elberkennou, Dmitri Demler, Thierry Meier, Luca Rispoli, Fanny Lehmann, Joel Oskarsson
Optics
Multi-contrast wide-field mid-infrared photothermal imaging
Anooj Thayyil Raveendran, Cornelia Reuter, Samir F. El-Mashtoly et al. (+2 more)
Wide-field mid-infrared photothermal (MIP) imaging enables high-speed, chemically specific imaging at sub-micrometer spatial resolution through several possible contrast mechanisms, including scattering change, fluorescence modulation, and phase change. Each mechanism offers distinct advantages, yet existing wide-field MIP instruments have typically been limited to a single contrast mechanism so far, requiring a dedicated instrument for each. Here, we introduce a switchable multi-contrast wide-field MIP microscope that allows the photothermal readout mechanism (based on scattering-, fluorescence-, or quantitative phase imaging (QPI)) to be matched to the sample and imaging conditions. We characterize the spectral fidelity and signal-to-noise (SNR) ratio of each mechanism using 5 \mu m polystyrene (PS) beads, and the effective spatial resolution using 300 nm PS beads. Scattering- and fluorescence-based detection achieved a sub-500 nm measured point spread function full width at half maximum, while QPI-based detection reached approximately 900 nm but provided up to 26-fold higher SNR than scattering. We further demonstrate imaging across a range of samples, including A549
cells in buffer, mouse lung tissue section, bacteria, and SU8
polymer at 1.4 and 5 \mu m thickness, with a field of view exceeding 200 \mu m. Comparison across these samples shows that each contrast mechanism offers distinct trade-offs in resolution, sensitivity, and applicability, guiding readout-strategy selection by sample type. These results establish a flexible, switchable multi-contrast platform for wide-field MIP imaging, with broad applicability across
polymer and biological samples.
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All authors Anooj Thayyil Raveendran, Cornelia Reuter, Samir F. El-Mashtoly, Jürgen Popp, Christoph Kraft
Applied Physics
A Scaling Framework for Mechanical Memristance: Dimensionless Metrics and Material Design Maps
Abdulla Alhembar, Fabrizio Scarpa, Chrystel D. L. Remillat et al. (+6 more)
Mechanical memristors are systems whose dissipative response depends on the history of previous loading through an evolving internal state. History-dependent forces and dissipation occur in a wide range of materials and devices, including viscoelastic
polymers, shape-
memory materials, piezoelectrics, granular media and field-responsive fluids. Determining which of these responses admits a mechanical-memristor representation requires a constitutive test, as well as a comparison of scales. In this work, a fractional-order mechanical memristor model is developed and cast into a nondimensional form to identify the governing parameters controlling
memory-dependent dissipation. The formulation leads to a set of dimensionless groups that characterise dissipation magnitude,
memory-state scale and
memory transfer. These quantities are combined into an effective mechanical memristance screening index \(\Mh = \beta\gamma |\mathcal H_\alpha(\Omega)|\), which provides a conditional measure of local damping modulation at matched response amplitude, constitutive slope and reference scales. Illustrative parameter scenarios are then constructed for material classes including shape-
memory polymers, shape-
memory alloys, hydrogels, nanocellulose, lignin-rich materials, natural fibres, piezoelectric
polymers, piezoelectric ceramics, electrorheological fluids, magnetorheological fluids and granular dampers. The framework establishes a common basis for comparing
memory-dependent damping within the adopted constitutive description and identifies the calibration required for its application to candidate materials and devices
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All authors Abdulla Alhembar, Fabrizio Scarpa, Chrystel D. L. Remillat, Rodrigo J. da Silva, Ross Anderson, Ludovico Cademartiri, Abderrezak Bezazi, James P. K. Armstrong, Adam W. Perriman
Optics
Topological photonic cavities based on dissimilar Bragg gratings
Alejandro Sánchez-Sánchez, José Manuel Luque-González, Gauthier Krizman et al. (+12 more)
Topological photonic cavities offer a powerful route to robust optical confinement and enhanced light-matter interactions. Interface states that emerge at the boundary between one-dimensional periodic structures with distinct topological phases, enable cavities with ultra-small mode volumes and intrinsic protection against disorder. Existing implementations typically create the trivial and topological phases by redefining the unit
cell on either side of the cavity, so that both periodic structures share the same band structure. This constraint limits design flexibility and the range of accessible devices. Here we introduce a fundamentally different strategy for realizing topological cavities based on combining periodic waveguides with distinct band structures. By exploiting bandgap closing and band inversion in Bragg gratings, we independently control the topological phase and bandgap width of each structure. We experimentally realize silicon topological cavities formed by two different Bragg gratings without period shifting, and observe topological modes despite significant differences between the two gratings. Our results establish a new route to topological photonic cavity design, demonstrating that band inversion between dissimilar Bragg gratings enables cavity formation beyond symmetric constraints and provides a mechanism to engineer optical confinement via mirror asymmetry.
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All authors Alejandro Sánchez-Sánchez, José Manuel Luque-González, Gauthier Krizman, Dorian Oser, Paula Nuño Ruano, David González-Andrade, David Medina Quiroz, Samson Edmond, Alejandro Ortega-Moñux, Jens H. Schmid, Pavel Cheben, Laurent Vivien, Iñigo Molina-Fernández, J. Gonzalo Wangüemert-Pérez, Carlos Alonso-Ramos
Optics · Cross-listed from quant-ph
Optical Quantum Computing
Hamza Hasnaoui, Leonardo Limongi, Taira Giordani et al. (+5 more)
Under the label of optical
quantum computing, there are a variety of protocols and experiments that use the
quantum properties of light to achieve a computational advantage over classical computing machines. In this review, we describe some of the main implementations, which differ in the type of encoding and in how the computation is performed, whether using gates or cluster states. For each protocol, we describe advantages and challenges with an overview of the experimental results obtained, summarized in tables. Because of the great relevance achieved in this field, there is a section dedicated to non-universal
quantum computation with
photons, where
boson sampling, variational
quantum eigensolvers, and
quantum machine learning applications are described. The aim is to give the reader the broadest overview of the applications where
photons and their
quantum properties play a key role in computation.
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All authors Hamza Hasnaoui, Leonardo Limongi, Taira Giordani, Beatrice Polacchi, Alberto Quaranta, Martino Bernard, Fabio Sciarrino, Mirko Lobino
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Quantum electrodynamics of equilibrium systems: A rigorous Maxwell-regularized functional-theoretic formulation
Markus Penz, Christian Jöns, Michael Ruggenthaler et al. (+1 more)
A framework for
quantum electrodynamics of
equilibrium systems is proposed that takes the Maxwell equations as foundational and links them to the structure of density-functional theory for the
quantum system. By switching from purely internal observables like the one-particle density to combined internal and external quantities, the external sources and their energy are taken into account. A fully regularized functional theory emerges that avoids the usual representability problems. With the Kohn-Sham construction that links to an auxiliary uncoupled system, the ultra-violet cutoff can be removed and one arrives at a fully renormalized and non-perturbative light-matter description. Regularized forms of density-functional theory with and without
magnetic fields appear as boundary cases, while the emergent physical picture reproduces the macroscopic Maxwell equations.
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All authors Markus Penz, Christian Jöns, Michael Ruggenthaler, Angel Rubio