Computational Physics
Intermittent Sub-grid Wave Correction from Differentiated Riemann Variables
Steve Shkoller
We introduce a low-cost every-$K$-step correction for one-dimensional Euler computations. The correction uses differentiated Riemann variables (DRVs) – characteristic derivatives that isolate the left acoustic wave, the contact, and the right acoustic wave – to locate the current wave packet, sample the surrounding constant states, perform a short Newton update for the intermediate pressure and contact speed, and conservatively remap a sharpened profile back onto the grid. The ingredients are elementary – filtered centered differences, local state sampling, a single Newton step, and conservative
cell averaging – yet the effect on accuracy is disproportionate. On a long-time severe-expansion
benchmark ($N=900$, $t=0.4$), intermittent correction drives the intermediate-state errors from $O(10^{-2})$ to $O(10^{-13})$, i.e. to machine precision. On a long-time LeBlanc
benchmark ($N=800$, $t=1$), the method crosses a qualitative threshold: one-shot final-time reconstruction fails entirely (shock location error $2.7\times 10^{-1}$), whereas correction every three steps recovers an almost exact sharp solution with contact and shock positions accurate to machine precision. The same detector-and-Newton mechanism handles two-shock and two-rarefaction packets without case-specific logic, with plateau improvements of four to sixteen orders of magnitude. In an unoptimized Python prototype the wall-clock overhead is below a factor of two even on the most aggressively corrected
benchmark. To our knowledge, no comparably lightweight fixed-grid add-on has been shown to recover this level of coarse-grid accuracy on the long-time LeBlanc and related near-
vacuum problems.
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Atomic Physics
Standalone optical frequency-offset locking electronics for atomic physics
K. Shalaby, T. Hunt, S. Moir et al. (+3 more)
We present a standalone frequency-offset locking system for controlling narrow-linewidth
lasers using off-the-shelf electronic components. We lock two frequency-doubled 1560 nm
lasers to a stable primary
laser operating at 780 nm via their optical beat note. This
radio-frequency beat note is fed through a broadband variable divider, a frequency-to-voltage converter, and a proportional-integrator controller to lock each follower
laser to a tunable offset frequency relative to the primary. This architecture provides a large capture range ($> 1$ GHz), fast response times ($< 1$ ms), and high linearity. We achieve a frequency resolution of 1.9 kHz and a short-term fractional frequency instability $10^{-11}/\sqrt{\tau \rm (s)}$ at 780 nm without the need for a dedicated, precise clock reference. We perform high-resolution spectroscopy of cold $^{87}$Rb atoms to demonstrate the tunability and precision of our locking system. We designed the system to be modular and extensible, making it applicable to a wide variety of atomic physics experiments, including
laser cooling, spectroscopy, and
quantum sensing with atoms, ions, and molecules.
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All authors K. Shalaby, T. Hunt, S. Moir, P. Trottier, T. Reuschel, B. Barrett
Plasma Physics
From the First to Subsequent Pulses: Evolution of Discharge inside a Preformed Bubble in Water
Yang Xia, Siyuan Liu, Zhanqiang Liu et al. (+2 more)
The
evolution of pulsed discharge behavior inside a preformed air bubble in water from the first to subsequent pulses was experimentally investigated using a synchronized needle to bubble system. A positive nanosecond high-voltage pulsed power supply, together with a pulse valve and ICCD imaging, was employed to generate reproducible preformed bubbles and to record the corresponding discharge development with good temporal synchronization. The results show that, although the preformed bubbles exhibit good repeatability in size and morphology under identical conditions, the first-pulse discharge inside the bubble remains highly
stochastic. The first discharge is predominantly corona-like and is not significantly affected by bubble size once the electrode is covered by the bubble. By varying the pulse width, the discharge inside the bubble was observed to evolve progressively from corona-like emission to streamer discharge, accompanied by increasing instability of the bubble interface. At sufficiently large pulse width and pulse number, bubble wrinkling and even rupture were induced. The effect of solution conductivity was also examined. Increasing conductivity significantly enhanced discharge intensity, enlarged the luminous region, and promoted streamer propagation along the inner bubble surface. At sufficiently high conductivity, the first pulse already produced strong discharge and rapid bubble rupture. In addition, the current amplitude and the energy dissipated per pulse increased with conductivity and pulse number. These results demonstrate that the discharge
evolution inside a preformed bubble is jointly governed by pulse history, pulse width, and solution conductivity, and that residual effects from previous pulses play an important role in the transition from the first pulse to subsequent discharges.
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All authors Yang Xia, Siyuan Liu, Zhanqiang Liu, Weishan Zhang, Zhihua Qi
Atmospheric and Oceanic Physics
Learning Data-driven Surrogate and Correction Models for Satellite Observations in Numerical Weather Prediction
Gian Luca Buono, Stefanie Hollborn, Roland Potthast et al. (+2 more)
Satellite observations play a critical role in numerical weather prediction where they are assimilated through an observation operator that maps model states to radiances. In the traditional Ensemble Kalman Filter, these observations are used to update the state by weighting their associated errors against model uncertainties to produce an optimal estimate. This process requires radiative transfer simulations for passive, downward-viewing satellite radiometers operating in the visible, infrared, and microwave spectra. Typically, such simulations rely on numerically integrating physical laws via models like RTTOV. In this paper, we introduce two machine learning surrogate observation operators inspired by modern computer-
vision architectures: First, a fully data-driven emulator of radiative transfer, and second, a hybrid incremental correction model that learns only the residual relative to RTTOV, thereby retaining established physics while enabling data-driven refinement in complex conditions such as cloud-affected situations. The residual formulation improves radiance accuracy (lower Root Mean Squared Error (RMSE) than the fully data-driven emulator and RTTOV) and adds only moderate computational costs to the assimilation step. Both models combine 3D convolutions for vertical profile encoding with a 2D U-Net operating on latitude-longitude grids, allowing joint learning of vertical structure, spatial correlations, and inter-channel dependencies. We further provide a theoretical justification for deploying the hybrid surrogate as an observation operator in data assimilation.
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All authors Gian Luca Buono, Stefanie Hollborn, Roland Potthast, Jörg Schäfer, Martin Simon
Optics
Mie-lithography: void-resonance-assisted femtosecond laser printing for deep-ultraviolet to near-infrared nano dispersion devices
Wei Gong, Zhen-Ze Li, Chang Yu et al. (+9 more)
Nanoscale control of optical dispersion is essential for applications ranging from miniaturized spectrometers to color printing, all of which demand broadband spectral tunability. However, the Kramers-Kronig relations impose a fundamental trade-off between dispersion and loss, strictly limiting the design ability of single-material devices across the deep ultraviolet (DUV) to near-infrared (NIR) regimes. Consequently, the fabrication of miniaturized dispersion devices heavily relies on costly nanofabrication or heterogeneous integration. Here we overcome these limitations by shifting the light-matter interaction from solid structure into air-filled voids. We introduce a fabrication strategy termed "Mie-lithography", in which
laser printed seed nanocavities excite Mie resonances in air and the resulting localized field enhancement drives the self-assembly of three-dimensionally tunable void-type optical resonators. Because the resonant modes are primarily confined within air voids, this architecture effectively alleviates material-imposed dispersion-loss constraints, allowing on-demand customization of the broadband spectral response. This approach could enable single-step, high-throughput (>= 10^6 pixels/s) printing of dispersion units with a resolution of 63,500 DPI. As a proof of concept, we demonstrate a single-material nano dispersion device for spectral encoding from 200 to 800 nm, with spectral reconstruction using a camera. Our approach can be extended into a platform for ultra-broadband (DUV-NIR) nano devices fabrication and design, opening avenues for high-pixel-density displays and miniaturized spectrometers.
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All authors Wei Gong, Zhen-Ze Li, Chang Yu, Zhen Wang, Han-Yue Fan, Yi Wang, Zhi-Hao Chen, Chun-Qi Jin, Yu-Hao Lei, Qi-Dai Chen, Lei Wang, Hong-Bo Sun
Computational Physics · Cross-listed from nlin.PS
A robust method to identify chimera states
S. Nirmala Jenifer, Riccardo Muolo, Paulsamy Muruganandam et al. (+1 more)
Chimera states are one of the most intriguing phenomena in nonlinear dynamics, characterized by the coexistence of coherent and incoherent behavior in systems of coupled identical oscillators. Despite extensive studies and numerous observations in different settings, the development of reliable and systematic methods to classify chimera states and distinguish them from other dynamical patterns remains a challenging task. Existing approaches are often limited in scope and lack robustness. In this work, we propose a method based on
Fourier analysis combined with statistical classification to identify chimera behavior. The method is applied to a system of topological signals coupled via the Dirac operator, where it successfully captures the rich dynamical regimes exhibited by the model. We demonstrate that the proposed approach is robust with respect to variations in network
topology and system parameters. Beyond the specific model considered, the framework provides a general and automated tool for distinguishing different dynamical regimes in complex systems.
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All authors S. Nirmala Jenifer, Riccardo Muolo, Paulsamy Muruganandam, Timoteo Carletti
Optics
Superbunched random fiber laser
Qiang Ji, Yuxi Pang, Weiming Zhang et al. (+4 more)
Photon superbunching, distinguished by second-order coherence values far exceeding the Gaussian thermal limit, represents a highly desirable resource for
quantum optics and correlation-based imaging technologies. However, existing approaches typically rely on fragile experimental platforms, inefficient nonlinear conversion processes, or mechanically complex optical architectures. Here, we demonstrate a fully fiber-integrated superbunched random fiber
laser (SRFL) in which intrinsic Rayleigh scattering cooperatively interacts with cascaded stimulated Brillouin scattering and quasi-phase-matched four-wave mixing to tailor extreme
photon statistics. The SRFL generates a multi-wavelength comb, in which individual spectral components exhibit widely tunable
photon bunching, with the second-order coherence g(2)(0) continuously controlled from ~1 to ~26 by tuning the pump power, spectral order and
diffusion length. Moreover, we establish a direct correlation between photonic phase transitions (quantified by the Parisi overlap order parameter) and the emergence of superbunching, thereby bridging macroscopic disorder physics and microscopic
photon statistics. Finally, we employ the superbunched emission for temporal ghost imaging, realizing high-fidelity temporal object reconstruction with a substantial reduction in required ensemble averaging. These findings validate random fiber
lasers as a robust, scalable, and integrated platform for generating extreme
photon statistics and unlock new avenues for correlation-enhanced photonic sensing and
quantum optics investigations in complex photonic systems.
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All authors Qiang Ji, Yuxi Pang, Weiming Zhang, Xian Zhao, Zengguang Qin, Zhaojun Liu, Yanping Xu
Atomic Physics
Theory Framework for Medium-Mass Muonic Atoms
S. Rathi, I. A. Valuev, Z. Sun et al. (+4 more)
We present a state-of-the-art theoretical approach for computing bound-state energies in muonic atoms, incorporating improved
quantum electrodynamics effects and
nuclear polarization corrections with a systematic assessment of theoretical uncertainties. Our approach is based on a combination of the $Z\alpha$-expansion and the all-order formalism (Furry picture) optimized for the medium-mass range $(3 \leq Z \lesssim 30)$ and guided by the accuracy requirements of modern muonic spectroscopy experiments. These calculations are directly relevant to ongoing and forthcoming measurements aimed at extracting
nuclear structure parameters, particularly
nuclear charge radii, with unprecedented precision.
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All authors S. Rathi, I. A. Valuev, Z. Sun, M. Heines, P. Indelicato, B. Ohayon, N. S. Oreshkina
Optics
Ultra-high THz-field-confinement at LaAlO3 twin walls
Jakob Wetzel, Javier Taboada-Gutiérrez, Matthias Roeper et al. (+13 more)
The control and steering of light at nanometre length scales is crucial for the development of both fundamental science and nanophotonic technologies. Recent advancements have been achieved by exploiting various crystalline anisotropies, allowing for subdiffractional and diffraction-less canalisation of energy. These studies in particular benefit from stacking and twisting of 2D materials, whereas corresponding capabilities of anisotropic bulk
crystals are rather unexplored. In this work, we show that ferroelastic twin walls - crystallographically perfect 2D-sheets that separate regions of differently oriented domains - in the distorted perovskite LaAlO3 provide a natural platform for broadband lateral confinement and superb canalisation of light at the nanoscale. Without fabrication processes, the electromagnetic fields localised at such walls exhibit lateral optical sizes up to 260 times smaller than the free-space wavelength. Depending on the adjacent domain orientation and frequency, the twin wall pattern preferentially concentrates or repels the electromagnetic energy, constituting a natural building block towards broadband MIR and THz nanophotonics for polaritonic circuitry.
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All authors Jakob Wetzel, Javier Taboada-Gutiérrez, Matthias Roeper, Felix G. Kaps, Giuliano Esposito, Drini Marchese, Robin Buschbeck, Pauline Lenz, J. Michael Klopf, Hans A. Bechtel, Stephanie N. Gilbert Corder, Jeremie Teyssier, Susanne C. Kehr, Lukas M. Eng, Alexey B. Kuzmenko, Samuel D. Seddon
Optics
Fabrication and study of femtosecond laser micromachined few-mode elliptical core waveguides
Prajal Chettri and Shailesh Srivastava
Femtosecond
laser micromachining (FLM) fabricated waveguides inherently form elliptical cores due to differences in focal spot size and the Rayleigh range of the microscope objective. Consequently, it is essential to study their propagation characteristics, which differ from those of conventional circular-core waveguides. In this work, we present the results of a parametric optimization of these waveguides to identify fabrication parameters that lead to minimal loss. A propagation loss characterization study revealed that, for a
laser wavelength of 1030 nm, a pulse width of $\sim$300 fs, a pulse energy of 600 nJ, a scan speed of 2 mm/s, and a repetition rate of 100 kHz, a transparent and micro-bubble-free waveguide with a propagation loss of $\sim$0.4 dB/cm was formed. The modal analysis further demonstrated that the V-number depends on the core aspect ratio. The waveguide modes were compared with computationally generated modes, revealing a correlation that aligns well with existing literature.
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Instrumentation and Detectors · Cross-listed from quant-ph
Hyperloss from coherent spatial-mode mixing in quantum-correlated networks
Stephan Grebien, Julian Gurs, Roman Schnabel et al. (+1 more)
Quantum-correlated networks distribute
quantum resources such as squeezed and entangled states. These states are central to modern
quantum technology, including photonic
quantum computing,
quantum communications, non-destructive biological sensing and gravitational-wave detection. Even for squeezed states of light - the most robust
quantum-correlated resource - loss-induced decoherence remains the dominant obstacle to strong
quantum advantage in in large-scale interferometric and networked
quantum systems. Common design assumption in these applications is treating mismatches between spatial modes as a small, incoherent loss. Here we show that this picture can fail: coherent spatial-mode mixing with higher-order spatial modes can produce an apparent loss exceeding 100% relative to the initial squeezing, a regime we term hyperloss. We experimentally demonstrate hyperloss in a minimal two-node
quantum network: with only 8% mode mismatch, a 5.8dB squeezed state is converted into an effectively thermal state with no quadrature squeezing, eliminating the
quantum advantage. Because the effect is coherent, it is controllable: lost correlations can be recovered by tuning differential spatial-mode phases (e.g., Gouy-/propagation-phase). We demonstrate this recovery experimentally, not only eliminating the hyperloss, but even significantly suppressing the mode mismatch loss, with 15%
geometric mismatch acting like only ~2.8% effective loss. Hyperloss is a design-limiting mechanism for all
quantum networks with squeezed light, from from photonic
quantum processors to large-scale interferometers and distributed
quantum-sensing networks. Our results provide a practical route to avoid hyperloss and turn mode mismatch into an explicit, phase-aware design parameter for future
quantum technologies.
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All authors Stephan Grebien, Julian Gurs, Roman Schnabel, Mikhail Korobko
Medical Physics
Fast undersampled dynamic MRI reconstruction using explicit representation learning with Gaussian splatting
M.L. Terpstra and C.A.T. van den Berg
Motivation: Quickly obtaining high-quality MRI from accelerated acquisitions is important to mitigate motion artifacts, maintain patient comfort, and improve clinical efficiency. Goals: To obtain high-quality dynamic MRI using efficient, personalized models. Approach: We propose a novel explicit representation learning approach using Gaussian splatting. Multiple Gaussian primitives are trained to represent the underlying tissue. We extend the Gaussian splatting framework to model anatomical motion, enabling learning an efficient, explicit representation of dynamic MRI. Results: Gaussian splats can be trained in 60s with 0.5ms/dynamic inference time. High-quality cardiac MRI is obtained at R=16. We show that the properties of the Gaussians directly encode physiological properties.
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Fluid Dynamics
Nonlocal energy transfer mechanism in three-dimensional quantum turbulence
Elliot Bes, Guillaume Balarac and Juan Ignacio Polanco
We investigate the kinetic energy cascade in zero-temperature
quantum turbulence. Using simple theoretical arguments and unprecedented numerical simulations, we unveil an universal mechanism transferring energy directly from large to very small scales, thus bypassing the Kolmogorov-like local energy cascade and resulting in nonclassical energy spectra. This mechanism rests both on the vast separation of scales typical of superfluid helium-4 flows and on the
alignment between
quantum vortices and large-scale velocity gradients, in direct analogy with
vortex stretching in classical flows.
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Optics
Bessel Gaussian Beam Propagation in a Thermally Induced Axially Varying GRIN Medium
Fatemeh Kalantarifard and Parviz Elahi
High power end pumped solid state
lasers often operate in regimes where pump induced heating creates a strong refractive index gradient (thermal
lensing) that governs resonator stability and mode quality. When the pump is absorbed according to the Beer Lambert law, the thermal load, and hence the GRIN strength, vary along the
crystal length, so the standard ABCD
matrix of a constant-gradient GRIN element is no longer directly applicable. Here, we derive a closed-form ABCD transmission
matrix for a thermally loaded
laser crystal pumped by atop-hat beam while explicitly accounting for axial absorption. Starting from the steady-state heat equation, we obtain the temperature field and the associated thermo-optic index profile. We then solve the paraxial eikonal ray equation analytically and express the transfer-
matrix elements in terms of Bessel and Neumann functions. The resulting
matrix is validated against the conventional slab product method and shown to recover the uniform-medium and constant gradient GRIN limits. Finally, we illustrate its utility by model ing Bessel Gaussian beam propagation through the axially varying thermally induced GRIN medium.
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Optics
Structured-light propagation in a medium with uniform torsion: polarization textures, geometric birefringence, and beam-resolved optical activity
Edilberto O. Silva
We investigate finite-width optical-beam propagation in a medium with uniform torsion described by the
geometric theory of a continuous distribution of screw dislocations. Starting from the Riemann–Cartan framework that yields torsion-induced circular birefringence for local plane waves, we construct a minimal paraxial beam model in which the same contortion-driven helicity splitting remains explicit. We show that uniform torsion breaks the degeneracy between the two circular-polarization sectors and induces a
geometric rotation of the polarization that scales with both the propagation distance and the radial position in the beam. As a consequence, a finite-width beam develops spatially varying polarization textures across its transverse profile, naturally described by the Stokes parameters. We introduce beam-level observables based on the integrated Stokes vector, the transverse inhomogeneity of the polarization texture, and the number of resolved radial polarization domains, thereby connecting the torsion parameter to experimentally accessible beam diagnostics. The paper combines two complementary levels of description: an analytic short-distance regime, used to isolate the
geometric mechanism, and full paraxial propagation including diffraction, used to test the robustness of the predicted textures. Within the cylindrically symmetric minimal model, the most robust structured-light signature of uniform torsion is beam-resolved polarization structuring, whereas strong orbital-angular-momentum conversion is not expected without additional azimuthal structure. We also identify the
geometric ingredient required for genuine torsion-assisted
spin–orbit conversion beyond the minimal radial model: an effective azimuthal
geometric connection.
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Optics
Stable (2+1)-dimensional soliton and breather molecules in a cold Rydberg atomic gas
Lu Qin, Hairu Zhai, Lu Liu et al. (+6 more)
We investigate the formation of stable (2+1)-dimensional spatial-domain optical
soliton molecules and breather molecules in a gas of Rydberg atoms, highlighting the role of the nonlocal nonlinearity, which is generated by the electromagnetically induced transparency in the Rydberg medium. The setting supports diverse species of large-size polygonal
soliton molecules, including rectangular and oblique rhombuses, checkerboard
cells, and hexagons. The analysis identifies two distinct formation regimes. In the case of moderately nonlocality, the long-range interactions alone stabilize the
soliton molecules in the static form. In contrast, in the strongly nonlocal regime, initially imposed rotation is required to generate a centrifugal force that counteracts the strong attraction, resulting in stably rotating
soliton molecules. The rotation period can be controlled by adjusting the system parameters. Furthermore, appropriate initial velocities can induce inherent breathing dynamics in the
solitons, leading to the formation of breather molecules. Tuning the initial velocity, one can control the
evolution of
soliton molecules and breather molecules and even realize their mutual conversion. Our study offers a new scheme for engineering
soliton molecules and breather molecules, and suggests new possibilities for the design of data processing and transmission in optical systems.
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All authors Lu Qin, Hairu Zhai, Lu Liu, Yingying Zhang, Zeyun Shi, Zunlue Zhu, Xingdong Zhao, Wuming Liu, Boris A. Malomed
Computational Physics
AMELI: Angular Matrix Elements of Lanthanide Ions
Reinhard Caspary
Matrix elements of spherical tensor operators are fundamental to analyzing lanthanide spectra in both amorphous and crystalline host materials. This work presents a comprehensive framework for calculating angular
matrix elements using a Slater determinant basis and their subsequent transformation to the traditional $LS$-coupling scheme using the classification introduced by Racah. While computationally demanding, this direct product-state approach is more universally applicable than conventional methods and remains well within modern desktop computing capabilities. We provide a concise set of general rules to calculate angular
matrix elements for virtually any spherical tensor operator within an $f^N$ configuration. Because these
matrices are mathematical constants independent of the host environment, they need only be calculated once. A comprehensive set of calculated
matrix elements for unit and angular momentum operators, alongside perturbation
Hamiltonians, is made available in the open-access repository AMELI. By utilizing exact arithmetic, AMELI eliminates the numerical artifacts and rounding errors inherent to conventional floating-point representations. This takes full advantage of the selection rules and
symmetry properties of each operator, resulting in a very compact data format due to the high sparsity of the
matrices and the small number of unique non-zero elements. While the evaluation of final physical observables requires subsequent numerical diagonalization, this foundational repository is intended to replace legacy tables currently used for semi-empirical calculations. Extensive quantitative comparisons to classic tables from Judd and Carnall are presented, and application examples are demonstrated using the open-source Python reference implementation YALIP.
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Chemical Physics
Suiren-1.0 Technical Report: A Family of Molecular Foundation Models
Junyi An, Xinyu Lu, Yun-Fei Shi et al. (+5 more)
We introduce Suiren-1.0, a family of molecular foundation models for the accurate modeling of diverse organic systems. Suiren-1.0 comprising three specialized variants (Suiren-Base, Suiren-Dimer, and Suiren-ConfAvg) is integrated within an algorithmic framework that bridges the gap between 3D conformational geometry and 2D statistical ensemble spaces. We first pre-train Suiren-Base (1.8B parameters) on a 70M-sample Density Functional Theory
dataset using spatial self-supervision and SE(3)-equivariant architectures, achieving robust performance in
quantum property prediction. Suiren-Dimer extends this capability through continued pre-training on 13.5M intermolecular interaction samples. To enable efficient downstream application, we propose Conformation Compression
Distillation (CCD), a
diffusion-based framework that distills complex 3D structural representations into 2D conformation-averaged representations. This yields the lightweight Suiren-ConfAvg, which generates high-fidelity representations from SMILES or molecular graphs. Our extensive evaluations demonstrate that Suiren-1.0 establishes state-of-the-art results across a range of tasks. All models and
benchmarks are open-sourced.
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All authors Junyi An, Xinyu Lu, Yun-Fei Shi, Li-Cheng Xu, Nannan Zhang, Chao Qu, Yuan Qi, Fenglei Cao
Optics · Cross-listed from cond-mat.mes-hall
Efficient photo-Nernst terahertz emission in single heavy-metal films
Lei Wang, Linxuan Song, Elbert E. M. Chia et al. (+5 more)
State-of-the-art metallic terahertz (THz) emitters rely predominantly on spintronic
heterostructures, where heavy metals serve as passive
spin-to-charge converters. Here, we demonstrate efficient THz radiation from standalone Pt nanofilms at cryogenic temperatures and under external
magnetic fields. The governing mechanism is identified as the ultrafast photo-Nernst effect, wherein a transient thermal gradient drives a transverse charge current. The THz emission polarity is directly dictated by the sign of the Nernst coefficient, as verified by the phase reversal observed between Pt and W or Ta. Remarkably, both thickness scaling and alloying-induced suppression of thermal conductivity independently amplify the single-layer emission to levels comparable with
benchmark spintronic
bilayers. These findings redefine the established role of heavy metals from passive
spin-sinks to active THz emitters, uncovering a universal emission paradigm applicable across diverse spintronic and
quantum materials.
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All authors Lei Wang, Linxuan Song, Elbert E. M. Chia, Peijie Sun, Jianlin Luo, Rongyan Chen, Yong-Chang Lau, Xinbo Wang
Computational Physics · Cross-listed from math.NA
A Novel Method for Enforcing Exactly Dirichlet, Neumann and Robin Conditions on Curved Domain Boundaries for Physics Informed Machine Learning
Suchuan Dong and Yuchuan Zhang
We present a systematic method for exactly enforcing Dirichlet, Neumann, and Robin type conditions on general quadrilateral domains with arbitrary curved boundaries. Our method is built upon exact mappings between general quadrilateral domains and the standard domain, and employs a combination of TFC (theory of functional connections) constrained expressions and transfinite interpolations. When Neumann or Robin boundaries are present, especially when two Neumann (or Robin) boundaries meet at a vertex, it is critical to enforce exactly the induced compatibility constraints at the intersection, in order to enforce exactly the imposed conditions on the joining boundaries. We analyze in detail and present constructions for handling the imposed boundary conditions and the induced compatibility constraints for two types of situations: (i) when Neumann (or Robin) boundary only intersects with Dirichlet boundaries, and (ii) when two Neumann (or Robin) boundaries intersect with each other. We describe a four-step procedure to systematically formulate the general form of functions that exactly satisfy the imposed Dirichlet, Neumann, or Robin conditions on general quadrilateral domains. The method developed herein has been implemented together with the extreme learning machine (ELM) technique we have developed recently for scientific machine learning. Ample numerical experiments are presented with several linear/nonlinear stationary/dynamic problems on a variety of two-dimensional domains with complex boundary geometries. Simulation results demonstrate that the proposed method has enforced the Dirichlet, Neumann, and Robin conditions on curved domain boundaries exactly, with the numerical boundary-condition errors at the machine accuracy.
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Chemical Physics
Molecular dynamics simulation of high slip flow of water confined between graphene nanochannels at experimentally accessible strain rates
Carmelo Civello, Luca Maffioli, Edward Smith et al. (+4 more)
The transient time correlation function method (TTCF) has emerged as a powerful methodology for accurately probing systems at low shear rates. In the present study, TTCF was used to evaluate the shear rate dependence of the slip length in a high-slip system consisting of water confined between
graphene walls at experimentally accessible shear rates, for which classical nonequilibrium molecular dynamics (NEMD) is unfeasible. The corresponding Navier friction coefficient was computed for all shear rates spanning six orders of magnitude and compared with the
equilibrium limit. We report for the first time NEMD results obtained at experimentally accessible shear rates using the TTCF approach for a system that has attracted significant interest over the past decades. The slip length calculated with TTCF is in good agreement with previous
equilibrium molecular dynamics simulations and experiments. Our aim here is to highlight the extraordinary power of TTCF, particularly for high-slip (low strain-rate) systems, and to verify that
equilibrium methods directly match NEMD measurements at experimentally accessible strain rates.
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All authors Carmelo Civello, Luca Maffioli, Edward Smith, James Ewen, Peter Daivis, Daniele Dini, Billy Todd
Chemical Physics
olLOSC: Unified and efficient density functional approximation to correct delocalization error in molecules and periodic materials
Yichen Fan, Jacob Z. Williams and Weitao Yang
Density functional theory (DFT) is the most promising method for calculating
quantum properties of molecules and materials at moderate and large scales. However, commonly used density functional approximations (DFAs) have systematic delocalization error, as demonstrated by underestimated band gaps, over-delocalized charges, and energy level misalignment at interfaces, which limits its quantitative prediction. Extensive efforts, such as the $GW$ approximation to many-body perturbation theory, system-specific tuning of DFA parameters, and correction functionals have been developed to address delocalization error. However, an accurate, efficient, and unified solution to describe total energy, charge density and band structure for both finite systems and materials is still not available. Building on the linear-response localized orbital scaling correction (lrLOSC), we introduce olLOSC: a localized orbital scaling correction with
curvature calculated by orbital-free electronic linear response. olLOSC has comparable accuracy to lrLOSC, but is much more computationally efficient. olLOSC corrects delocalization error - especially underestimated gaps, but also the total energy - both in molecules and in materials with small and moderate band gaps, within the same orbital-free approximation. Critically, with a a unified approximation, olLOSC opens the path for robust and efficient DFT applications across molecules, materials, and interfaces.
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Fluid Dynamics
Measurement of traveling pressure waves inside a droplet
Sayaka Ichihara, Samuele Fiorini, Yoshiyuki Tagawa et al. (+1 more)
Shock wave-droplet interactions have been receiving increasing
attention due to their relevance in aviation fuel combustion and minimally invasive medical treatments, yet quantifying them experimentally remains a challenge. In this study, we propose a background-oriented schlieren (BOS) technique for quantitative spatiotemporal measurements of shock wave-droplet interaction, employing a novel ray-tracing correction, a synchronization system, and a projected background.
Underwater shock waves propagating both inside and outside a millimetric perfluorohexane droplet immersed in water are experimentally measured. The quantified density-gradient and pressure fields are compared with numerical simulations, and the BOS measurements-including sound speeds, the shock-focusing location, and the maximum pressure-are found to be in close agreement with the numerical results. Notably, the technique successfully captures the phase shift before and after shock focusing that had previously only been hypothesized.
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All authors Sayaka Ichihara, Samuele Fiorini, Yoshiyuki Tagawa, Outi Supponen
Physics and Society
Scientific Research as a Weapon in Russia's Hybrid War in Europe: an Example of the Joint Institute for Nuclear Research in Dubna, Russia
Tetiana Berger-Hrynova
This paper examines how the Joint Institute for
Nuclear Research (JINR), an international organization formally committed to peaceful science, is deeply embedded in an ecosystem of military-industrial enterprises in the city of Dubna in Russia, contributing to training specialists and developing technologies used in Russia's military operations, including attacks on civilian facilities in Ukraine. It also shows how JINR collaborates with scientific institutions on the Ukrainian territories occupied by Russia, legitimizing the occupation and exposing international partners to legal and ethical risks. Despite these ties, JINR maintains broad international collaborations, allowing its scientists and engineers to access advanced technologies and indirectly support Russia's military capabilities, highlighting the need for greater awareness in the global scientific community and coordinated sanctions enforcement.
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Physics and Society
Industry Aware Firm Level Network Reconstruction
Mitja Devetak and Antoine Mandel
A number of recent contributions have put forward the topological structure of production networks as a key determinant of macro-economic dynamics. However, firm-to-firm production networks data is generally not available. Against this background, reconstruction method based on firms' size have been developed. This paper enriches this set of reconstruction methods by integrating input-output sectoral flows in the reconstruction process. We derive analytical expressions for the maximum
entropy solutions to the firm network reconstruction problem with sectoral input-output constraints, first for binary networks and then for weight reconstruction. We perform a numerical analysis comparing standard and input-output based reconstruction methods using Hungarian production network data. Our results show that adding input-output constraints substantially reduces deviations from the input-output structure compared with standard methods. Our augmented method provides an almost perfect fit to input-output data, though all methods have difficulties reproducing other structural characteristics.
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Biological Physics
$\pi$-Girsanov: A Generalized Method to Construct Markov State Models from Non-Equilibrium and Multiensemble Biased Simulations
Mingyuan Zhang, Yong Wang, Bettina G. Keller et al. (+1 more)
We introduce $\pi$-Girsanov, a new method for constructing Markov state models from biased enhanced-sampling molecular dynamics simulations based on Girsanov reweighting. The key idea behind this new method is to separate the reweighting of the stationary density from the reweighting of the correlation function. We evaluate the effectiveness of this approach on several analytical potentials and on a model biomolecular system, comparing its performance with the original method. Our results show that $\pi$-Girsanov not only improves the estimation in a single-ensemble setting, but also resolves key challenges in estimating transition
matrices from multiensemble and non-
equilibrium biased trajectories. Overall, $\pi$-Girsanov represents a substantial advance in kinetic reweighting, strengthening the connection between enhanced sampling techniques and Markov state modeling.
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All authors Mingyuan Zhang, Yong Wang, Bettina G. Keller, Hao Wu
Applied Physics
Real-space Hybrid Topological Singularities in Structured Elastic Waves
Tong Fu, Pengfei Zhao, Liyou Luo et al. (+5 more)
Real-space singularities govern a broad spectrum of wave phenomena, yet they remain largely unexplored in elastic wave systems. Here, we report hybrid topological singularities that emerge on the surfaces of finite-sized solids due to the full vectorial character of elastic waves. These textures fuse
spin-field singularities with displacement-field singularities and exhibit unique non-pairwise topological charge dynamics. Moreover, a subset of these singularities imprint dislocation lines onto the radiated acoustic field, generating robust acoustic
vortices in free space from an otherwise achiral source and structure. Our results establish elastic waves as a powerful platform for engineering real-space singularities and open avenues for singular phononics and the exploration of rich topological defects in elastic media.
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All authors Tong Fu, Pengfei Zhao, Liyou Luo, Zhiling Zhou, Dong Liu, Wanyue Xiao, Jensen Li, Shubo Wang
Accelerator Physics · Cross-listed from hep-ex
Study of the Run-3 muon flux at the SND@LHC experiment
The SND@LHC Collaboration
Long-range
muons produced in
proton-
proton collisions at the ATLAS interaction point constitute the primary background for
neutrino interaction searches at the SND@LHC experiment. This work presents a comprehensive characterization of the
muon flux throughout LHC Run-3, benchmarking Monte Carlo simulations against experimental measurements. Measured and simulated
muon rates agree within 10-15% across all Run-3 configurations. Following the substantial background increase in 2024 as a result of a beam optics change, the reversion to nominal optics in 2025 did not restore the 2022-2023 levels due to the unprecedented adoption of horizontal crossing in ATLAS. As enlightened by simulation results, the latter enhanced the contribution of high-angle
muons originating from diffractive
proton losses in the LHC Dispersion Suppressor region. Their identification enabled the design of mitigation strategies that were experimentally validated. The simulation framework was also applied to the future High-Luminosity LHC configuration, resulting in a considerable
muon rate rise, driven by both the planned luminosity increase and the enlarged magnet aperture. Nevertheless, the upgrade from emulsion films to silicon vertex detectors will preserve the efficiency of the experiment even in such a high-rate environment.
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Fluid Dynamics
NeuralFVM: Neural-physics-based Finite Volume Method for Turbulent Flows Using the $k$-$\omega$ Model
Tingkai Xue, Yu Jiao, Te Ba et al. (+9 more)
In this work, we develop a neural-physics solver based on finite volume method (FVM), namely NeuralFVM, for turbulent flows by implementing the standard $k$-$\omega$ model designed for efficient Graphics Processing Unit (GPU) execution. The governing equations for fluid flow and heat transfer are reformulated as local tensor operations using convolution-based stencil operators, which enables compatibility with deep learning libraries while preserving the conservative properties of the FVM. A key challenge in implementing the turbulent model within such a framework is the treatment of the stiff destruction terms in the $k$ and $\omega$ transport equations. To address this issue, an operator-splitting strategy is introduced in which the stiff destruction terms are handled semi-implicitly while the remaining terms are advanced explicitly. This formulation avoids global
matrix assembly and allows the entire solver to be implemented using local tensor operations. In addition, the pressure-velocity coupling is solved using a convolution-based
geometric multigrid
algorithm embedded within a neural network architecture. The resulting NeuralFVM solver is validated through comparison with simulations conducted using the commercial CFD software ANSYS Fluent for several channel-flow configurations and an indoor airflow scenario. The results demonstrate close agreement in velocity, temperature, and
turbulence quantities, confirming the accuracy of the proposed approach. The developed GPU framework achieves a speedup of around 19-46 times compared with its Central Processing Unit (CPU) counterpart under different meshes. Moreover, the proposed solver naturally integrates with machine learning workflows, providing a promising foundation for future data-driven
turbulence modeling and optimization.
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All authors Tingkai Xue, Yu Jiao, Te Ba, Jingliang Wang, Juntao Yang, Simon See, Boyang Chen, Claire E. Heaney, Christopher C. Pain, Chang Wei Kang, Mohamed Arif Bin Mohamed, Hongying Li
Chemical Physics · Cross-listed from cond-mat.soft
Emergent single-species non-reciprocity from bistable chemical dynamics
Jakob Metson and Ramin Golestanian
The appearance of emergent
symmetries in complex systems with components that can form composite units provides us with opportunities for design and control of exotic phase behaviour, for example by exploiting the dynamical
symmetry breaking associated with them. We present a novel mechanism for the emergence of non-reciprocal interactions in a single-species suspension of chemically active colloids made out of semi-permeable vesicles, which encapsulate enzymes that catalyze a non-linear chemical reaction. Bistable chemical dynamics enables the colloidal reaction chamber to act as a net producer or consumer of a chemical, depending on the selected values of the chemical concentrations inside and around it. Since the internal chemical state of the colloid depends on the dynamic chemical concentrations rather than the material parameters, two identically produced colloids can present different effective chemical interactions within the same system upon responding to the corresponding gradients via diffusiophoresis. Furthermore, the colloids can spontaneously and reversibly switch between being effective consumers or producers. As a consequence, the colloids can dynamically switch between ignoring, attracting, repelling, and chasing each other, in a non-reciprocal manner. This flexibility can be exploited by manipulation of tuning parameters to induce bifurcations in the chemical dynamics, resulting in a robust control over the interaction motifs, and rich emergent dynamics such as spontaneous many-body polar swarming.
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