Showing 1–50 of 337 results for author: Xu, K

An asymptotic-preserving adjoint unified gas kinetic scheme for sensitivity analysis

Authors: Yue Zhang, Junzhe Cao, Wenpei Long, Kun Xu

Abstract: High-dimensional sensitivity analysis and uncertainty quantification for multiscale gas dynamics, spanning the continuum to rarefied regimes, require computationally efficient and mathematically consistent gradient evaluation. This paper develops a discrete adjoint method for the unified gas-kinetic scheme (UGKS) based on a dual-consistent formulation. The adjoint system is derived directly from t… ▽ More High-dimensional sensitivity analysis and uncertainty quantification for multiscale gas dynamics, spanning the continuum to rarefied regimes, require computationally efficient and mathematically consistent gradient evaluation. This paper develops a discrete adjoint method for the unified gas-kinetic scheme (UGKS) based on a dual-consistent formulation. The adjoint system is derived directly from the discrete microscopic velocity-distribution equation coupled with the macroscopic-moment compatibility conditions. To resolve the stiff cross-scale coupling, we propose an asymptotic-preserving (AP) adjoint formulation constructed via macroscopic-moment projection and microscopic lifting. Under this framework, the AP adjoint formulation eliminates the stiff collision coupling and removes the collision-time step restriction in the continuum regime. Numerically, a memory-efficient residual-evaluation algorithm that mirrors the forward UGKS cell-vertex data structure is implemented to bypass the memory bottleneck in velocity space. Furthermore, a macroscopic--microscopic predictor--corrector implicit marching scheme is designed to accelerate convergence without solving a globally coupled system. The accuracy, consistency, and robustness of the proposed AP-adjoint scheme are rigorously verified against an independent linearized UGKS solver across a wide range of Knudsen numbers, including lid-driven cavity heat conduction, microchannel thermal creep flow, and hypersonic flow past a circular cylinder. △ Less

Submitted 4 August, 2026; originally announced August 2026.

A Low-Storage Implicit Dual-Time Finite-Volume Framework for Radio-Frequency Capacitively Coupled Plasma Fluid Simulations

Authors: Yuze Zhu, Hangkong Wu, Junzhe Cao, Yufeng Wei, Kun Xu

Abstract: Radio-frequency (RF) capacitively coupled plasmas (CCPs) are widely utilized in semiconductor manufacturing. Efficiently and accurately solving the underlying fluid governing equations to resolve the complex multi-physics fields is crucial for optimizing plasma reactor designs and process control. To overcome the severe numerical stiffness and prohibitive time-step constraints inherent in low-temp… ▽ More Radio-frequency (RF) capacitively coupled plasmas (CCPs) are widely utilized in semiconductor manufacturing. Efficiently and accurately solving the underlying fluid governing equations to resolve the complex multi-physics fields is crucial for optimizing plasma reactor designs and process control. To overcome the severe numerical stiffness and prohibitive time-step constraints inherent in low-temperature plasma modeling, we present a robust, low-storage implicit dual-time finite-volume framework for RF CCP simulations, establishing a highly efficient and memory-friendly pathway for the predictive modeling of multi-dimensional low-temperature plasmas. In this approach, the physical time advancement is strictly decoupled from explicit stability limits through a backward-difference formula (BDF), while the resulting nonlinear system is efficiently solved using pseudo-time iterations. A localized block-implicit relaxation method is employed to handle the stiff transport and chemical source terms at the cell level, effectively circumventing the massive memory overhead typical of conventional fully implicit solvers. Concurrently, a semi-implicit treatment of Poisson's equation is integrated to accelerate the electrostatic coupling. The framework is first verified against a standard one-dimensional argon discharge benchmark, demonstrating that a highly accurate periodic state can be achieved with satisfactory computational efficiency through the optimal selection of the physical time step, pseudo-CFL number, and inner iteration step. To further demonstrate the multidimensional applicability of the proposed method, the solver is extended to genuine two-dimensional configurations. The numerical results show the multi-dimensional distortion of the electrostatic potential and localized electron heating zones induced by the transverse boundaries. △ Less

Submitted 20 July, 2026; originally announced July 2026.

Comments: 30 pages

An Implicit Time-Domain Harmonic Balance Method for Radio-Frequency Capacitively Coupled Plasma Simulations

Authors: Yuze Zhu, Yufeng Wei, Yue Zhang, Kun Xu

Abstract: Fast and accurate fluid simulation of radio-frequency capacitively coupled plasmas (RF CCPs) is of great importance for the iterative design and parameter optimization of modern plasma reactors. This study presents the first successful extension of the time-domain harmonic balance (HB) method to a fully coupled drift-diffusion-Poisson system with complete electron-energy transport for RF plasma si… ▽ More Fast and accurate fluid simulation of radio-frequency capacitively coupled plasmas (RF CCPs) is of great importance for the iterative design and parameter optimization of modern plasma reactors. This study presents the first successful extension of the time-domain harmonic balance (HB) method to a fully coupled drift-diffusion-Poisson system with complete electron-energy transport for RF plasma simulations. To resolve the severe numerical stiffness arising from highly nonlinear energy-dependent kinetics and dense phase-coupling, a highly efficient spatiotemporal operator-splitting strategy is employed. By sequentially executing a spatial implicit relaxation and a cell-local temporal inversion, this strategy entirely avoids the memory-intensive assembly of global Jacobians while preserving robust numerical stability. The proposed method is rigorously validated against a standard parallel-plate argon CCP benchmark. Evaluated across all discrete temporal collocation points, the HB solution demonstrates that retaining eight harmonics perfectly resolves both the quasi-steady bulk plasma and the highly nonlinear transient sheath dynamics, yielding macroscopic relative errors strictly below 0.3% compared to conventional dual-time stepping (DTS) solutions. Beyond its high physical fidelity, the time-domain HB method completely bypasses the prohibitive physical transients required by conventional time-marching methods. Evaluated on a purely sequential single-core execution, the HB method delivers a greater than 10-fold speedup over fully converged DTS baselines and remains over 5 times faster than the coarsest time-marching configurations. These results establish the time-domain HB framework as a physically rigorous, memory-efficient, and highly accelerated paradigm for practical RF plasma simulations. △ Less

Submitted 23 July, 2026; v1 submitted 20 July, 2026; originally announced July 2026.

Comments: 41 pages, 23 figures, research article

Modeling Equations in Wave-Particle Turbulence Simulation

Authors: Xiaojian Yang, Gaocheng Liu, Kun Xu

Abstract: Recently, the wave-particle turbulence simulation (WPTS) has been proposed as a novel framework for non-equilibrium turbulence modeling and simulation. In this work, for the first time the complete model equations of WPTS are explicitly derived from the perspective of wave-particle decomposition, and the physical mechanism of each term is clearly interpreted. To extend its applicability to wall-bo… ▽ More Recently, the wave-particle turbulence simulation (WPTS) has been proposed as a novel framework for non-equilibrium turbulence modeling and simulation. In this work, for the first time the complete model equations of WPTS are explicitly derived from the perspective of wave-particle decomposition, and the physical mechanism of each term is clearly interpreted. To extend its applicability to wall-bounded flows, the WPTS coupled with wall model is developed, and the introduction of wall model substantially alleviates the near-wall grid-resolution constraint. In the bulk region, the wave component resolves the large-scale structures, whereas the particle component accounts for subgrid-scale modeling through the non-equilibrium transport mechanism. As a result, the coupled method enables accurate predictions of the flat-plate transition on coarse-grid. In particular, the computed skin-friction coefficient and mean velocity profiles in the fully turbulent region agree well with the reference data from direct numerical simulation, and the accuracy is markedly superior to that of the gas-kinetic scheme (GKS) under the identical grid. These findings underscore the considerable promise of the multi-scale WPTS method for transitional flow simulations. △ Less

Submitted 11 July, 2026; originally announced July 2026.

Rigorously justified local time stepping in UGKWP method for steady multiscale flow simulation

Authors: Wenzhi Guo, Junzhe Cao, Wenpei Long, Kun Xu

Abstract: In this Letter, local time stepping (LTS) is incorporated into the unified gas-kinetic wave-particle (UGKWP) method for steady multiscale flow simulation. It accelerates convergence step by a factor of $3.8\times$--$20\times$ and reduces wall-clock time by up to $21\times$ relative to global time stepping (GTS). A rigorous analysis of the particle flux under LTS identifies that fixed per-cell as… ▽ More In this Letter, local time stepping (LTS) is incorporated into the unified gas-kinetic wave-particle (UGKWP) method for steady multiscale flow simulation. It accelerates convergence step by a factor of $3.8\times$--$20\times$ and reduces wall-clock time by up to $21\times$ relative to global time stepping (GTS). A rigorous analysis of the particle flux under LTS identifies that fixed per-cell as $Δt_i$ is a sufficient condition for the time-averaged flux balance. This condition has not been stated in prior particle-based LTS work, where $Δt_i$ varies in time and the flux balance is therefore not guaranteed. Together with proportional rescaling of particle mass and free transport time at cell interfaces, the fixed-$Δt_i$ condition yields a conservative framework with no free parameters. The UGKWP-LTS method is validated on cylinder and flat-plate benchmarks that possess multiscale flow features. △ Less

Submitted 10 July, 2026; originally announced July 2026.

Spatially variant arbitrary polarization shaping for optical skyrmions generation

Authors: Yu-Hao Lei, Zi-Ting Liu, Jun-Quan Guo, Xin Zhang, Minxin Ye, Qi-Dai Chen, Ke-Mi Xu, Shih-Chi Chen, Lei Wang

Abstract: Polarization is fundamental degree of freedom of light, crucial for applications from imaging to quantum optics. Although numerous methods can spatially manipulate the polarization orientation, e.g., for generating vector beam, achieving simultaneous, spatially resolved control of both the orientation (ψ) and ellipticity (\c{hi}) remains challenging. Here, we present an efficient and compact platf… ▽ More Polarization is fundamental degree of freedom of light, crucial for applications from imaging to quantum optics. Although numerous methods can spatially manipulate the polarization orientation, e.g., for generating vector beam, achieving simultaneous, spatially resolved control of both the orientation (ψ) and ellipticity (\c{hi}) remains challenging. Here, we present an efficient and compact platform to generate spatially variant arbitrary polarization states, e.g., optical skyrmions, in free space, using cascaded spatially variant waveplates in a single silica glass plate via ultrafast laser direct writing. We propose two configurations: (1) a spatially variant half-waveplate (S-HWP) and followed by a quarter-waveplate (S-HWP); and (2) two cascaded spatially variant quarter-waveplates (S-QWPs). Design rules linking the target polarization parameters (orientation ψ and ellipticity \c{hi}) to the fast-axis distributions enable spatially resolved arbitrary polarization control. Using these devices, we realize Néel-, Bloch-, and anti-skyrmions of different orders (e.g., second and fourth) and n-π textures (2π and 3π), with polarization-resolved measurements in excellent agreement with simulations. We further demonstrate 3 by 3 arrays comprising either identical or hybrid skyrmions. This approach enables the realization of spatially variant arbitrary polarization state and scalable skyrmion lattices. △ Less

Submitted 4 July, 2026; originally announced July 2026.

From Materials Database to Materials Bank: Assetizing Data for AI Driven Materials Innovation

Authors: Chenyao Ma, Di Zhang, Weibo Gong, Wei Du, Rui Su, Yuhang Chen, Kan Xu, Huan Gu, Limin Li, Piao Ma, Zhenghao Li, Hao Li

Abstract: Driven by high-throughput experimentation, computational modeling, and artificial intelligence (AI), materials data has expanded at an unprecedented rate. Conventional materials databases function only as passive repositories, archiving raw experimental records indiscriminately including both successful and failed data, without systematic value filtering or asset management. This creates a critica… ▽ More Driven by high-throughput experimentation, computational modeling, and artificial intelligence (AI), materials data has expanded at an unprecedented rate. Conventional materials databases function only as passive repositories, archiving raw experimental records indiscriminately including both successful and failed data, without systematic value filtering or asset management. This creates a critical gap between massive data accumulation and actionable innovation, hindering the identification of high-potential materials and industrial translation. To address this bottleneck, we propose an industrialization-oriented Materials Bank, a dedicated valuefiltering and assetization layer that operates beyond traditional databases. It does not merely curate high-quality data but systematically elevates qualified candidates into standardized, upgradable materials assets via a multi-dimensional BankCard framework covering scientific validity, synthesis feasibility, application readiness, and industrial value. By unifying databases, AI models, automated experimentation, and multi-criteria assessment into a cohesive closed-loop ecosystem, the Materials Bank establishes a clear trajectory from data to knowledge, candidate, asset, and product. It serves not as an enhanced database or screening tool, but as a decision infrastructure bridging academic discovery and industrial demand, offering a scalable paradigm to accelerate AI-driven materials innovation and deliver tangible real-world impact. △ Less

Submitted 25 July, 2026; v1 submitted 30 June, 2026; originally announced June 2026.

Journal ref: AI for Materials 2026, 1(1), 9

Efficient Wall-Modeled High-Order Compact Gas-Kinetic Scheme for Compressible Turbulent Flows

Authors: Yaqing Yang, Fengxiang Zhao, Kun Xu

Abstract: Scale-resolving simulations of wall-bounded turbulent flows remain prohibitively expensive at high Reynolds numbers, owing to the stringent near-wall resolution requirements. High-order compact gas-kinetic schemes (CGKS) are accurate, robust, and efficient for compressible flows, making them an attractive foundation for reducing this cost. Building on the fifth-order scheme CGKS-5th, we develop a… ▽ More Scale-resolving simulations of wall-bounded turbulent flows remain prohibitively expensive at high Reynolds numbers, owing to the stringent near-wall resolution requirements. High-order compact gas-kinetic schemes (CGKS) are accurate, robust, and efficient for compressible flows, making them an attractive foundation for reducing this cost. Building on the fifth-order scheme CGKS-5th, we develop a wall-modeled CGKS framework that alleviates the near-wall resolution burden through a pressure-gradient-based non-equilibrium wall model while preserving the resolving power of the outer solver. CGKS-5th resolves the outer flow and supplies the wall model with data at the exchange location. On coarse near-wall meshes, the wall model reconstructs the under-resolved viscous wall stress, while CGKS-5th provides the inviscid wall flux directly; the two combine to form the wall momentum flux. To capture non-equilibrium effects in adverse-pressure-gradient and separated regions, the wall model retains a pressure-gradient source term together with a pressure-gradient-corrected near-wall damping function. We assess the framework on two distinct flows: bluff-body separation past a circular cylinder, and a shock-induced separation bubble on the transonic RAE 2822 airfoil, using near-wall meshes far coarser than wall-resolved simulations require. For the RAE 2822 case, this corresponds to a twentyfold coarsening in the wallnormal direction, with comparable coarsening in other directions. In both cases, the wall-modeled CGKS-5th reproduces the separated flow structures and markedly improves near-wall predictions over its wall-model-free counterpart, most notably the skin-friction coefficient. The framework thus delivers accurate predictions of these separated flows at substantially reduced near-wall cost, while its lightweight coupling adds less than 1% runtime overhead in a multi-GPU implementation. △ Less

Submitted 29 June, 2026; originally announced June 2026.

A second-order unified gas-kinetic wave-particle method with enhanced mesh independence for hypersonic flows

Authors: Junzhe Cao, Rui Zhang, Wenpei Long, Chengwen Zhong, Kun Xu

Abstract: Benefiting from the direct modeling of physical laws in a discretized space and the automatic decomposition of the gas distribution function into hydrodynamic waves and particles, the UGKWP method offers significant advantages for multiscale flows such as hypersonic flows, plasma transport, and radiation transport. In this study, the particle sampling accuracy in the UGKWP method is improved from… ▽ More Benefiting from the direct modeling of physical laws in a discretized space and the automatic decomposition of the gas distribution function into hydrodynamic waves and particles, the UGKWP method offers significant advantages for multiscale flows such as hypersonic flows, plasma transport, and radiation transport. In this study, the particle sampling accuracy in the UGKWP method is improved from first order to second order, so that the second-order spatial and temporal accuracy is preserved across the full scheme. Specifically, the modifications include second-order particle sampling based on local macroscopic gradients, a weighted least-squares gradient reconstruction that incorporates wall values, a revised Venkatakrishnan limiter for highly stretched cells, and conservation corrections after particle sampling. Moreover, the first-order Chapman--Enskog term is considered in the free-transport part of the hydrodynamic wave flux, enabling better recovery of the GKS in the near-continuum regime. Based on these improvements, the mesh-independence behavior of the UGKWP method is notably enhanced, which is more consistent with the performance of the UGKS, validated by a detailed hypersonic cylinder flow test case. Furthermore, systematic comparisons with the single-scale DSMC method are performed for two-dimensional hypersonic flow over a cylinder and three-dimensional flow over a blunt cone. Wall pressure, shear stress, and heat flux coefficients (CP, CF, and CQ) are examined in the cylinder case, while the overall aerodynamic coefficients (CL, CD, and L/D) are assessed in the cone case. The multiscale UGKWP method exhibits significantly better mesh-independence performance than DSMC for mesh-sensitive quantities such as CF, CQ, CD, and L/D, which are critical for aerodynamic and thermal protection design of near-space hypersonic vehicles. △ Less

Submitted 29 June, 2026; originally announced June 2026.

Empowering Polymeric Materials Discovery by Artificial Intelligence

Authors: Chenyao Ma, Linda Zhang, Yuheng Chen, Wei Du, Shangwen Fang, Zihao Jiang, Chuanyu Liu, Xinyu Ma, Rui Su, Gang Wang, Muyao Yu, Dong Zhong, Jie Zhu, Weibo Gong, Huan Gu, Limin Li, Chen Shen, Rui Wu, Zhenghao Wu, Kan Xu, Min Zhou, Donglin He, Xiayun Huang, Shan Jiang, Pengfei Ou , et al. (7 additional authors not shown)

Abstract: Polymeric materials underpin modern technologies spanning energy storage, microelectronics, healthcare and sustainable manufacturing. Yet their rational design remains exceptionally challenging because material performance emerges from complex interactions among molecular composition, chain architecture, processing history and hierarchical structural evolution across multiple length and time scale… ▽ More Polymeric materials underpin modern technologies spanning energy storage, microelectronics, healthcare and sustainable manufacturing. Yet their rational design remains exceptionally challenging because material performance emerges from complex interactions among molecular composition, chain architecture, processing history and hierarchical structural evolution across multiple length and time scales. Consequently, polymer research has long relied on labor-intensive experimentation and fragmented modeling approaches, limiting both mechanistic understanding and innovation efficiency. Recent advances in data infrastructure, machine learning, large artificial intelligence (AI) models and laboratory automation are beginning to reshape this landscape. Rather than functioning as isolated tools, polymer databases, predictive models, AI agents and automated laboratories are increasingly converging into interconnected discovery ecosystems. As a result, the central challenge is shifting from improving predictive accuracy alone to enabling reliable decision-making, adaptive learning and seamless integration across computation, experimentation and scientific reasoning. We argue that polymer science is entering an era of autonomous discovery, in which data, simulation, reasoning and experimentation operate within self-improving feedback loops that continuously generate hypotheses, design materials, execute experiments and refine predictive models. By unifying molecular design, process optimization, experimental validation and industrial translation, such autonomous ecosystems establish a more predictive, reproducible and scalable paradigm for polymer innovation, fundamentally transforming how polymer research is conducted. △ Less

Submitted 16 August, 2026; v1 submitted 18 June, 2026; originally announced June 2026.

A symmetric relaxation method for entire two-dimensional cellular networks and its implications

Authors: Kai Xu, Lifan Weng, Zihan Wang, Yuyang Lian, Bin Huang

Abstract: To simulate the relaxation of an entire 2D cellular network, this study proposes a symmetric relaxation method for both inner and marginal vertices. The relaxations of these two types of vertices are determined by the central angle symmetry of associated cells and the angle symmetry at each vertex, but with different major considerations. Trimmed Voronoi networks with varying irregularity are used… ▽ More To simulate the relaxation of an entire 2D cellular network, this study proposes a symmetric relaxation method for both inner and marginal vertices. The relaxations of these two types of vertices are determined by the central angle symmetry of associated cells and the angle symmetry at each vertex, but with different major considerations. Trimmed Voronoi networks with varying irregularity are used as initial networks for the relaxation simulation. In particular, we propose a regular hexagon disordering method to generate Voronoi networks and find that the inner cells of networks with an irregularity value of one exhibit a conserved edge number distribution, as found in other 2D cellular networks. Simulation results agree with the von Neumann-Mullins law for both inner and marginal cells, and a modified equation including a geometric correction term significantly improves prediction quality. The Aboav-Weaire law and Lewis law are also reproduced, with the latter showing that relaxed cells tend to approach the ellipses' maximum inscribed polygons. Analysis of edge length, interior angle, and shape index reveals that symmetric relaxation inhibits T1 (neighbour exchange) topological transitions by reducing short edges while increasing area disparity among neighbouring cells. The findings suggest that T1 events may be triggered when force disequilibrium overcomes the stabilising effect of symmetric relaxation, providing a possible mechanistic explanation for T1 in 2D foams. △ Less

Submitted 16 June, 2026; originally announced June 2026.

A High-Precision Frequency Locking Method Based on All-Phase FFT Demonstrated on a Crystal Oscillator with Rubidium Clock Reference

Authors: Qibin Zheng, Kang Xu, Jiacheng Yang, Liguo Zhou, Li Ding, Xianfeng Jiang, Zhaohui Bu

Abstract: This article proposes a novel frequency-locking method based on frequency-domain unbiased phase estimation (FDUPE) for high-precision frequency control. By performing weighted recombination of the acquired data followed by Fourier-transform processing, the phase at the center of the data segment can be estimated without bias, making the method suitable for frequency-locking applications. The princ… ▽ More This article proposes a novel frequency-locking method based on frequency-domain unbiased phase estimation (FDUPE) for high-precision frequency control. By performing weighted recombination of the acquired data followed by Fourier-transform processing, the phase at the center of the data segment can be estimated without bias, making the method suitable for frequency-locking applications. The principle of the proposed method is analyzed, and an electronic prototype is developed to experimentally validate its feasibility. In the prototype, analog-to-digital converters (ADCs) are used for signal digitization, and a field-programmable gate array (FPGA) is used to implement the FDUPE algorithm. A digital proportional-integral-derivative (PID) controller is also implemented on the FPGA to provide feedback for accurate frequency locking. In the experiment, a (10~\mathrm{MHz}) voltage-controlled oscillator (VCO) with a free-running Allan deviation of (1 \times 10^{-9}) at (1~\mathrm{s}) is used as the device under test (DUT), while a rubidium atomic clock with an Allan deviation of (2 \times 10^{-11}) at (1~\mathrm{s}) serves as the high-stability reference source. Experimental results show that the proposed system achieves excellent locking performance, reducing the standard deviation of frequency fluctuations from (12.75~\mathrm{mHz}) root-mean-square (rms) in the free-running state to (0.88~μ\mathrm{Hz}) rms after locking. Correspondingly, the Allan deviation at (10~\mathrm{s}) is reduced from (9.6 \times 10^{-10}) to (1.45 \times 10^{-14}), representing a five-order-of-magnitude improvement in frequency stability. △ Less

Submitted 16 June, 2026; originally announced June 2026.

Comments: Submitted to IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

A GPGPU-Oriented Full Phase-Space Parallel Unified Gas-Kinetic Scheme with Velocity-Block Pipelining

Authors: Zhiwen Zhuang, Yixiao Wang, Xinhang Guo, Xing Ji, Xian Wang, Kun Xu

Abstract: The deterministic unified gas-kinetic scheme (UGKS) provides a multiscale framework for nonequilibrium gas dynamics, but its high-dimensional phase-space discretization leads to severe memory pressure and communication overhead, especially on large unstructured meshes. This paper presents a GPGPU-oriented UGKS with velocity-block pipelining and full phase-space MPI decomposition. In the proposed f… ▽ More The deterministic unified gas-kinetic scheme (UGKS) provides a multiscale framework for nonequilibrium gas dynamics, but its high-dimensional phase-space discretization leads to severe memory pressure and communication overhead, especially on large unstructured meshes. This paper presents a GPGPU-oriented UGKS with velocity-block pipelining and full phase-space MPI decomposition. In the proposed formulation, the discrete velocity space is partitioned into fixed-size velocity blocks for accelerator execution, while MPI ranks are organized into coupled physical-space and velocity-space communicators. As a result, each rank stores and advances only a local physical subdomain together with a contiguous subset of velocity blocks, and macroscopic moments are recovered through lightweight reductions over the velocity-space communicator. To improve concurrency and reduce exposed communication cost, a triple-buffered pipeline is further developed to overlap microscopic reconstruction, physical-halo exchange, nonequilibrium flux evaluation, and the first-stage distribution update during the local velocity-block sweep. The implementation targets SIMT-based GPGPU accelerators through a portable device-runtime abstraction. Numerical experiments demonstrate that the $P_v=8$ configuration achieves a $33.4$--$35.4\times$ strong-scaling speedup on 64 nodes, while an Orion-like capsule simulation reaches approximately $1.33\times10^{11}$ phase-space degrees of freedom on 4096 GPGPU accelerators. These results indicate that the proposed method preserves the original UGKS flux construction and two-stage time discretization, while substantially reducing microscopic storage per rank and improving the scalability of large unstructured phase-space simulations. △ Less

Submitted 14 June, 2026; originally announced June 2026.

Fermi gas of polar molecules in the Pauli-blocked regime

Authors: Junyu Lin, Annette N. Carroll, Phillip Martin, Calder Miller, Reuben R. W. Wang, Kevin Xu, John L. Bohn, Tim de Jongh, Jun Ye

Abstract: Quantum gases of polar molecules have recently emerged as a powerful platform for exploring exotic many-body dynamics and correlated quantum behavior. To achieve the full potential of this platform, the production of deeply degenerate quantum gases of molecules in arbitrary confinement geometries is necessary. Here, we successfully evaporate fermionic KRb molecules in both 3D and quasi-2D geometri… ▽ More Quantum gases of polar molecules have recently emerged as a powerful platform for exploring exotic many-body dynamics and correlated quantum behavior. To achieve the full potential of this platform, the production of deeply degenerate quantum gases of molecules in arbitrary confinement geometries is necessary. Here, we successfully evaporate fermionic KRb molecules in both 3D and quasi-2D geometries to well below their Fermi temperatures utilizing dipolar collisions. As we evaporate deeper into degeneracy in both geometries, we enter the Pauli-blocked regime with polar molecules, which we independently confirm for the first time by measuring the Pauli suppression of elastic collisions. Moreover, the Pauli suppression of collisions contributes to the limitation of our final molecular temperature to about 25% of the Fermi temperature in both geometries, particularly limiting quasi-2D evaporation where the Pauli blockade drastically reduces an otherwise large elastic to inelastic scattering ratio. This work demonstrates the production of degenerate Fermi gases of polar molecules both in a 3D harmonic trap and in mono- and bi-layer 2D configurations. Further, our work explores the fundamental limits on evaporation of molecular Fermi gases set by the Pauli-exclusion principle, which could be overcome in the future by introducing distinguishable scattering partners. △ Less

Submitted 12 June, 2026; originally announced June 2026.

Comments: 21+26 pages, 4+11 figures

An Implicit Discrete Adjoint Gas-Kinetic Scheme for Aerodynamic Shape Optimization across all Mach Number Regimes

Authors: Hangkong Wu, Yuze Zhu, Yajun Zhu, Kun Xu

Abstract: The gas-kinetic scheme (GKS) integrates the characteristics of flux difference scheme (FDS) and flux vector splitting (FVS) scheme, providing high accuracy in smooth regions and strong robustness near discontinuities across all Mach regimes. Leveraging these properties, an implicit discrete adjoint GKS is developed for aerodynamic shape optimization over a wide range of Mach numbers. The adjoint s… ▽ More The gas-kinetic scheme (GKS) integrates the characteristics of flux difference scheme (FDS) and flux vector splitting (FVS) scheme, providing high accuracy in smooth regions and strong robustness near discontinuities across all Mach regimes. Leveraging these properties, an implicit discrete adjoint GKS is developed for aerodynamic shape optimization over a wide range of Mach numbers. The adjoint solver is constructed using the source-transformation-based algorithmic differentiation tool Tapenade. To enhance computational efficiency, both the flow and adjoint GKS equations are solved using an implicit time-marching strategy, also known as the Lower-Upper Symmetric Gauss-Seidel (LU-SGS) method. The effectiveness of the implicit formulation is demonstrated through comparisons with the explicit approach. To accurately impose solid wall boundary conditions, particularly in hypersonic regimes, kinetic boundary conditions and their adjoint counterparts are formulated for both adiabatic no-slip and isothermal walls. Four benchmark test cases covering subsonic, transonic, supersonic, and hypersonic flows are used to verify the effectiveness of the developed adjoint-based design optimization system. △ Less

Submitted 12 June, 2026; originally announced June 2026.

Surrogate-Based Aerodynamic Shape Optimization in Multiscale Flows via the Implicit Unified Gas-Kinetic Scheme

Authors: Xiaozhe Xi, Wenpei Long, Wenzhi Guo, Junzhe Cao, Kun Xu

Abstract: While hypersonic glide vehicles such as the HTV-2 continue to be a focal point in aerospace research, their aerodynamic characteristics in complex near-space environments are not yet fully understood. Because traditional continuum assumptions fail to accurately capture multiscale flow features across varying rarefied altitudes, this study investigates the aerodynamic shape optimization of an HTV-2… ▽ More While hypersonic glide vehicles such as the HTV-2 continue to be a focal point in aerospace research, their aerodynamic characteristics in complex near-space environments are not yet fully understood. Because traditional continuum assumptions fail to accurately capture multiscale flow features across varying rarefied altitudes, this study investigates the aerodynamic shape optimization of an HTV-2-type aircraft across multiple flow regimes. An automated optimization framework is developed by coupling surrogate-based optimization (SBO) with the implicit unified gas-kinetic scheme (IUGKS). To ensure relevance to practical engineering requirements, both volumetric and center-of-pressure constraints are incorporated into the optimization process. The resulting optimized configurations are subsequently validated through high-fidelity computations, detailed flow-field evaluations, and global sensitivity analyses. Under volumetric constraints, the optimized lift-to-drag ratio ($L/D$) increases significantly at altitudes ranging from 70 km to 100 km. The optimal aerodynamic strategy is shown to shift with altitude: at 70 km, reducing the windward radius ($R_1$) weakens the oblique shock wave, whereas at highly rarefied altitudes, reducing the leeward radius ($R_3$) enhances the expansion wave. Correspondingly, sensitivity analyses confirm that as flow rarefaction increases, aerodynamic dominance shifts toward $R_3$. Furthermore, reducing the wingtip bluntness ($R_2$)yields consistent aerodynamic benefits across the entire flight envelope, ultimately driving the optimized geometries toward a flatter and more slender profile. △ Less

Submitted 30 May, 2026; originally announced June 2026.

On the Applicability of the Gas-Kinetic Scheme with Kinetic Boundary Conditions for Near-Continuum Hypersonic Flows

Authors: Wenpei Long, Junzhe Cao, Yue Zhang, Kun Xu

Abstract: Rarefied gas effects are of critical importance for the aerodynamic performance of hypersonic vehicles operating at high altitudes. In these scenarios, conventional computational fluid dynamics (CFD) solvers break down as the linear constitutive relations underlying the Navier-Stokes equations cease to be valid. Based on direct modeling, the unified gas-kinetic scheme (UGKS) and the unified gas-ki… ▽ More Rarefied gas effects are of critical importance for the aerodynamic performance of hypersonic vehicles operating at high altitudes. In these scenarios, conventional computational fluid dynamics (CFD) solvers break down as the linear constitutive relations underlying the Navier-Stokes equations cease to be valid. Based on direct modeling, the unified gas-kinetic scheme (UGKS) and the unified gas-kinetic wave-particle (UGKWP) method successfully capture non-equilibrium physics across all Knudsen numbers, yet they incur substantially higher computational costs than continuum solvers. Within the same kinetic framework, the gas-kinetic scheme (GKS) employs the Chapman-Enskog expansion for near-equilibrium flow physics and adopts the same kinetic boundary conditions as UGKS and UGKWP. This formulation naturally permits velocity slip and temperature jump, thereby extending the applicability of GKS into the slip and transitional regimes. By utilizing this natural kinetic slip boundary condition, the GKS provides a more physically faithful representation of non-equilibrium wall interactions than conventional CFD solvers equipped with Maxwell-type slip conditions, ultimately yielding more accurate aerodynamic predictions. To determine the applicability of the GKS in near-continuum flow regimes, we first examine a simple circular cylinder geometry, comparing surface quantities and distribution functions in detail. Furthermore, we investigate a 9°blunted cone, a 70° blunted cone with a cylindrical sting, and the Apollo 6 command module. This analysis focuses on integrated aerodynamic predictions, which are validated against experimental data, Direct Simulation Monte Carlo (DSMC) simulations, and other kinetic methods. △ Less

Submitted 22 May, 2026; originally announced May 2026.

Comments: 29 pages, 18 figures

A unified gas-kinetic wave-particle method for multiscale binary-species gas mixtures

Authors: Junzhe Cao, Yufeng Wei, Wenpei Long, Chengwen Zhong, Kun Xu

Abstract: This paper presents a unified gas-kinetic wave-particle (UGKWP) method for simulating multiscale binary-species gas mixtures. Benefiting from direct modeling in a discretized space, the UGKWP method enables the automatic decomposition of the gas distribution function into analytical hydrodynamic waves and discrete particles, which respectively describe its near-equilibrium and non-equilibrium part… ▽ More This paper presents a unified gas-kinetic wave-particle (UGKWP) method for simulating multiscale binary-species gas mixtures. Benefiting from direct modeling in a discretized space, the UGKWP method enables the automatic decomposition of the gas distribution function into analytical hydrodynamic waves and discrete particles, which respectively describe its near-equilibrium and non-equilibrium parts. This approach offers significant advantages for simulating various multiscale physical phenomena, such as hypersonic flows, plasma transport, and radiation transport. In this study, we employ the model proposed by Groppi et al. [EPL, 96 (2011) 64002] to calculate the macroscopic velocity and temperature of the local target equilibrium distribution function, thereby recovering the correct viscosity and diffusion coefficients in the continuum flow regime. To address the heat conduction coefficient, the Shakhov model is incorporated to correct the Prandtl number. Diffusion effects are accounted for not only in the source term via an operator-splitting method, but also in the flux evolution through the characteristic integral solution, while strictly maintaining consistency between the wave and particle descriptions. Furthermore, the microscopic model for high-speed particles is improved by utilizing a physically corrected collision time to determine their free-transport time. Through a series of numerical tests spanning the continuum to rarefied regimes, the proposed UGKWP method is shown to accurately capture the differences in velocity and temperature between different species. Notably, for hypersonic flows, the predicted wall pressure, shear stress, and heat flux coefficients agree well with DSMC results. △ Less

Submitted 21 May, 2026; originally announced May 2026.

Dynamically Reconfigurable Optical Skyrmions Enabled by a Silicon Microring Optical Phased Array for Robust Free-Space Communication

Authors: Zili Cai, Tian Zhang, Qi Chen, Zheng Wang, Jian Dai, Kun Xu

Abstract: Optical skyrmions offer a robust vectorial information degree of freedom for free-space communication, but practical deployment requires a compact platform capable of active topological reconfiguration. Here, we propose a silicon microring-resonator optical phased array that integrates spin-selective emission and programmable phase control on a single chip. Optimized inner- and outer-grating micro… ▽ More Optical skyrmions offer a robust vectorial information degree of freedom for free-space communication, but practical deployment requires a compact platform capable of active topological reconfiguration. Here, we propose a silicon microring-resonator optical phased array that integrates spin-selective emission and programmable phase control on a single chip. Optimized inner- and outer-grating microring emitters provide decoupled LCP and RCP radiation bases with polarization fractions of 90.27% and 91.40%, enabling active switching between Néel-type and Bloch-type skyrmions, while dynamically tuning the skyrmion number across Nsk =-1.914 to 1.918. Using these programmable topological states, a 4-symbol free-space communication link is constructed and compared with ideal LG-OAM encoding under Kolmogorov turbulence. The skyrmion-encoded link maintains a lower symbol error rate over a broader turbulence range, demonstrating that topological observables are more robust than scalar OAM modes. These results establish actively reconfigurable optical skyrmions as compact, programmable, and turbulence-tolerant information carriers for next-generation free-space optical communication. △ Less

Submitted 11 May, 2026; originally announced May 2026.

Information Extraction of Nested Complex Structure of Quantum Cascade Lasers via Large Language Models

Authors: Xiao Fang, Ming Lü, Hanwen Liang, Xingshen Song, Kele Xu, Hui Cai, Chaofan Zhang

Abstract: The rapid advancement of Large Language Models has transformed scientific research workflows, including enabling the automated extraction of data directly from published literature. Most existing efforts, however, focus on extracting simple labeled key-value entities, whereas many scientific applications require more complex, hierarchically structured data. A representative example is Quantum Casc… ▽ More The rapid advancement of Large Language Models has transformed scientific research workflows, including enabling the automated extraction of data directly from published literature. Most existing efforts, however, focus on extracting simple labeled key-value entities, whereas many scientific applications require more complex, hierarchically structured data. A representative example is Quantum Cascade Lasers, whose device architectures are defined by tens of interdependent parameters organized in nested layer sequences. In this work we propose a \emph{JSON-Schema Guided Information Extraction Pipeline} (JSG-IE) that enables reliable extraction of deeply structured device data without model fine-tuning. By transforming extraction into a schema-constrained generation task, our approach significantly improves structural consistency and accuracy. Across 12 state-of-the-art LLMs, a properly designed JSON Schema improves performance by 5.7\% over conventional prompting, with the highest $F_1$ score up to 83.4\%, achieved by the reasoning-enabled Kimi-k2-thinking model. Importantly, this performance enhancement is most significant for mid-tier and open-source models, where $F_1$ gains reach as high as 24.1\%, effectively enabling these widely accessible models to achieve extraction fidelity previously restricted to much larger architectures. This framework provides a scalable path toward automated construction of high-fidelity device databases, accelerating data-driven optoelectronic design. △ Less

Submitted 10 May, 2026; originally announced May 2026.

A Time-Domain Harmonic Balance Unified Gas-Kinetic Scheme for Temporally Periodic Flows Across all Knudsen Regimes

Authors: Yuze Zhu, Hangkong Wu, Yufeng Wei, Kun Xu

Abstract: This paper introduces a time-domain harmonic balance unified gas-kinetic scheme (HB-UGKS) designed to simulate temporally periodic flows across all Knudsen regimes. The harmonic balance approach reformulates the periodic problem into a block-coupled, quasi-steady system via a time-spectral source term. This allows for pseudo-time marching, local time-stepping, and the concurrent resolution of all… ▽ More This paper introduces a time-domain harmonic balance unified gas-kinetic scheme (HB-UGKS) designed to simulate temporally periodic flows across all Knudsen regimes. The harmonic balance approach reformulates the periodic problem into a block-coupled, quasi-steady system via a time-spectral source term. This allows for pseudo-time marching, local time-stepping, and the concurrent resolution of all sub-time levels, drastically reducing wall-clock time. Coupled with the UGKS-which maintains essential transport-collision coupling in its flux evaluations--the framework ensures multiscale validity across the entire Knudsen number range. The method is validated against two representative cavity flows. For a shear-driven oscillatory cavity under small-amplitude excitation, the fundamental harmonic alone accurately resolves the flow dynamics across various Knudsen and Strouhal numbers, successfully capturing the anti-resonance phenomenon and matching hydrodynamic damping predictions from linearized Boltzmann analyses. For a thermally driven cavity with large temperature modulations, higher-order harmonics prove essential to capture strong nonlinear waveform distortions and rarefaction effects. Beyond its physical fidelity, the HB-UGKS demonstrates substantial computational efficiency over explicit time-domain methods. This advantage peaks in high-frequency regimes, achieving speedup factors of 9.0 and 8.26 for the shear-driven and thermally driven cases, respectively. △ Less

Submitted 5 May, 2026; originally announced May 2026.

Comments: 33 pages, 34 figures

Hyperfine-resolved laser excitation and detection of nuclear isomer in trapped $^{229}$Th$^{3+}$ ions

Authors: Wu Wang, Ke Zhang, Ke-Mi Xu, Shan-Gui Zhou

Abstract: We present a comprehensive theoretical investigation of hyperfine-resolved excitation and detection of the low-energy isomeric state of $^{229}$Th in trapped $^{229}\mathrm{Th}^{3+}$ ions. Using a quantum master equation approach, we analyze the dependence of the isomeric population on laser linewidth, detuning, and irradiation time, showing that their proper matching is essential for efficient ex… ▽ More We present a comprehensive theoretical investigation of hyperfine-resolved excitation and detection of the low-energy isomeric state of $^{229}$Th in trapped $^{229}\mathrm{Th}^{3+}$ ions. Using a quantum master equation approach, we analyze the dependence of the isomeric population on laser linewidth, detuning, and irradiation time, showing that their proper matching is essential for efficient excitation. We further propose two nuclear-state detection schemes based on three hyperfine-resolved electronic fluorescence channels at 690, 984, and 1088 nm. Our analysis shows that the 690-nm and 984-nm scheme yields detectable photon rates on the order of $10^4~\mathrm{s}^{-1}$ per ion for each wavelength, whereas the 1088-nm scheme achieves a higher rate on the order of $10^5~\mathrm{s}^{-1}$ per ion. By quantifying the trade-off between irradiation time and scan-step size, we show that the nuclear transition can be located within one month for a 100-MHz uncertainty using currently available vacuum-ultraviolet laser technology. These results provide practical guidance for trapped-ion $^{229}\mathrm{Th}$ spectroscopy and the development of nuclear clocks. △ Less

Submitted 30 April, 2026; originally announced April 2026.

Comments: 12 Pages, 10 figures, and 2 tables

High-key-rate Fully-Passive Quantum Access Network with Thermal Source

Authors: H. W. Yin, B. D. Zhu, H. Peng, T. Wang, X. Q. Jiang, Y. K. Xu, G. H. Zeng

Abstract: To accommodate classical communication systems with progressively increasing transmission rates, quantum access networks (QAN) have undergone systematic and protocol-level optimizations in recent years, where quantum passive optical network (QPON) architectures are gaining significant attention due to their simple structure. It is challenging for the previous QAN based on active protocols or Stoke… ▽ More To accommodate classical communication systems with progressively increasing transmission rates, quantum access networks (QAN) have undergone systematic and protocol-level optimizations in recent years, where quantum passive optical network (QPON) architectures are gaining significant attention due to their simple structure. It is challenging for the previous QAN based on active protocols or Stokes operator coding protocols to achieve high-speed linear modulation with high extinction ratio and stability under practical conditions. In this work, we propose and experimentally demonstrate a downstream fully passive quantum access network protocol using passive state preparation (PSP) with free-space and single-mode fiber hybrid channels, and the final key generation rate is up to a record-breaking 19.48 Mbps per quantum network unit. The proposed PSP-QPON scheme extends the scope of PSP-CVQKD from point-to-point to point-to-multi-point networks, which enables high-key-rate, high-stability, and low-resource-consumption implementation. Moreover, the network channel in this experiment is fully compatible with access networks in classical optical communications, which allows integration with existing optical infrastructure without the need for additional modifications, providing a promising solution for local area network quantum access network at home or a mobile terminal. △ Less

Submitted 29 April, 2026; originally announced April 2026.

A Hybrid Gas-Kinetic Scheme and Discrete Velocity Method for Continuum and Rarefied Flows

Authors: Hangkong Wu, Yuze Zhu, Yajun Zhu, Kun Xu

Abstract: The gas-kinetic scheme (GKS) provides high computational efficiency and accuracy for continuum flow simulations but is unable to reliably capture rarefaction effects. In contrast, although the discrete velocity method (DVM) is better suited for rarefied flows, it exhibits reduced accuracy and slow convergence when applied to continuum regimes. To overcome these limitations, this work proposes a hy… ▽ More The gas-kinetic scheme (GKS) provides high computational efficiency and accuracy for continuum flow simulations but is unable to reliably capture rarefaction effects. In contrast, although the discrete velocity method (DVM) is better suited for rarefied flows, it exhibits reduced accuracy and slow convergence when applied to continuum regimes. To overcome these limitations, this work proposes a hybrid GKS-DVM method that integrates the strengths of both approaches. The hybrid approach balances the equilibrium distribution function in GKS with the upwind-reconstructed non-equilibrium distribution function in DVM through a numerical collision time. This balancing strategy ensures to recover Navier-Stokes solutions in the continuum limit (asymptotic preserving), while naturally capturing free molecular flows in the rarefied limit. Moreover, the introduction of a numerical collision time significantly enhances robustness in shock capturing for continuum flow applications. To further reduce computational cost of the hybrid approach, several adaptive strategies based on the local Knudsen number and Mach number have been proposed. The effectiveness and accuracy of the proposed hybrid method are systematically assessed through four representative test cases: a flat-plate boundary layer, a lid-driven cavity flow, shock structures, and flow past a semi-cylinder. The first case is subjected to continuum conditions, while the latter two span a broad range of Knudsen numbers. The results demonstrate that the proposed method achieves high solution accuracy and computational efficiency across both continuum and rarefied flow regimes. △ Less

Submitted 7 May, 2026; v1 submitted 29 April, 2026; originally announced April 2026.

Comments: 31 pages, 57 figures

Revisit viscous shock tube at low Reynolds number

Authors: Yue Zhang, Kun Xu

Abstract: The viscous shock tube is a canonical test case for assessing Navier-Stokes (NS) solvers in the continuum-flow regime, widely used to validate numerical accuracy and probe flow physics. It features a rich set of interacting structures-shock and rarefaction waves, contact discontinuities, boundary layers, and their coupling-spanning multiple spatial and temporal scales. However, NS-based modeling,… ▽ More The viscous shock tube is a canonical test case for assessing Navier-Stokes (NS) solvers in the continuum-flow regime, widely used to validate numerical accuracy and probe flow physics. It features a rich set of interacting structures-shock and rarefaction waves, contact discontinuities, boundary layers, and their coupling-spanning multiple spatial and temporal scales. However, NS-based modeling, which presumes near-equilibrium behavior, may fail to capture important non-equilibrium effects even in nominally continuum conditions. This study investigates the viscous shock tube at low Reynolds numbers and demonstrates the presence of non-equilibrium phenomena within the conventional continuum regime. To obtain physically consistent solutions across scales, we employ the unified gas-kinetic scheme (UGKS) and compare its results with NS solutions computed using the gas-kinetic scheme (GKS). Discrepancies between UGKS and GKS solutions reveal pronounced non-equilibrium effects in regions where shock waves interact with boundary layers. For continuum flows at high Mach and low Reynolds numbers, such multiscale non-equilibrium transport becomes important, underscoring the need for multiscale methods in analysis and prediction. △ Less

Submitted 25 April, 2026; originally announced April 2026.

Cross Fusion and Correlation Beamformer for Row-Column Array Based 3D Ultrasound Imaging

Authors: Qiandong Sun, Rui He, Shilin Hou, Jiyan Dai, Kailiang Xu

Abstract: Row column addressed (RCA) transducers present a promising solution for ultrafast volumetric imaging with a reduced channel count and a large field of view. However, RCA-based 3D imaging is fundamentally limited by severe sidelobe artifacts and a low signal-to-noise ratio (SNR), primarily due to weak transmit focusing inherent in RCA based ultrafast imaging strategies. To overcome these challenges… ▽ More Row column addressed (RCA) transducers present a promising solution for ultrafast volumetric imaging with a reduced channel count and a large field of view. However, RCA-based 3D imaging is fundamentally limited by severe sidelobe artifacts and a low signal-to-noise ratio (SNR), primarily due to weak transmit focusing inherent in RCA based ultrafast imaging strategies. To overcome these challenges, we propose a cross fusion and correlation (CFAC) method that leverages the incoherence of sidelobe artifacts and noise across datasets acquired using orthogonal apertures and multiple steering angle sets. The performance of the proposed method was validated through simulations, in vitro imaging of a multi-purpose ultrasound phantom, and in vivo experiments, and benchmarked against four established techniques: orthogonal plane wave (OPW) imaging, XDoppler method, row-column-specific frame-multiply-and-sum beamforming (RC-FMAS), and coherent factor (CF) imaging. Simulation results demonstrated that CFAC reduced sidelobe levels by 42.0 dB, 38.9 dB, 28.3 dB, and 25.5 dB compared to OPW, XDoppler, RC-FMAS, and CF, respectively. In phantom experiments, CFAC improved the CNR by up to 17.5 dB. Furthermore, in vivo imaging of a rat kidney showed that CFAC enables visualization of a significantly more detailed microvascular network, achieving a CNR improvement of over 25 dB against all benchmarked methods. In conclusion, the proposed CFAC method effectively suppresses sidelobe artifacts and noise in RCA-based imaging under low-SNR conditions, enabling high-contrast 3D visualization while preserving the high frame rate capabilities of ultrafast ultrasound imaging. △ Less

Submitted 24 April, 2026; originally announced April 2026.

High-Fidelity Reconstruction of Charge Boundary Layers and Sharp Interfaces in Electro-Thermal-Convective Flows via Residual-Attention PINNs

Authors: Baitong Zhou, Ze Tao, Ke Xu, Fujun Liu, Xuan Fang

Abstract: Accurate reconstruction of localized extreme structures remains a critical bottleneck in the physics-informed modeling of electro-thermal-convective flows. Although conventional physics-informed neural networks effectively capture smooth global dynamics, they frequently suffer from numerical diffusion and distortion when attempting to resolve sharp charge boundary layers or abrupt multiphase inter… ▽ More Accurate reconstruction of localized extreme structures remains a critical bottleneck in the physics-informed modeling of electro-thermal-convective flows. Although conventional physics-informed neural networks effectively capture smooth global dynamics, they frequently suffer from numerical diffusion and distortion when attempting to resolve sharp charge boundary layers or abrupt multiphase interfaces. To address these limitations, we propose a Residual-Attention Physics-Informed Neural Network (RA-PINN) that embeds gated attention modulation within a residual feature framework to adaptively enhance local sensitivity to steep physical gradients. The proposed architecture is rigorously evaluated against standard and recurrent network baselines using canonical electrohydrodynamic scenarios, encompassing near-electrode exponential boundary layers and sharply concentrated charge fields. Quantitative analyses demonstrate that the RA-PINN significantly reduces localized errors and faithfully preserves critical interface topologies without compromising the global consistency dictated by the coupled governing equations. Ultimately, this methodology establishes a highly robust predictive framework for resolving complex interfacial and boundary layer phenomena in advanced fluid dynamics applications. △ Less

Submitted 11 April, 2026; originally announced April 2026.

Comments: 16 pages, 5 figures

Automated Classification of Plasma Regions at Mars Using Machine Learning

Authors: Yilan Qin, Chuanfei Dong, Hongyang Zhou, Chi Zhang, Kaichun Xu, Jiawei Gao, Simin Shekarpaz, Xinmin Li, Liang Wang

Abstract: The plasma environment around Mars is highly variable because it is strongly influenced by the solar wind. Accurate identification of plasma regions around Mars is important for the community studying solar wind-Mars interactions, region-specific plasma processes, and atmospheric escape. In this study, we develop a machine-learning-based classifier to automatically identify three key plasma region… ▽ More The plasma environment around Mars is highly variable because it is strongly influenced by the solar wind. Accurate identification of plasma regions around Mars is important for the community studying solar wind-Mars interactions, region-specific plasma processes, and atmospheric escape. In this study, we develop a machine-learning-based classifier to automatically identify three key plasma regions--solar wind, magnetosheath, and induced magnetosphere--using only ion omnidirectional energy spectra measured by the MAVEN Solar Wind Ion Analyzer (SWIA). Two neural network architectures are evaluated: a multilayer perceptron (MLP) and a convolutional neural network (CNN) that incorporates short temporal sequences. Our results show that the CNN can reliably distinguish the three plasma regions, whereas the MLP struggles to separate the solar wind and magnetosheath. Therefore, the CNN-based approach provides an efficient and accurate framework for large-scale plasma region identification at Mars and can be readily applied to future planetary missions. △ Less

Submitted 18 April, 2026; originally announced April 2026.

Comments: 14 pages, 4 figures

Impact of leaky dynamics on predictive path integration accuracy in recurrent neural networks

Authors: Yanlin Zhang, Yan Zhang, Muhua Zheng, Kesheng Xu

Abstract: Experimental evidence indicates that intrinsic temporal dynamics operating across multiple time scales are closely associated with the emergence of periodic spatial activity of increasing complexity. However, how information encoded in grid-like firing patterns for path integration is processed across these intrinsic time scales remains unclear. To address this question, we introduce adaptive time… ▽ More Experimental evidence indicates that intrinsic temporal dynamics operating across multiple time scales are closely associated with the emergence of periodic spatial activity of increasing complexity. However, how information encoded in grid-like firing patterns for path integration is processed across these intrinsic time scales remains unclear. To address this question, we introduce adaptive time scales through a leak term in recurrent neural networks (RNNs), forming leaky RNNs discretized from the continuous attractors of firing rate models. Our results demonstrate that leaky RNNs substantially enhance the emergence of well-defined and highly regular hexagonal firing patterns. Compared with vanilla RNNs lacking a leak term, the trained leaky RNNs produce more accurate position estimates while generating reliable grid-cell-like representations. Furthermore, under identical noise conditions, leaky RNNs consistently exhibit more stable dynamics and better-defined grid structures. The learned dynamics also give rise to stable torus attractors with a clear central hole, supporting robust and regular grid-like activity. Overall, the dynamic leak acts as a low-pass filtering mechanism that protects recurrent neural circuitry from noise, stabilizes network dynamics, and improves path-integration accuracy in recurrent neural networks. △ Less

Submitted 17 April, 2026; originally announced April 2026.

Comments: 13 figures and 15 pages

Journal ref: Nonlinear Dynamics 114, no. 12 (2026): 849

Role of chloride concentration in modulating seizure transitions in excitatory and inhibitory networks

Authors: Qianchen Gong, Yingpeng Liu, Yan Zhang, Muhua Zheng, Kesheng Xu

Abstract: Experimental evidence indicates that intracellular chloride concentration regulates the excitation and inhibition (EI) balance, yet the mechanisms by which activity-dependent chloride dynamics drive seizure evolution and stage transitions remain unclear. We present a conductance-based neuronal network in which EI balance emerges from chloride homeostasis via channel-mediated influx and transporter… ▽ More Experimental evidence indicates that intracellular chloride concentration regulates the excitation and inhibition (EI) balance, yet the mechanisms by which activity-dependent chloride dynamics drive seizure evolution and stage transitions remain unclear. We present a conductance-based neuronal network in which EI balance emerges from chloride homeostasis via channel-mediated influx and transporter-mediated extrusion. We show that the fraction of inhibitory synaptic conductance contributing to channel-mediated influx acts as a control parameter that organizes seizure dynamics into distinct stages,pre-ictal, ictal-tonic, and ictal-clonic,distinguished by characteristic amplitude and frequency signatures. Decreasing this fraction shortens ictal activity and suppresses seizure initiation, whereas high fraction promotes the emergence of ictal-tonic and ictal-clonic stages and spiral-wave dynamics, rendering seizure dynamics largely insensitive to inhibition. At intermediate values, seizures bypass the ictal-tonic stage and emerge directly as the icta,clonic stage. Moreover, joint variation of fractions with synaptic strengths reveals that recurrent excitation expands the tonic-clonic seizure, while recurrent inhibition prolongs pre-ictal states and suppresses ictal-clonic activity. △ Less

Submitted 17 April, 2026; originally announced April 2026.

Comments: 16 pages, 15 figures

Journal ref: Physical Review E 113, 034401 (2026)

A Discrete Adjoint Gas-Kinetic Scheme for Aerodynamic Shape Optimization in Turbulent Continuum Flows

Authors: Hangkong Wu, Yuze Zhu, Yajun Zhu, Kun Xu

Abstract: This study presents an efficient and accurate discrete adjoint gas-kinetic scheme (GKS) for sensitivity analysis and aerodynamic shape optimization in continuum flow regimes. Developed using the backward mode of algorithmic differentiation (AD), the adjoint solver is rigorously verified against a duality-preserving linearized GKS solver generated via forward-mode AD. The robustness and practical e… ▽ More This study presents an efficient and accurate discrete adjoint gas-kinetic scheme (GKS) for sensitivity analysis and aerodynamic shape optimization in continuum flow regimes. Developed using the backward mode of algorithmic differentiation (AD), the adjoint solver is rigorously verified against a duality-preserving linearized GKS solver generated via forward-mode AD. The robustness and practical effectiveness of the solver are evaluated through three benchmark cases: the inverse design of turbine blades, lift-to-drag ratio enhancement, and shock-strength reduction for a NACA 0012 airfoil. To capture realistic flow physics, fully turbulent optimizations are conducted using the one-equation Spalart--Allmaras (SA) model. Numerical results demonstrate excellent agreement between the discrete adjoint and linearized solvers, exhibiting matching sensitivity convergence behaviors, identical asymptotic residual decay rates, and negligible discrepancies in final sensitivity predictions. Furthermore, the optimization studies confirm that targeted design objectives are consistently achieved within a limited number of design cycles, highlighting the solver's computational efficiency, accuracy, and suitability for complex aerodynamic geometries. △ Less

Submitted 15 April, 2026; originally announced April 2026.

Comments: 38 pages, 39 figures

Limits of Statistical Models of Ultracold Complex Lifetimes

Authors: Kevin B. Xu, John L. Bohn

Abstract: The puzzle of "sticky collisions," in which molecular collision complexes exhibit unexpectedly long lifetimes, remains an unresolved mystery. A central challenge to solving this mystery is that traditional close-coupling calculations remain limited by the vast computational cost needed to take into account all the degrees of freedom involved in the collision. In this work, we propose a statistical… ▽ More The puzzle of "sticky collisions," in which molecular collision complexes exhibit unexpectedly long lifetimes, remains an unresolved mystery. A central challenge to solving this mystery is that traditional close-coupling calculations remain limited by the vast computational cost needed to take into account all the degrees of freedom involved in the collision. In this work, we propose a statistical model designed to simulate the result of full close-coupling calculations, with the goal of collecting statistics about reasonable lifetimes of collision complexes. To do so, we numerically sample resonances using random matrix theory and utilize results from quantum defect theory to calculate scattering properties and lifetimes. We find that in the limit of dense resonances, our theory agrees well with the Rice-Ramsperger-Kassel-Markus (RRKM) prediction, whereas in the limit of sparse resonances, the physics is governed by threshold behavior rather than resonant effects. By comparing these predictions to experimental results in two limits, we argue that close-coupling calculations alone may be insufficient to resolve the issue of long lifetimes. △ Less

Submitted 20 April, 2026; v1 submitted 13 April, 2026; originally announced April 2026.

Comments: 14 pages, 9 figures

Unified Gas-Kinetic Scheme for Unsteady Multiscale Flows with Moving Boundaries

Authors: Yue Zhang, Wenpei Long, Junzhe Cao, Kun Xu

Abstract: Simulating multiscale flows with moving boundaries, such as hypersonic multi-body separation and flows in micro-electro-mechanical systems (MEMS), requires robust numerical methods that couple mesh deformation with complex flow physics. This paper presents a hybrid overlapping moving-mesh technique developed within the unified gas-kinetic scheme (UGKS). To mitigate the Courant-Friedrichs-Lewy (CFL… ▽ More Simulating multiscale flows with moving boundaries, such as hypersonic multi-body separation and flows in micro-electro-mechanical systems (MEMS), requires robust numerical methods that couple mesh deformation with complex flow physics. This paper presents a hybrid overlapping moving-mesh technique developed within the unified gas-kinetic scheme (UGKS). To mitigate the Courant-Friedrichs-Lewy (CFL) constraint, we extend the implicit unsteady UGKS solver to support moving meshes, incorporating memory-efficient data handling and parallel computing optimizations to maximize computational efficiency. Validated against hypersonic multi-body separation and thermal rarefied MEMS flows, the proposed scheme accurately resolves complex, dynamic multiscale phenomena. The results confirm that this robust and efficient method provides a highly reliable tool for modeling dynamic flow interactions in complex geometric configurations. △ Less

Submitted 10 April, 2026; originally announced April 2026.

Learnable Viscosity Modulation in Physics-Informed Neural Networks for Incompressible Flow Reconstruction

Authors: Ke Xu, Ze Tao, Fujun Liu

Abstract: Accurately and stably solving the incompressible Navier--Stokes equations with physics-informed neural networks (PINNs) remains challenging, particularly for sparse or noisy observations and for flow regimes in which the local balance among convection, diffusion, and pressure is difficult to capture. To address this issue, we propose a framework, denoted as LVM-PINN, which incorporates a learnable… ▽ More Accurately and stably solving the incompressible Navier--Stokes equations with physics-informed neural networks (PINNs) remains challenging, particularly for sparse or noisy observations and for flow regimes in which the local balance among convection, diffusion, and pressure is difficult to capture. To address this issue, we propose a framework, denoted as LVM-PINN, which incorporates a learnable viscosity modulation (LVM) mechanism into the PINN residual. Specifically, the model predicts a spatiotemporal scalar field that is embedded directly into the viscous diffusion term of the momentum equations, thereby enabling adaptive modulation of the local dissipation strength during training. This modification improves optimization stability while enhancing the representation of complex flow structures. The effect of the proposed mechanism is further examined through a controlled ablation setting with an otherwise unchanged network architecture, as well as through comparisons with GRU- and residual-attention-based backbone baselines. Numerical experiments on two-dimensional benchmark problems, including the Kovasznay flow and two manufactured forcing flows, show that the proposed framework yields more stable training behavior and more accurate flow reconstruction under sparse and noisy data conditions. △ Less

Submitted 28 March, 2026; originally announced March 2026.

Comments: 10 pages, 12 figures

MSC Class: 35Q30 (Primary) 68T07; 76D05 (Secondary) ACM Class: I.6.5

Adaptive finite volume-particle method for free surface flows

Authors: Jiawang Zhang, Fengxiang Zhao, Kun Xu

Abstract: This study proposes a novel adaptive finite volume-particle method (AFVPM) for accurate and efficient free surface flow simulations. The proposed AFVPM synergistically combines the Eulerian finite volume method (FVM) on unstructured meshes with the Lagrangian smoothed particle hydrodynamics (SPH) approach. Specifically, the mesh-based FVM is employed in the bulk flow regions to leverage its comput… ▽ More This study proposes a novel adaptive finite volume-particle method (AFVPM) for accurate and efficient free surface flow simulations. The proposed AFVPM synergistically combines the Eulerian finite volume method (FVM) on unstructured meshes with the Lagrangian smoothed particle hydrodynamics (SPH) approach. Specifically, the mesh-based FVM is employed in the bulk flow regions to leverage its computational efficiency and numerical accuracy, while a weakly compressible SPH formulation is applied in the vicinity of the interface to maintain robust free-surface tracking capabilities. A key innovation of this framework is a block-based dynamic and adaptive conversion strategy between Eulerian mesh regions and Lagrangian particle regions and a buffer region-based cell-particle algorithm is designed to ensure seamless data communication across the Eulerian mesh-Lagrangian particle interface. Furthermore, isothermal gas-kinetic scheme (GKS) incorporating gravitational effects is utilized to calculate the fluxes in the mesh regions. The performance and reliability of the proposed AFVPM are validated through a series of benchmark cases that involve complex free surface phenomena. Numerical results demonstrate that AFVPM achieves superior accuracy and efficiency compared to full SPH approaches. △ Less

Submitted 26 March, 2026; originally announced March 2026.

Design and implementation of a high-density sub-nanosecond timing system for a C-band photocathode electron gun test platform

Authors: Peng Zhu, Kangjia Xue, Lin Wang, Yuliang Zhang, Yongcheng Hea, Xuan Wu, Mingtao Li, Sinong Cheng, Xiaohan Lu, Shiming Jiang, Xiao Li

Abstract: This paper presents the design and implementation of a high-density, deterministic trigger distribution system tailored for the C-band photocathode electron gun test platform at the Southern Advanced Photon Source (SAPS). Implemented within a scalable 6U VME modular architecture, the system achieves high-density integration by consolidating a master controller, clock distribution network, and 80 h… ▽ More This paper presents the design and implementation of a high-density, deterministic trigger distribution system tailored for the C-band photocathode electron gun test platform at the Southern Advanced Photon Source (SAPS). Implemented within a scalable 6U VME modular architecture, the system achieves high-density integration by consolidating a master controller, clock distribution network, and 80 heterogeneous output channels into a single chassis. This design leverages a high-performance FPGA core combined with custom backplane interconnections to establish a master-slave topology, significantly reducing the system footprint compared to stacked standalone generators. To guarantee timing determinism in high-noise environments, precise placement and timing constraints are applied to the FPGA logic, while optical isolation is employed to mitigate electromagnetic interference. Furthermore, a dual-channel SFP optical signaling architecture enables seamless expansion to 160 synchronized channels. A remote control framework based on a serial server and a virtual machine Input/Output Controller (IOC) facilitates flexible configuration. Performance tests demonstrate adjustable trigger frequencies from 1 Hz to 100 Hz, with delays and pulse widths tunable from 0 to 10 ms at a resolution of 10 ns (or the RF period). The local electrical output exhibits an ultra-low RMS jitter of 6.55 ps (60 ps peak-to-peak). For remote optical distribution, the system maintains a sub-nanosecond RMS jitter of 119.5 ps, with peak-to-peak variation confined to 1 ns due to the combined effects of transceiver optoelectronic conversion (utilizing HFBR-1414T/2412T modules) and fiber transmission. The system has been successfully commissioned and is currently in reliable routine operation, verifying the architecture as a robust, highly integrated, and cost-effective solution for compact accelerator facilities. △ Less

Submitted 19 March, 2026; originally announced March 2026.

Robustness and size-dependence of circadian rhythms in multiscale suprachiasmatic-nucleus networks

Authors: Youhao Zhuo, Yingpeng Liu, Jiao Wu, Kesheng Xu, Muhua Zheng

Abstract: Understanding how multi-scale network structure influences circadian rhythms in the suprachiasmatic nucleus (SCN) is essential for uncovering the principles of rhythmic robustness and synchronization. Previous studies using synthetic SCN networks suggested a size-dependent phenomenon, in which rhythmic activity initially strengthens with network size and then saturates, but it remains unclear whet… ▽ More Understanding how multi-scale network structure influences circadian rhythms in the suprachiasmatic nucleus (SCN) is essential for uncovering the principles of rhythmic robustness and synchronization. Previous studies using synthetic SCN networks suggested a size-dependent phenomenon, in which rhythmic activity initially strengthens with network size and then saturates, but it remains unclear whether this occurs in real SCN networks. Here, we apply geometric branch growth (GBG) and geometric renormalization (GR) to generate self-similar scaled-up and scaled-down replicas from a single-scale functional mouse SCN network. Unlike synthetic models, these SCN replicas do not exhibit size-dependent rhythms: average period, amplitude, and synchronization remain stable across scales. By increasing the average degree with network size, we reproduce size-dependent rhythms and show that they arise from network connectivity, whereas low-degree networks fragment and fail to sustain oscillations. Disrupting clustering self-similarity slightly reduces synchronization, but circadian rhythms remain robust, indicating that average degree, rather than clustering, is the dominant structural driver. These results highlight the resilience of SCN rhythms to network scaling and provide a framework for linking multi-scale network structure to biological timekeeping. △ Less

Submitted 7 March, 2026; originally announced March 2026.

Comments: 20 pages, 14 figures

Journal ref: Phys. Rev. E 113, 034304 (2026)

NEP-CG and NEP-AACG: Efficient coarse-grained and multiscale all-atom-coarse-grained neuroevolution potentials

Authors: Zheyong Fan, Wenjun Zhang, Zhenhao Zhang, Ke Xu, Xuecheng Shao, Haikuan Dong

Abstract: Machine-learned coarse-grained (CG) models often suffer from noisy training data, limiting their accuracy and transferability. We propose a method to generate low-noise training data based on the potential of mean force by constraining CG beads during atomistic simulations and accumulating time-averaged forces. Implemented within the neuroevolution potential (NEP) framework, our approach achieves… ▽ More Machine-learned coarse-grained (CG) models often suffer from noisy training data, limiting their accuracy and transferability. We propose a method to generate low-noise training data based on the potential of mean force by constraining CG beads during atomistic simulations and accumulating time-averaged forces. Implemented within the neuroevolution potential (NEP) framework, our approach achieves training accuracy comparable to atomistic models trained on density functional theory data. For liquid water, the NEP-CG model accurately reproduces densities from 1 bar to 1 GPa, successfully extrapolating beyond the 0.5 GPa training limit, with a virial correction essential for the correct equation of state. For an anisotropic C$_{60}$ monolayer, distinguishing crystallographically distinct bead types reduces stress errors by an order of magnitude and captures directional thermal conductivity. We further introduce a multiscale NEP-AACG model integrating all-atom (AA) and CG degrees of freedom, demonstrated for gold nanowire fracture at an experimentally relevant strain rate. Computational speeds for NEP-CG models reach hundreds to thousands of ns/day using a single consumer-grade GPU. This work provides a robust framework for constructing accurate, transferable, and efficient CG models across diverse systems. △ Less

Submitted 1 March, 2026; originally announced March 2026.

Comments: 12 pages, 8 figures

Wave Particle Turbulent Simulation of Spatially Developing Round Jets Using a Non Equilibrium Transport Model with a Mixing Length Characteristic Time Closure

Authors: Xiaojian Yang, Kun Xu

Abstract: In this paper, the wave-particle turbulent simulation (WPTS), a recently developed multiscale, non-equilibrium turbulence modeling approach, is coupled with a turbulence characteristic-time closure derived from Prandtl mixing-length hypothesis and applied to spatially developing round jets. In WPTS, fluid elements in strongly turbulent regions are represented by Lagrangian particles that travel a… ▽ More In this paper, the wave-particle turbulent simulation (WPTS), a recently developed multiscale, non-equilibrium turbulence modeling approach, is coupled with a turbulence characteristic-time closure derived from Prandtl mixing-length hypothesis and applied to spatially developing round jets. In WPTS, fluid elements in strongly turbulent regions are represented by Lagrangian particles that travel a finite distance before interacting with the background flow field represented in a wave-like (Eulerian) form. This mechanism bears conceptual similarity to the discrete fluid parcels invoked in the Prandtl mixing-length picture. WPTS differs from conventional mixing-length-based turbulence models in two key respects. First, particle evolution follows a non-equilibrium transport mechanism, rather than the equilibrium assumptions typically embedded in eddy-viscosity closures. Second, WPTS advances the wave and particle components in a coupled manner, with the particle fraction governed primarily by the modeled turbulence characteristic time, enabling laminar and turbulent regimes to be represented within a unified framework. Because spatially developing jets provide a canonical test case with well-established similarity behavior, they are used here for evaluation. Specifically, this work (1) develops a mixing-length-based characteristic-time model tailored to jet flows and (2) incorporates it into WPTS to assess predictive performance. The resulting WPTS framework accurately reproduces the jet similarity solution and other characteristic features at Reynolds numbers of 5,000 and 20,000, demonstrating the promise of WPTS as a practical tool for turbulence modeling and simulation. △ Less

Submitted 10 February, 2026; originally announced February 2026.

A single-stage high-order compact gas-kinetic scheme in arbitrary Lagrangian-Eulerian formulation

Authors: Yue Zhang, Xing Ji, Yibing Chen, Fengxiang Zhao, Kun Xu

Abstract: This study presents the development of a compact gas-kinetic scheme using an arbitrary Lagrangian-Eulerian (ALE) formulation for structured meshes. Unlike the Eulerian formulation, the ALE approach effectively tracks flow discontinuities, such as shock waves and contact discontinuities. However, mesh motion alters the geometry and increases computational costs. To address this, two key strategies… ▽ More This study presents the development of a compact gas-kinetic scheme using an arbitrary Lagrangian-Eulerian (ALE) formulation for structured meshes. Unlike the Eulerian formulation, the ALE approach effectively tracks flow discontinuities, such as shock waves and contact discontinuities. However, mesh motion alters the geometry and increases computational costs. To address this, two key strategies were introduced to reduce costs and enhance accuracy. The first strategy is to use the gas-kinetic scheme to construct a third-order gas-kinetic flux, rather than the Runge-Kutta method to achieve high-order time accuracy, which allows a single reconstruction and flux calculation per time step. This approach enables direct updates of both cell-averaged flow variables and their gradients using a time-accurate flux function, facilitating compact reconstruction. Second, the significant computational expense is spent on reconstruction, which requires recalculating the reconstruction matrix at each time step due to mesh changes. A simplified fourth-order compact reconstruction using a small matrix was used to mitigate this cost. The combination of fourth-order spatial reconstruction and third-order time-accurate flux evolution ensures both high resolution and computational efficiency in the ALE framework. The tests shows that the current reconstruction is 2.4x to 3.0x faster than the previous reconstruction. Additionally, a generalized ENO(GENO) method for handling discontinuities enhances the scheme's robustness. The numerical test cases, such as the Riemann problem, Sedov problem, Noh problem, and Saltzmann problem, demonstrated the robustness and accuracy of our method. △ Less

Submitted 10 February, 2026; originally announced February 2026.

Comments: arXiv admin note: substantial text overlap with arXiv:2401.02157

qNEP: A highly efficient neuroevolution potential with dynamic charges for large-scale atomistic simulations

Authors: Zheyong Fan, Benrui Tang, Esmée Berger, Ethan Berger, Erik Fransson, Ke Xu, Zihan Yan, Zhoulin Liu, Zichen Song, Haikuan Dong, Shunda Chen, Lei Li, Ziliang Wang, Yizhou Zhu, Julia Wiktor, Paul Erhart

Abstract: Although electrostatics can be incorporated into machine-learned interatomic potentials, existing approaches are computationally very demanding, limiting large-scale, long-time simulations of electrostatics-driven phenomena such as dielectric response, infrared activity, and field-matter coupling. Here, we extend the neuroevolution potential (NEP), a highly efficient machine-learned interatomic po… ▽ More Although electrostatics can be incorporated into machine-learned interatomic potentials, existing approaches are computationally very demanding, limiting large-scale, long-time simulations of electrostatics-driven phenomena such as dielectric response, infrared activity, and field-matter coupling. Here, we extend the neuroevolution potential (NEP), a highly efficient machine-learned interatomic potential, to a charge-aware framework (qNEP) by introducing explicit, environment-dependent partial charges. Each ionic partial charge is represented by a neural network as a function of the local descriptor vector, analogous to the NEP site-energy model. This formulation enables the direct prediction of the Born effective charge tensor for each ion and, consequently, the polarization. As a result, dielectric properties, infrared spectra, and coupling to external electric fields can be evaluated within a unified framework. We derive consistent expressions for the forces and virials that explicitly account for the position dependence of the partial charges. The qNEP method has been implemented in the free-and-open-source GPUMD package, with support for both Ewald summation and particle-particle particle-mesh treatments of electrostatics. We demonstrate the accuracy and efficiency of the qNEP approach through representative applications to water, Li7La3Zr2O12, BaTiO3, and a magnesium-water interface. These results show that qNEP enables accurate atomistic simulations with explicit long-range electrostatics, scalable to million-atom systems on nanosecond time scales using consumer-grade GPUs. △ Less

Submitted 26 January, 2026; originally announced January 2026.

Comments: 17 pages, 7 figures

Electric field switching of altermagnetic spin-splitting in multiferroic skyrmions

Authors: Gui Wang, Yuhang Li, Bin Li, Xianzhe Chen, Jianting Dong, Weizhao Chen, Xiaobing Chen, Naifu Zheng, Maosen Guo, Aomei Tong, Hua Bai, Hongrui Zhang, Yifan Gao, Kaiwen Shen, Jiangyuan Zhu, Jiahao Han, Yingfen Wei, Hao Jiang, Xumeng Zhang, Ming Wang, Kebiao Xu, Wu Shi, Pengfei Wang, Jia Zhang, Qihang Liu , et al. (4 additional authors not shown)

Abstract: Magnetic skyrmions are localized magnetic structures that retain their shape and stability over time, thanks to their topological nature. Recent theoretical and experimental progress has laid the groundwork for understanding magnetic skyrmions characterized by negligible net magnetization and ultrafast dynamics. Notably, skyrmions emerging in materials with altermagnetism, a novel magnetic phase f… ▽ More Magnetic skyrmions are localized magnetic structures that retain their shape and stability over time, thanks to their topological nature. Recent theoretical and experimental progress has laid the groundwork for understanding magnetic skyrmions characterized by negligible net magnetization and ultrafast dynamics. Notably, skyrmions emerging in materials with altermagnetism, a novel magnetic phase featuring lifted Kramers degeneracy-have remained unreported until now. In this study, we demonstrate that BiFeO3, a multiferroic renowned for its strong coupling between ferroelectricity and magnetism, can transit from a spin cycloid to a Neel-type skyrmion under antidamping spin-orbit torque at room temperature. Strikingly, the altermagnetic spin splitting within BiFeO3 skyrmion can be reversed through the application of an electric field, revealed via the Circular photogalvanic effect. This quasiparticle, which possesses a neutral topological charge, holds substantial promise for diverse applications-most notably, enabling the development of unconventional computing systems with low power consumption and magnetoelectric controllability. △ Less

Submitted 10 January, 2026; originally announced January 2026.

LSTM-PINN: An Hybrid Method for Prediction of Steady-State Electrohydrodynamic Flow

Authors: Ze Tao, Ke Xu, Fujun Liu

Abstract: Physics-Informed Neural Networks (PINNs) have demonstrated considerable success in solving complex fluid dynamics problems. However, their performance often deteriorates in regimes characterized by steep gradients, intricate boundary conditions, and stringent physical constraints, leading to convergence failures and numerical instabilities. To overcome these limitations, we propose a hybrid framew… ▽ More Physics-Informed Neural Networks (PINNs) have demonstrated considerable success in solving complex fluid dynamics problems. However, their performance often deteriorates in regimes characterized by steep gradients, intricate boundary conditions, and stringent physical constraints, leading to convergence failures and numerical instabilities. To overcome these limitations, we propose a hybrid framework that integrates Long Short-Term Memory (LSTM) networks into the PINN architecture, enhancing its ability to capture spatial correlations in the steady-state velocity field of a two-dimensional charged fluid under an external electric field. Our results demonstrate that the LSTM-enhanced PINN model significantly outperforms conventional Multilayer Perceptron (MLP)-based PINNs in terms of convergence rate, numerical stability, and predictive accuracy. This innovative approach offers improved computational efficiency and reliability for modeling electrohydrodynamic flows, providing new insights and strategies for applications in microfluidics and nanofluidics. △ Less

Submitted 25 December, 2025; originally announced December 2025.

UGKS and UGKWP Methods for Multiscale Simulation of Electrostatic Plasma in Quasineutral and Hydrodynamic Limits

Authors: Zhigang Pu, Kun Xu

Abstract: This study extends the Unified Gas-Kinetic Scheme (UGKS) and the Unified Gas-Kinetic Wave-Particle (UGKWP) method for electrostatic plasma modeling, ensuring the correct asymptotic limits with respect to both the Debye length and the mean free path. By coupling collision and transport processes within the numerical flux, the proposed approach effectively removes the hydrodynamic-limit constraint a… ▽ More This study extends the Unified Gas-Kinetic Scheme (UGKS) and the Unified Gas-Kinetic Wave-Particle (UGKWP) method for electrostatic plasma modeling, ensuring the correct asymptotic limits with respect to both the Debye length and the mean free path. By coupling collision and transport processes within the numerical flux, the proposed approach effectively removes the hydrodynamic-limit constraint associated with the mean free path. In addition, a reformulated Poisson equation, coupled with the macroscopic moment equations, is introduced to overcome the inefficiency of the standard Poisson formulation in the quasineutral regime. The accuracy and asymptotic consistency of the proposed schemes are verified through several benchmark tests, including linear and nonlinear Landau damping and the bump-on-tail instability. The results demonstrate that the methods robustly capture plasma dynamics across hydrodynamic and quasineutral regimes, without resolution constraints imposed by either the Debye length or the mean free path. △ Less

Submitted 17 December, 2025; originally announced December 2025.

The study of coherent Rayleigh-Brillouin scattering in multiple flow regimes using unified gas-kinetic scheme

Authors: Xiaozhe Xi, Junzhe Cao, Kun Xu

Abstract: Coherent Rayleigh-Brillouin scattering (CRBS) holds great promise for the characterization of gas properties and the investigation of gas kinetic processes. The CRBS spectrum exhibits a strong dependence on the Knudsen number (Kn), revealing its inherently multiscale nature. In the unified gas-kinetic scheme (UGKS), collisions are intrinsically coupled with free transport during flux construction,… ▽ More Coherent Rayleigh-Brillouin scattering (CRBS) holds great promise for the characterization of gas properties and the investigation of gas kinetic processes. The CRBS spectrum exhibits a strong dependence on the Knudsen number (Kn), revealing its inherently multiscale nature. In the unified gas-kinetic scheme (UGKS), collisions are intrinsically coupled with free transport during flux construction, endowing the method with distinct multiscale capabilities. Specifically, the UGKS reduces to a Boltzmann solver when the relaxation time is greater than or equal to the time step, and to the gas-kinetic scheme (GKS)-a Navier-Stokes solver-when the relaxation time is much smaller than the time step, thereby accommodating flow regimes without constraints on the molecular mean free path or collision time. In this study, the UGKS is extended to simulate CRBS phenomena, with the governing equation formulated based on the BGK-Shakhov model. Detailed derivations are provided. To account for the additional perturbation source term, a second-order accurate numerical algorithm is developed using the Strang splitting method within the UGKS framework. The proposed model is validated against argon CRBS experiments, demonstrating excellent agreement. Building on this validated framework, the impact of incident signal intensity on CRBS spectra across a range of Knudsen numbers is systematically examined, accompanied by an in-depth analysis of the underlying physical mechanisms. This work broadens the applicability of CFD-based CRBS simulations and provides a reliable numerical foundation for exploring high-intensity, multiscale gas-kinetic phenomena in future research. △ Less

Submitted 20 December, 2025; v1 submitted 17 December, 2025; originally announced December 2025.

Comments: 18 pages, 6 figures,

Exceptional Alkaline Methanol Electrooxidation on Bi-modified Pt3M Intermetallics: Kinetic Origins and an OH Binding Energy Descriptor

Authors: Lecheng Liang, Hengyu Li, Shao Ye, Peng Li, Kaiyang Xu, Jinhui Liang, Binwen Zeng, Bo Shen, Taisuke Ozaki, Zhiming Cui

Abstract: The exploration of advanced CO-free catalysts and clarifying the ambiguous kinetic origins and governing factors would undoubtedly open up opportunities to overcome the sluggish kinetics of methanol electrooxidation and promote the development of direct methanol fuel cells. Herein, we constructed a family of Bi-modified Pt3M intermetallic catalysts (Bi-Pt3M/C, M=Cr, Mn, Co, Zn, In, Ga, and Sn) tha… ▽ More The exploration of advanced CO-free catalysts and clarifying the ambiguous kinetic origins and governing factors would undoubtedly open up opportunities to overcome the sluggish kinetics of methanol electrooxidation and promote the development of direct methanol fuel cells. Herein, we constructed a family of Bi-modified Pt3M intermetallic catalysts (Bi-Pt3M/C, M=Cr, Mn, Co, Zn, In, Ga, and Sn) that follow CO-free dominated pathway and exhibit exceptional catalytic activity. More significantly, leveraging this platform, we have identified the pivotal factor governing the reaction kinetics in CO-free pathway, namely OH binding energy (OHBE). This arises because the rate-determining step (RDS) encompasses both C-H bond activation and water dissociation, whose respective barriers can be reflected by the OHBE. Accordingly, OHBE can act as an activity descriptor. Specifically, Bi-Pt3In/C stands out from other Bi-Pt3M/C and delivers the unprecedented mass activity of 36.7 A mgPt-1 at peak potential, far exceeding state-of-the-art Pt-based catalysts reported to date. Taking Bi-Pt3In/C as a proof of concept, we clearly elucidate the origin of enhanced MOR activity by combining theoretical calculations, kinetic isotope effects, and formaldehyde electrooxidation. Moreover, there exhibits a volcano-type trend between OHBE and the activity of Bi-Pt3M/C. Beyond the discovery of ultrahigh-performance catalysts, these findings provide a detailed mechanistic picture of RDS and offer an innovative design principle for advanced catalysts. △ Less

Submitted 12 December, 2025; originally announced December 2025.

Generation of Polarization-Tunable Hybrid Cylindrical Vector gamma Rays

Authors: Si-Man Liu, Yue Cao, Kun Xue, Li-Xiang Hu, Xin-Yu Liu, Xin-Yan Li, Chao-Zhi Li, Xin-Rong Xu, Ke Liu, Wei-Quan Wang, De-Bin Zou, Yan Yin, Jian-Xing Li, Tong-Pu Yu

Abstract: Cylindrical vector (CV) gamma rays can introduce spatially structured polarization as a new degree of freedom for fundamental research and practical applications. However, their generation and control remain largely unexplored. Here, we put forward a novel method to generate CV gamma rays with tunable hybrid polarization via a rotating electron beam interacting with a solid foil. In this process,… ▽ More Cylindrical vector (CV) gamma rays can introduce spatially structured polarization as a new degree of freedom for fundamental research and practical applications. However, their generation and control remain largely unexplored. Here, we put forward a novel method to generate CV gamma rays with tunable hybrid polarization via a rotating electron beam interacting with a solid foil. In this process, the beam generates a coherent transition radiation field and subsequently emits gamma rays through nonlinear Compton scattering. By manipulating the initial azimuthal momentum of the beam, the polarization angle of gamma rays relative to the transverse momentum can be controlled, yielding tunable hybrid CV polarization states. Three-dimensional spin-resolved particle-in-cell simulations demonstrate continuous tuning of the polarization angle across (-90°, 90°) with a high polarization degree exceeding 60%. Our work contributes to the development of structured gamma rays, potentially opening new avenues in high-energy physics, nuclear science, and laboratory astrophysics. △ Less

Submitted 9 December, 2025; originally announced December 2025.

Deep-Learning Based Super-Resolution Functional Ultrasound Imaging of Transient Brain-Wide Neurovascular Activity on a Microscopic Scale

Authors: Yang Cai, Shaoyuan Yan, Long Xu, Yanfeng Zhu, Bo Li, Kailiang Xu

Abstract: Transient brain-wide neuroimaging on a microscopic scale is pivotal for brain research, yet existing imaging modalities face challenges in meeting such spatiotemporal requirements. Functional ultrasound (fUS) enables transient neurovascular imaging through red blood cell backscattering, but suffers from diffraction-limited spatial resolution. Functional ultrasound localization microscopy (fULM) ha… ▽ More Transient brain-wide neuroimaging on a microscopic scale is pivotal for brain research, yet existing imaging modalities face challenges in meeting such spatiotemporal requirements. Functional ultrasound (fUS) enables transient neurovascular imaging through red blood cell backscattering, but suffers from diffraction-limited spatial resolution. Functional ultrasound localization microscopy (fULM) has addressed this limitation by integrating ULM with fUS; but this approach requires repeated stimulation and data accumulation. Here, we introduce super-resolution functional ultrasound (SR-fUS), a deep learning-based framework that reconstructs super-resolution ULM images from contrast-free ultrafast Doppler data. By incorporating red blood cell radial gradient fluctuation priors with uncertainty-driven loss, SR-fUS enables microscopic scale hemodynamic imaging with 25-μm spatial spatial resolution. In rat brains, SR-fUS visualized transient pain-evoked hemodynamic responses, distinguished stimulus-specific microvascular activation patterns during single-whisker stimulation, and dynamically tracked isoflurane anesthesia-induced microvascular dilation. The accuracy of SR-fUS was further preliminarily assessed through a comparative study with two-photon microscopy. △ Less

Submitted 14 June, 2026; v1 submitted 17 November, 2025; originally announced November 2025.

A paradox of the Navier-Stokes turbulence

Authors: Shijie Qin, Kun Xu, Shijun Liao

Abstract: The Navier-Stokes (NS) equations as a turbulence model have been widely applied in lots of fields. The NS equations contain such a fundamental assumption that all small physical/artificial disturbances could be neglected. Is this assumption correct? In this paper a two-dimensional Rayleigh-Bénard convection governed by the NS equations is predicted by traditional direct numerical simulation (DNS)… ▽ More The Navier-Stokes (NS) equations as a turbulence model have been widely applied in lots of fields. The NS equations contain such a fundamental assumption that all small physical/artificial disturbances could be neglected. Is this assumption correct? In this paper a two-dimensional Rayleigh-Bénard convection governed by the NS equations is predicted by traditional direct numerical simulation (DNS) using double precision arithmetic and a range of different time-steps. It is found that the final flow type tends either to vortical flow or zonal flow, whose statistics are completely different. Notably, these two flow types frequently alternate as the time-step is reduced to a very small value, suggesting that the time-step corresponding to each turbulent flow type should be densely distributed. Thus, stochastic numerical noise exerts a huge influence on the final flow type and statistics of numerically simulated NS turbulence because the time-step has a close relationship with numerical noise. This clearly indicates that small disturbances have significant influences on the NS turbulence, which therefore should not be neglected. This leads to a logical paradox for the NS turbulence, which is a great challenge for us, although a paradox often leads to some significant breakthroughs. △ Less

Submitted 26 April, 2026; v1 submitted 13 October, 2025; originally announced October 2025.

Comments: 13 page, 4 figures

Ultra-chaotic property of Navier-Stokes turbulence

Authors: Shijie Qin, Kun Xu, Shijun Liao

Abstract: A chaotic system is called ultra-chaos when its statistics have sensitivity dependence on initial condition and/or other small disturbances. In this paper, using two-dimensional turbulent Kolmogorov flow as an example, we illustrate that tiny variation of initial condition of Navier-Stokes equations can lead to huge differences not only in spatiotemporal trajectory but also in flow symmetry and it… ▽ More A chaotic system is called ultra-chaos when its statistics have sensitivity dependence on initial condition and/or other small disturbances. In this paper, using two-dimensional turbulent Kolmogorov flow as an example, we illustrate that tiny variation of initial condition of Navier-Stokes equations can lead to huge differences not only in spatiotemporal trajectory but also in flow symmetry and its statistics. Here, in order to avoid the influence of artificial numerical noise, we apply ``clean numerical simulation'' (CNS) which can guarantee that the numerical noise can be reduced to such a desired low level that they are negligible in a time interval long enough for calculating statistics. This discovery highly suggests that the Navier-Stokes turbulence (i.e. turbulence governed by the Navier-Stokes equations) might be an ultra-chaos, say, small disturbances must be considered even from viewpoint of statistics. This however leads to a paradox in logic, since small disturbances, which are unavoidable in practice, are unfortunately neglected by the Navier-Stokes turbulence. Some fundamental characteristics of turbulence model are discussed and suggested in general meanings. △ Less

Submitted 8 October, 2025; originally announced October 2025.

Comments: 12 pages, 6 figures

Journal ref: European Journal of Mechanics / B Fluids 119 (2026) 204540