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Kun Xu

Publications and source records attributed to Kun Xu.

At least 91 records · Page 5Linked to original sources
arXiv2025

Integrated diffractive full-Stokes spectro-polarimetric imaging

Spectro-polarimetric imaging provides multidimensional optical information acquisition capabilities, offering significant potential for diverse applications. Current spectro-polarimetric imaging systems typically suffer from large physical footprints, high design complexity, elevated costs, or the drawback of requiring replacement of standard components with polarization optics. To address these issues, we propose an integrated diffractive full-Stokes spectro-polarimetric imaging framework that synergistically combines end-to-end designed diffractive polarization spectral element (DPSE) with SPMSA-Net to demonstrate high-performance spectro-polarimetric imaging. The DPSE modulates scene and generates modulated images carrying phase-encoding and polarization information. The modulated images are the input of the SPMSA-NET for the reconstruction of the spectro-polarimetric data cube. The framework achieves an average improvement of 0.78 dB in PSNR and 0.012 in SSIM over existing state-of-the-art algorithms. Based on this framework, our prototype system can simultaneously capture spectral information (400-700 nm) with 10 nm spectral resolution and full-Stokes parameters (S0,S1,S2,S3). Meanwhile, the system provides high spatial resolution of 2252*2252 pixels. Experimental results demonstrate that our system achieves high-fidelity spectral imaging (over 98.9% fidelity) and precise polarization characterization, with a compact architecture (modulation component of merely 2-mm thickness).

eess.IV↗
arXiv2025

Make Identity Unextractable yet Perceptible: Synthesis-Based Privacy Protection for Subject Faces in Photos

Deep learning-based face recognition (FR) technology exacerbates privacy concerns in photo sharing. In response, the research community developed a suite of anti-FR methods to block identity extraction by unauthorized FR systems. Benefiting from quasi-imperceptible alteration, perturbation-based methods are well-suited for privacy protection of subject faces in photos, as they allow familiar persons to recognize subjects via naked eyes. However, we reveal that perturbation-based methods provide a false sense of privacy through theoretical analysis and experimental validation. Therefore, new alternative solutions should be found to protect subject faces. In this paper, we explore synthesis-based methods as a promising solution, whose challenge is to enable familiar persons to recognize subjects. To solve the challenge, we present a key insight: In most photo sharing scenarios, familiar persons recognize subjects through identity perception rather than meticulous face analysis. Based on the insight, we propose the first synthesis-based method dedicated to subject faces, i.e., PerceptFace, which can make identity unextractable yet perceptible. To enhance identity perception, a new perceptual similarity loss is designed for faces, reducing the alteration in regions of high sensitivity to human vision. As a synthesis-based method, PerceptFace can inherently provide reliable identity protection. Meanwhile, out of the confine of meticulous face analysis, PerceptFace focuses on identity perception from a more practical scenario, which is also enhanced by the designed perceptual similarity loss. Sufficient experiments show that PerceptFace achieves a superior trade-off between identity protection and identity perception compared to existing methods. We provide a public API of PerceptFace and believe that it has great potential to become a practical anti-FR tool.

cs.CR↗
arXiv2025

A Geometric Multigrid-Accelerated Compact Gas-Kinetic Scheme for Fast Convergence in High-Speed Flows on GPUs

Implicit methods and GPU parallelization are two distinct yet powerful strategies for accelerating high-order CFD algorithms. However, few studies have successfully integrated both approaches within high-speed flow solvers. The core challenge lies in preserving the robustness of implicit algorithms in the presence of strong discontinuities, while simultaneously enabling massive thread parallelism under the constraints of limited GPU memory. To address this, we propose a GPU-optimized, geometric multigrid-accelerated, high-order compact gas kinetic scheme (CGKS) that incorporates three key innovations: (1) a multi-color lower-upper symmetric Gauss-Seidel scheme that eliminates thread conflicts and preserves memory efficiency, serving as an implicit smoother on coarse grids; (2) a discontinuity-adaptive relaxation technique and a multigrid prolongation process, based on a discontinuous feedback factor, which dynamically stabilize shock regions without compromising convergence in smooth zones; and (3) a three-layer V-cycle geometric parallel multigrid strategy specifically tailored for unstructured meshes. Extensive tests on multi-dimensional subsonic to hypersonic flows demonstrate that our GPU-based high-performance solver achieves one to two orders of magnitude faster convergence compared to previous explicit solvers. More importantly, it preserves the shock-capturing robustness of the explicit CGKS and exhibits strong scalability on GPU architectures. This work presents a unified framework that synergistically leverages implicit acceleration and GPU optimization for high-speed flow simulations, effectively overcoming traditional trade-offs between parallelism, memory constraints, and numerical stability in high-order methods.

math.NA↗
arXiv2025

Robust End-to-End FSO Transmission with Joint Coding Modulation and BiLSTM-Based Channel Modeling under Atmospheric Turbulence

Free space optical (FSO) communication is considered a promising solution in next_generation communication networks. However, its performance is significantly influenced by atmospheric turbulence. To enhance system robustness to turbulence, we propose a turbulence_robust end_to_end FSO communication system (TRFSO) that integrates a data-driven channel model with joint source_channel coding modulation (JSCCM). Specifically, a bidirectional long short-term memory (BiLSTM)_based channel model is developed and trained on data collected over a physical FSO link under varying turbulence conditions. This model accurately captures real_world channel distortions, achieving a minimum Kullback_Leibler (KL) divergence of 0.0019 in amplitude distribution matching. Experimental results show that the TRFSO system trained with the BiLSTM_based channel model outperforms the same architecture trained under the additive white Gaussian noise (AWGN) channel, achieving an average 3.5 dB improvement in multi-scale structural similarity (MS_SSIM) under strong atmospheric turbulence. These results demonstrate the effectiveness of the proposed TRFSO in achieving robust and reliable transmission under dynamic atmospheric turbulence.

physics.optics↗
arXiv2025

Very High-order Compact Gas-kinetic Scheme With Discontinuity Feedback Factor

This paper presents a robust and efficient very high-order scheme for compressible flow simulation, addressing critical limitations of existing high-order methods. The proposed scheme combines the compact gas-kinetic scheme (CGKS) with an adaptive stencil extension reconstruction with discontinuity feedback factor (ASE-DFF), achieving significant improvements in both robustness and computational efficiency. Traditional weighted essentially non-oscillatory (WENO) schemes suffer from reduced robustness at higher order and require costly smoothness indicators for large stencils. Meanwhile, compact methods based on Discontinuous Galerkin (DG) and Flux Reconstruction (FR) struggle with poor time-marching efficiency. In contrast, the ASE-DFF-CGKS introduces two key innovations: (1) a unified framework enabling arbitrarily high-order compact gas-kinetic scheme without sacrificing large CFL number, and (2) a discontinuity feedback factor that eliminates the need for expensive smoothness indicator calculations while essentially keeping first-order robustness near discontinuities. The scheme's advantages are demonstrated through benchmark simulations. It maintains a CFL number above 0.5 for up to 9th-order case, unlike conventional compact methods that restrict a CFL less than 0.05. Also it delivers high-resolution results for flow involving strong shock and rarefaction wave. This work provides a practically impactful solution for high-fidelity compressible flow simulation, balancing computational efficiency, high-order accuracy and robustness in challenging flow regimes.

physics.comp-ph↗
arXiv2025

A well-balanced gas-kinetic scheme with adaptive mesh refinement for shallow water equations

This paper presents the development of a well-balanced gas-kinetic scheme (GKS) with space-time adaptive mesh refinement (STAMR) for the shallow water equations (SWE). While well-balanced GKS have been established on Cartesian and triangular meshes, the proposed STAMR framework utilizes arbitrary quadrilateral meshes with hanging nodes, introducing additional challenges for maintaining well-balanced properties. In addition to spatial adaptivity, temporal adaptivity is incorporated by assigning adaptive time steps to cells at different refinement levels, further enhancing computational efficiency. Furthermore, the numerical flux in the GKS adaptively transitions between equilibrium fluxes for smooth flows and non-equilibrium fluxes for discontinuities, providing the proposed GKS-based STAMR method with strong robustness, high accuracy, and high resolution. Standard benchmark tests and real-world case studies validate the effectiveness of the GKS-based STAMR and demonstrate its potential for interface capturing and the simulation of complex flows.

math.NA↗
arXiv2025

Performance evaluation of high-order compact and second-order gas-kinetic schemes in compressible flow simulations

The trade-off among accuracy, robustness, and computational cost remains a key challenge in simulating complex flows. Second-order schemes are computationally efficient but lack the accuracy required for resolving intricate flow structures, particularly in turbulence. High-order schemes, especially compact high-order schemes, offer superior accuracy and resolution at a relatively modest computational cost. To clarify the practical performance of high-order schemes in scale-resolving simulations, this study evaluates two representative gas-kinetic schemes: the newly developed fifth-order compact gas-kinetic scheme (CGKS-5th) and the conventional second-order gas-kinetic scheme (GKS-2nd). Test cases ranging from subsonic to supersonic flows are used to quantitatively assess their accuracy and efficiency. The results demonstrate that CGKS-5th achieves comparable resolution to GKS-2nd at roughly an order of magnitude lower computational cost. Under equivalent computational resources, CGKS-5th delivers significantly higher accuracy and resolution, particularly in turbulent flows involving shocks and small-scale vortices. This study provides the first clear verification of the advantages of high-order compact gas-kinetic schemes in simulating viscous flows with discontinuities. Additionally, multi-GPU parallelization using CUDA and MPI is implemented to enable large-scale applications.

math.NA↗
arXiv2025

Broadband Near-Infrared Compressive Spectral Imaging System with Reflective Structure

Near-infrared (NIR) hyperspectral imaging has become a critical tool in modern analytical science. However, conventional NIR hyperspectral imaging systems face challenges including high cost, bulky instrumentation, and inefficient data collection. In this work, we demonstrate a broadband NIR compressive spectral imaging system that is capable of capturing hyperspectral data covering a broad spectral bandwidth ranging from 700 to 1600 nm. By segmenting wavelengths and designing specialized optical components, our design overcomes hardware spectral limitations to capture broadband data, while the reflective optical structure makes the system compact. This approach provides a novel technical solution for NIR hyperspectral imaging.

eess.IV↗
arXiv2025

An effective implementation of high-order compact gas-kinetic scheme on structured meshes for compressible flows

A novel fifth-order compact gas-kinetic scheme is developed for high-resolution simulation of compressible flows on structured meshes. Its accuracy relies on a new multidimensional fifth-order compact reconstruction that uses line-averaged derivatives to introduce additional degrees of freedom, enabling a compact stencil with superior resolution. For non-orthogonal meshes, reconstruction is performed on a standard reference cell in a transformed computational space. This approach provides a unified polynomial form, significantly reducing memory usage and computational cost while simplifying implementation compared to direct multi-dimensional or dimension-by-dimension methods. A nonlinear adaptive method ensures high accuracy and robustness by smoothly transitioning from the high-order linear scheme in smooth regions to a second-order scheme at discontinuities. The method is implemented with multi-GPU parallelization using CUDA and MPI for large-scale applications. Comprehensive numerical tests, from subsonic to supersonic turbulence, validate the scheme's high accuracy, resolution and excellent robustness.

math.NA↗
arXiv2025

An implicit gas-kinetic scheme for internal and external flows

The gas-kinetic scheme(GKS) is a promising computational fluid dynamics (CFD) method for solving the Navier-Stokes equations. It is based on the analytical solution of the BGK equation, which enables accurate and robust simulations. While GKS has demonstrated excellent properties (e.g., unified treatment of inviscid and viscous fluxes, inherent adaptive dissipation control), its application to classical engineering problems, such as aerodynamic flows and fluid machinery, remains underdeveloped compared to conventional CFD methods. This study bridges this gap by advancing GKS capabilities for real-world engineering challenges. First, the GKS is extended to a rotating coordinate frame, enabling efficient simulations of internal flows in turbomachinery. Second, the computational inefficiency of explicit GKS is addressed through an implicit time discretization using the generalized minimal residual method. The Jacobian matrices for inviscid/viscous fluxes are approximated using the first-order kinetic flux vector splitting scheme and the thin shear layer approximation to enhance robustness and computational efficiency further. Third, the shear-stress transport turbulence model is coupled to expand GKS's applicability to industrial turbulent flows. Numerical tests, including internal compressor rotor flow and external flow over a 3-D wingbody, validate the proposed method's accuracy and efficiency. Via our implicit scheme, the force coefficients of the 3-D wing-body flow with about five million mesh elements can converge after 500 steps. This work represents a practical advancement of GKS, demonstrating its potential to compete with established CFD solvers in high-Reynolds-number external and internal turbulent flows.

physics.flu-dyn↗
arXiv2025

A generalized ENO reconstruction in compact GKS for compressible flow simulations

This paper presents a generalized ENO (GENO)-type nonlinear reconstruction scheme for compressible flow simulations. The proposed reconstruction preserves the accuracy of the linear scheme while maintaining essentially non-oscillatory behavior at discontinuities. By generalizing the adaptive philosophy of ENO schemes, the method employs a smooth path function that directly connects high-order linear reconstruction with a reliable lower-order alternative. This direct adaptive approach significantly simplifies the construction of nonlinear schemes, particularly for very high-order methods on unstructured meshes. A comparative analysis with various WENO methods demonstrates the reliability and accuracy of the proposed reconstruction, which provides an optimal transition between linear and nonlinear reconstructions across all limiting cases based on stencil smoothness. The consistency and performance of the GENO reconstruction are validated through implementation in both high-order compact gas-kinetic schemes (GKS) and non-compact Riemann-solver-based methods. Benchmark tests confirm the robustness and shock-capturing capabilities of GENO, with particularly superior performance when integrated with compact schemes. This work advances the construction methodology of nonlinear schemes and establishes ENO-type reconstruction as a mature and practical approach for engineering applications.

math.NA↗
arXiv2025

Wave-Particle Turbulence Simulation of Spatially Developing Round Jets: Turbulent Flow Modeling and Method Validation

Spatially developing round jet flows are fundamental to numerous engineering applications. This letter applies the wave-particle turbulence simulation (WPTS) method, a recently developed multiscale approach, to simulate a spatially developing circular jet at Reynolds number 5000, a canonical configuration for validating turbulence models. The study aims to further establish the effectiveness and accuracy of WPTS for shear-driven turbulent flows. WPTS employs a multiscale framework that couples wave and particle components, where the wave component captures cell-resolved flow structures while the particle component models sub-grid flow information through non-equilibrium transport. Using a computational grid containing only 2% of the cells required for direct numerical simulation (DNS), WPTS successfully predicts both qualitative flow features and quantitative turbulence statistics, including: the characteristic linear decay of centerline velocity, radial profiles of mean velocity, and anisotropic Reynolds stress components. The results demonstrate excellent agreement with DNS data and experimental measurements. These findings establish WPTS as an effective computational tool for turbulence simulation, capable of maintaining high fidelity in capturing essential turbulence characteristics while utilizing significantly coarser grids than traditional methods. The successful application to turbulent jet flow demonstrates the method's potential for extension to more complex engineering flow configurations, offering a computationally efficient alternative for industrial applications.

physics.flu-dyn↗
arXiv2025

Describing the Nonuniversal Galaxy Merger Timescales in IllustrisTNG: Effects of Host Halo Mass, Baryons, and Sample Selection

Galaxy merger timescales are crucial for understanding and modeling galaxy formation in our hierarchically structured Universe. However, previous studies have reported widely varying dependencies of merger timescales on initial orbital parameters and mass ratio at the first crossing of $r_{\rm vir}$. Using IllustrisTNG simulations, we find that these dependencies vary with host halo mass, suggesting that discrepancies in prior studies may arise from differences in the systems analyzed. Specifically, in low-mass halos, merger timescales show a stronger dependence on initial orbital parameters, while in high-mass halos, this dependence weakens. To account for these variations, we present a fitting formula that incorporates host mass dependence, achieving a logarithmic scatter smaller than 0.15 dex. Comparing dark matter-only and baryonic simulations, we observe similar merger timescales for circular orbits but notable differences for radial orbits. In halos with $M_{\rm{host}} < 10^{12.5} h^{-1} M_{\odot}$, mergers in dark matter-only runs take longer than in baryonic runs, whereas the trend reverses in more massive halos. We attribute these differences to the competing effects of tidal disruption by central galaxy disks and the resistance of baryonic satellites to tidal stripping. Finally, we extend our model to predict merger timescales from any starting radius within the halo. By fitting the extended model to the entire infall sample, we find that using only the merger sample can underestimate merger timescales, particularly for low mass ratios. Our model provides a valuable tool for improving semi-analytical and empirical models of galaxy formation.

astro-ph.GA↗
arXiv2025

The Dependence of Dark Matter Halo Properties on the Morphology of Their Central Galaxies from Weak Lensing

Xu \& Jing reported a monotonic relationship between host halo mass $M_h$ and the morphology of massive central galaxies, characterized by the Sérsic index $n$, at fixed stellar mass, suggesting that morphology could serve as a good secondary proxy for halo mass. Since their results were derived using the indirect abundance matching method, we further investigate the connection between halo properties and central galaxy morphology using weak gravitational lensing. We apply galaxy-galaxy lensing to measure the excess surface density around CMASS central galaxies with stellar masses in the range of $11.3 < \log M_*/{\rm M_\odot} < 11.7$, using the HSC shear catalog processed through the Fourier\_Quad pipeline. By dividing the sample based on $n$, we confirm a positive correlation between $n$ and $M_h$, and observe a possible evidence of the positive correlation of $n$ and halo concentration. After accounting for color, we find that neither color nor morphology alone can determine halo mass, suggesting that a combination of both may serve as a better secondary proxy. In comparison to hydrodynamic simulations, we find that TNG300 produce much weaker correlations between $M_h$ and $n$. Furthermore, using SIMBA simulations with different feedback mode, we find jet-mode active galactic nuclei feedback might be related to the relationship of Sérsic index and halo mass.

astro-ph.GA↗
arXiv2025

UGKWP and IUGKP methods for Multi-Scale Phonon Transport with Dispersion and Polarization

This paper presents two novel methods for solving multi-scale phonon transport problems with dispersion and polarization effects: the unified gas-kinetic wave-particle (UGKWP) method and the implicit unified gas-kinetic particle (IUGKP) method. Both approaches are based on solving multiple groups of BGK equations at discrete frequency points. The UGKWP method constructs multiscale macroscopic fluxes at cell interfaces through the integral solution of the unsteady BGK equation and efficiently captures non-equilibrium transport using statistical particles. Its wave-particle adaptive framework ensures computational efficiency across different regimes: in the diffusive limit, it matches the cost of explicit diffusion equation solutions, while in the ballistic limit, it performs comparably to pure particle methods. The IUGKP method, specifically designed for steady-state problems, determines the particle evolution scale based on the physical mean free path. This approach enables rapid convergence at both large and small Knudsen numbers, with the latter facilitated by a newly constructed macroscopic prediction equation. Both methods incorporate an adaptive frequency-space sampling technique that maintains particle counts per cell comparable to single-frequency methods, significantly improving computational efficiency and memory usage. The accuracy and efficiency of both methods are validated through various numerical tests, including large-scale three-dimensional conduction heat transfer simulations. Results demonstrate their effectiveness in handling complex phonon transport phenomena across multiple scales.

physics.comp-ph↗
arXiv2025

Adaptive criterion and modification of wave-particle decomposition in UGKWP method for high-speed flow simulation

Benefitting from the direct modeling of physical laws in a discretized space and the automatic decomposition of hydrodynamic waves and particles, the unified gas-kinetic wave-particle (UGKWP) method offers notable advantages in various multiscale physics, such as hypersonic flow, plasma transport and radiation transport. Aiming at achieving a more suitable and efficient wave-particle decomposition in high-speed flow simulation and enhancing the performance in the drastic scale variation region, in this work, the scale adaptive criterion is studied and the flux evolution of UGKWP method is modified. Specifically, besides the perspective of time which is naturally considered in the time-dependent distribution function of UGKWP method, two more criteria from views of space and gradient are utilized to identify the local scale, and to reduce the computational consumption of particles on describing the near-equilibrium microscopic gas distribution function. Moreover, corresponding to the coefficients in the time integration flux of unified gas-kinetic scheme (UGKS), the evolution of hydrodynamic wave is modified to be more consistent with particles, which is essential when the scale changes intensely in different cells. A variety of test cases are conducted to validate the performance of the adaptive UGKWP method, including hypersonic flows around a cylinder at multiple inflow Knudsen numbers, hypersonic flow over a slender cavity, side-jet impingement on hypersonic flow and three-dimensional hypersonic flows over a $70^{\circ}$ blunted cone with a cylindrical sting.

physics.comp-ph↗
arXiv2025

Propagation of chaos for mean-field reflected BSDEs with jumps

In this paper, we study a class of mean-field reflected backward stochastic differential equations (MF-RBSDEs) driven by a marked point process and also analyze MF-RBSDEs driven by a Poisson process. Based on a $g$-expectation representation lemma, we give the existence and uniqueness of the particle system of MF-RBSDEs driven by a marked point process under Lipschitz generator conditions and obtain a convergence result of this system. We also establish the well-posedness of the MF-RBSDEs driven by a Poisson process and the convergence rate of the corresponding particle system towards the solution to the MF-RBSDEs driven by a Poisson process under bounded terminal, bounded obstacle conditions.

math.PR↗