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相关论文: Reduced Particle in Cell method for the Vlasov-Poi…

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Numerical schemes that preserve the structure of the kinetic equations can provide stable simulation results over a long time. An electromagnetic particle-in-cell solver for the Vlasov-Maxwell equations that preserves at the discrete level…

数值分析 · 数学 2020-02-24 Benedikt Perse , Katharina Kormann , Eric Sonnendrücker

We present an efficient and accurate energy-conserving implicit particle-in-cell~(PIC) algorithm for the electrostatic Vlasov system, with particular emphasis on its high robustness for simulating complex plasma systems with multiple…

计算物理 · 物理学 2022-11-21 Zhuoning Li , Zhenli Xu , Zhiguo Yang

Despite advancements in high-performance computing and modern numerical algorithms, computational cost remains prohibitive for multi-query kinetic plasma simulations. In this work, we develop data-driven reduced-order models (ROMs) for…

In this work, we develop and rigorously analyze a new class of particle methods for the magnetized Vlasov--Poisson--Fokker--Planck system. The proposed approach addresses two fundamental challenges: (1) the curse of dimensionality, which we…

数值分析 · 数学 2025-03-03 Anjiao Gu , Xiaojiang Zhang

We propose and study a Particle-In-Cell (PIC) method based on the Crank-Nicolson time discretization for the Vlasov-Poisson system with a strong and inhomogeneous external magnetic field with fixed direction, where we focus on the motion of…

数值分析 · 数学 2025-12-04 Francis Filbet , L Miguel Rodrigues , Kim Han Trinh

Model reduction of high-dimensional dynamical systems alleviates computational burdens faced in various tasks from design optimization to model predictive control. One popular model reduction approach is based on projecting the governing…

动力系统 · 数学 2018-08-24 Francisco J. Gonzalez , Maciej Balajewicz

The kinetic analyses of many-particle soft matter often employ many simulation studies of various physical phenomena which supplement the experimental limitations or compliment the theoretical findings of the study. Such simulations are…

等离子体物理 · 物理学 2024-05-28 Allen Lobo , Vinod Kumar Sayal

Energy conserving particle-in-cell schemes are constructed for a class of reduced relativistic Vlasov--Maxwell equations of laser-plasma interaction. Discrete Poisson equation is also satisfied by the numerical solution. Specifically,…

数值分析 · 数学 2022-11-30 Yingzhe Li

We revisit the Scovel-Weinstein framework (Scovel & Weinstein, CPAM 1994) for reducing the Vlasov-Poisson system while preserving its Hamiltonian structure. Standard particle-in-cell (PIC) algorithms approximate the distribution function by…

数值分析 · 数学 2026-05-22 Mandela B. Quashie , J. W. Burby , Andrew J. Christlieb , Qi Tang

We develop new numerical schemes for Vlasov--Poisson equations with high-order accuracy. Our methods are based on a spatially monotonicity-preserving (MP) scheme and are modified suitably so that positivity of the distribution function is…

计算物理 · 物理学 2017-11-08 Satoshi Tanaka , Kohji Yoshikawa , Takashi Minoshima , Naoki Yoshida

Computing reduced-order models using non-intrusive methods is particularly attractive for systems that are simulated using black-box solvers. However, obtaining accurate data-driven models can be challenging, especially if the underlying…

数学物理 · 物理学 2024-01-03 Alberto Padovan , Blaine Vollmer , Daniel J. Bodony

We present the standard electromagnetic Particle-in-Cell method, starting from the discrete approximation of derivatives on a uniform grid. The application to second-order, centered, finite-difference discretization of the equations of…

计算物理 · 物理学 2020-08-18 J. L. Vay

This paper presents a novel non-linear model reduction method: Probabilistic Manifold Decomposition (PMD), which provides a powerful framework for constructing non-intrusive reduced-order models (ROMs) by embedding a high-dimensional system…

数值分析 · 数学 2026-01-09 Jiaming Guo , Dunhui Xiao

Explicit high-order non-canonical symplectic particle-in-cell algorithms for classical particle-field systems governed by the Vlasov-Maxwell equations are developed. The algorithm conserves a discrete non-canonical symplectic structure…

等离子体物理 · 物理学 2016-03-15 Jianyuan Xiao , Hong Qin , Jian Liu , Yang He , Ruili Zhang , Yajuan Sun

In this work, we propose a framework that constructs reduced order models for nonlinear structural mechanics in a nonintrusive fashion, and can handle large scale simulations. We identify three steps that are carried out separately in time,…

数值分析 · 数学 2023-02-02 Fabien Casenave , Nissrine Akkari , Felipe Bordeu , Christian Rey , David Ryckelynck

For decades, the Vlasov-Darwin model has been recognized to be attractive for particle-in-cell (PIC) kinetic plasma simulations in non-radiative electromagnetic regimes, to avoid radiative noise issues and gain computational efficiency.…

计算物理 · 物理学 2016-05-04 Guangye Chen , Luis Chacon

Recently developed reduced-order modeling techniques aim to approximate nonlinear dynamical systems on low-dimensional manifolds learned from data. This is an effective approach for modeling dynamics in a post-transient regime where the…

动力系统 · 数学 2023-09-27 Samuel E. Otto , Gregory R. Macchio , Clarence W. Rowley

We present a novel structure-preserving framework for solving the Vlasov-Poisson-Landau system of equations using a particle in cell (PIC) discretization combined with discrete gradient time integrators. The Vlasov-Poisson-Landau system is…

等离子体物理 · 物理学 2026-02-16 Daniel S. Finn , Joseph V. Pusztay , Matthew G. Knepley , Mark F. Adams

Particle discretizations of partial differential equations are advantageous for high-dimensional kinetic models in phase space due to their better scalability than continuum approaches with respect to dimension. Complex processes…

等离子体物理 · 物理学 2025-12-23 Mark F. Adams , Daniel S. Finn , Matthew G. Knepley , Joseph V. Pusztay

In this study, we develop an extended implicit moment method, namely, a coupled high-order low-order (HOLO) method and apply it to the electromagnetic Vlasov-Darwin model. The high-order (HO) system evolves particles in a manner that…

等离子体物理 · 物理学 2025-08-13 Derek A. Kuldinow , William T. Taitano , Kentaro Hara