Multiscale Numerical Schemes for the Collisional Vlasov Equation in the Finite Larmor Radius Approximation Regime

IF 1.9 4区 数学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Multiscale Modeling & Simulation Pub Date : 2023-09-14 DOI:10.1137/22m1496839
Anaïs Crestetto, Nicolas Crouseilles, Damien Prel
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Abstract

This work is devoted to the construction of multiscale numerical schemes efficient in the finite Larmor radius approximation of the collisional Vlasov equation. Following the paper of Bostan and Finot [Commun. Contemp. Math., 22 (2020), 1950047], the system involves two different regimes, a highly oscillatory and a dissipative regime, whose asymptotic limits do not commute. In this work, we consider a Particle-in-Cell discretization of the collisional Vlasov system which enables us to deal with the multiscale characteristics equations. Different multiscale time integrators are then constructed and analyzed. We prove asymptotic properties of these schemes in the highly oscillatory regime and in the collisional regime. In particular, the asymptotic preserving property towards the modified equilibrium of the averaged collision operator is recovered. Numerical experiments are then shown to illustrate the properties of the numerical schemes.
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有限Larmor半径近似下碰撞Vlasov方程的多尺度数值格式
本文研究了碰撞Vlasov方程的有限Larmor半径近似的多尺度数值格式的构造。继Bostan and Finot (common)的文件之后。一栏。数学。[j], 22(2020), 1950047],系统涉及两个不同的状态,一个高振荡状态和一个耗散状态,其渐近极限不交换。在这项工作中,我们考虑了碰撞Vlasov系统的单元内粒子离散化,使我们能够处理多尺度特征方程。然后构造并分析了不同的多尺度时间积分器。我们证明了这些格式在高振荡区和碰撞区的渐近性质。特别地,恢复了平均碰撞算子对修正平衡的渐近保持性质。数值实验说明了数值格式的性质。
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来源期刊
Multiscale Modeling & Simulation
Multiscale Modeling & Simulation 数学-数学跨学科应用
CiteScore
2.80
自引率
6.20%
发文量
45
审稿时长
6-12 weeks
期刊介绍: Centered around multiscale phenomena, Multiscale Modeling and Simulation (MMS) is an interdisciplinary journal focusing on the fundamental modeling and computational principles underlying various multiscale methods. By its nature, multiscale modeling is highly interdisciplinary, with developments occurring independently across fields. A broad range of scientific and engineering problems involve multiple scales. Traditional monoscale approaches have proven to be inadequate, even with the largest supercomputers, because of the range of scales and the prohibitively large number of variables involved. Thus, there is a growing need to develop systematic modeling and simulation approaches for multiscale problems. MMS will provide a single broad, authoritative source for results in this area.
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