TY - JOUR

T1 - Weakly convergent stochastic simulation of electron collisions in plasmas

AU - Wu, Wentao

AU - Liu, Jian

AU - Fisch, Nathaniel J.

AU - Xiao, Jianyuan

AU - Cai, Huishan

AU - Liu, Zhaoyuan

AU - Zhang, Ruili

AU - He, Yang

N1 - Funding Information:
This research is supported by the National Natural Science Foundation of China (Grant Nos. 11901564 , 11775222 ), the National Magnetic Confinement Fusion Energy Research and Development Program of China ( 2019YFE03090100 ), the Key Research Program of Frontier Sciences CAS ( QYZDB-SSW-SYS004 ), and the Geo-Algorithmic Plasma Simulator (GAPS) Project.
Publisher Copyright:
© 2023 Elsevier B.V.

PY - 2023/8

Y1 - 2023/8

N2 - Collisions between charged particles can be described and solved using Monte Carlo methods in the framework of stochastic differential equations (SDEs). In this paper, we start from an SDE including the extended Lorentz collision operator, which can recover the collisions between a sampling electron and background ions and electrons. On this basis, we construct a second order weakly convergent algorithm (WCA2) to simulate collisional effects of electrons in plasmas. Superseding the Weiner process by a three-point distribution, WCA2 possesses high weakly convergent accuracy as well as low computational costs. The definition and properties of weak convergence are discussed in detail. The weakly convergent order of WCA2 is verified both theoretically and numerically. Through two trial moment functions, we carefully analyze the numerical solutions of the SDE using rigorous statistical tests in the sense of weak convergence. The criteria and practical operations of finding the benchmark solution of SDEs are introduced at length. In order to illustrate the power of WCA2, we apply it to simulate the backward runaways in plasmas, which is a dramatic physical phenomenon. By comparison with the Euler-Maruyama method and the Cadjan-Ivanov method, the advantage and efficiency of WCA2 is exhibited. The backward runaway probability and its dependence on initial conditions are accurately studied using WCA2.

AB - Collisions between charged particles can be described and solved using Monte Carlo methods in the framework of stochastic differential equations (SDEs). In this paper, we start from an SDE including the extended Lorentz collision operator, which can recover the collisions between a sampling electron and background ions and electrons. On this basis, we construct a second order weakly convergent algorithm (WCA2) to simulate collisional effects of electrons in plasmas. Superseding the Weiner process by a three-point distribution, WCA2 possesses high weakly convergent accuracy as well as low computational costs. The definition and properties of weak convergence are discussed in detail. The weakly convergent order of WCA2 is verified both theoretically and numerically. Through two trial moment functions, we carefully analyze the numerical solutions of the SDE using rigorous statistical tests in the sense of weak convergence. The criteria and practical operations of finding the benchmark solution of SDEs are introduced at length. In order to illustrate the power of WCA2, we apply it to simulate the backward runaways in plasmas, which is a dramatic physical phenomenon. By comparison with the Euler-Maruyama method and the Cadjan-Ivanov method, the advantage and efficiency of WCA2 is exhibited. The backward runaway probability and its dependence on initial conditions are accurately studied using WCA2.

KW - Backward runaway

KW - Boltzmann equations

KW - Lorentz collision operator

KW - Stochastic differential equation

KW - Weak convergence

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U2 - 10.1016/j.cpc.2023.108758

DO - 10.1016/j.cpc.2023.108758

M3 - Article

AN - SCOPUS:85153512454

SN - 0010-4655

VL - 289

JO - Computer Physics Communications

JF - Computer Physics Communications

M1 - 108758

ER -