Stochastic weighted particle control for electrostatic particle-in-cell Monte Carlo collision simulations in an axisymmetric coordinate system

IF 7.2 2区物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Physics Communications Pub Date : 2024-10-04 DOI:10.1016/j.cpc.2024.109390

Zili Chen , Zhaoyu Chen , Yu Wang , Jingwen Xu , Zhipeng Chen , Wei Jiang , Hongyu Wang , Ya Zhang

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引用次数: 0

Abstract

The non-uniform grids in the axisymmetric coordinate system pose a significant challenge for electrostatic particle-in-cell/Monte Carlo collision (PIC/MCC) simulations because they require numerous macroparticles to manage numerical heating around the mid-axis. To address this, we have developed a stochastic weighted particle control method that selectively samples small-weight particles, effectively controlling the particle number without inducing numerical heating. This method is based on a rejection-acceptance probability merging scheme, which is easy to implement and has a low time complexity. We have also made essential modifications, including a corrected density deposition scheme, an energy conservation scheme, and the introduction of target weights. By applying this particle control method, the number of macroparticles in the simulation can be reduced by more than one order of magnitude, significantly reducing the required computing time and storage. Furthermore, appropriately setting target weights also enables enhanced resolution of dilute regions with an acceptable increase in computational cost.

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轴对称坐标系中静电粒子-细胞蒙特卡洛碰撞模拟的随机加权粒子控制

轴对称坐标系中的非均匀网格给静电粒子入胞/蒙特卡洛碰撞（PIC/MCC）模拟带来了巨大挑战，因为它们需要大量大粒子来控制中轴附近的数值加热。为了解决这个问题，我们开发了一种随机加权粒子控制方法，该方法可选择性地对小重量粒子进行采样，从而在不引起数值加热的情况下有效控制粒子数量。该方法基于拒绝-接受概率合并方案，易于实现且时间复杂度低。我们还做了一些必要的修改，包括修正密度沉积方案、能量守恒方案和目标权重的引入。通过应用这种粒子控制方法，模拟中的大粒子数量可以减少一个数量级以上，从而大大减少了所需的计算时间和存储空间。此外，适当设置目标权重还能在可接受的计算成本增加的情况下提高稀释区域的分辨率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Physics Communications 物理-计算机：跨学科应用

CiteScore

12.10

自引率

3.20%

发文量

287

审稿时长

5.3 months

期刊介绍： The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.