Adaptive mesh refinement in semi-implicit particle-in-cell method

IF 3.4 2区物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Physics Communications Pub Date : 2025-08-11 DOI:10.1016/j.cpc.2025.109806

Talha Arshad, Yuxi Chen, Gábor Tóth

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引用次数: 0

Abstract

The particle-in-cell (PIC) method is powerful for simulating plasma kinetic processes. However, PIC simulations are usually computationally expensive, and improving the computational efficiency is essential for expanding their capabilities. Adaptive mesh refinement (AMR) is an important technique that can be applied to accelerate PIC simulations. In this paper, we introduce a novel adaptive mesh refinement (AMR) algorithm that is implemented for a semi-implicit electromagnetic particle-in-cell (PIC) code. Our approach supports different refinement ratios as well as multiple refinement levels. The electric field solver is carefully designed to minimize artifacts at interfaces of different levels, and we introduce an algorithm to reduce errors in Gauss's law across all levels. To maintain a uniform particle distribution, which is crucial for achieving high computational efficiency, particle splitting and merging techniques are integrated into the code. We validate our algorithm with several tests, including a two-dimensional double current sheet reconnection test, that show accurate solutions on the AMR grid with considerable speed-up relative to a uniform high-resolution grid.

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半隐式单元内粒子法的自适应网格细化

粒子池（PIC）方法是模拟等离子体动力学过程的有效方法。然而，PIC模拟通常在计算上很昂贵，提高计算效率对于扩展其功能至关重要。自适应网格细化（AMR）是加速PIC仿真的一项重要技术。本文介绍了一种新的自适应网格细化（AMR）算法，该算法适用于半隐式电磁粒子单元码（PIC）。我们的方法支持不同的细化比例以及多个细化级别。电场求解器经过精心设计，以尽量减少不同层次界面上的伪像，并引入了一种算法来减少高斯定律在所有层次上的误差。为了保持均匀的粒子分布，这是实现高计算效率的关键，在代码中集成了粒子分裂和合并技术。我们通过几个测试验证了我们的算法，包括一个二维双电流片重连接测试，结果显示，相对于均匀的高分辨率网格，AMR网格上的精确解决方案具有相当大的加速。

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.