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Apar-T: code, validation, and physical interpretation of particle-in-cell results

机译:Apar-T:细胞内颗粒结果的代码,验证和物理解释

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We present the parallel particle-in-cell (PIC) code Apar-T and, more importantly, address the fundamental question of the relations between the PIC model, the Vlasov-Maxwell theory, and real plasmas. First, we present four validation tests: spectra from simulations of thermal plasmas, linear growth rates of the relativistic tearing instability and of the filamentation instability, and nonlinear filamentation merging phase. For the filamentation instability we show that the effective growth rates measured on the total energy can differ by more than 50% from the linear cold predictions and from the fastest modes of the simulation. We link these discrepancies to the superparticle number per cell and to the level of field fluctuations. Second, we detail a new method for initial loading of Maxwell-Jüttner particle distributions with relativistic bulk velocity and relativistic temperature, and explain why the traditional method with individual particle boosting fails. The formulation of the relativistic Harris equilibrium is generalized to arbitrary temperature and mass ratios. Both are required for the tearing instability setup. Third, we turn to the key point of this paper and scrutinize the question of what description of (weakly coupled) physical plasmas is obtained by PIC models. These models rely on two building blocks: coarse-graining, i.e., grouping of the order of p?~?1010 real particles into a single computer superparticle, and field storage on a grid with its subsequent finite superparticle size. We introduce the notion of coarse-graining dependent quantities, i.e., quantities depending on p. They derive from the PIC plasma parameter ΛPIC, which we show to behave as ΛPIC?∝?1/p. We explore two important implications. One is that PIC collision- and fluctuation-induced thermalization times are expected to scale with the number of superparticles per grid cell, and thus to be a factor p?~?1010 smaller than in real plasmas, a fact that we confirm with simulations. The other is that the level of electric field fluctuations scales as 1/ΛPIC?∝?p. We provide a corresponding exact expression, taking into account the finite superparticle size. We confirm both expectations with simulations. Fourth, we compare the Vlasov-Maxwell theory, often used for code benchmarking, to the PIC model. The former describes a phase-space fluid with Λ?=??+?∞ and no correlations, while the PIC plasma features a small Λ and a high level of correlations when compared to a real plasma. These differences have to be kept in mind when interpreting and validating PIC results against the Vlasov-Maxwell theory and when modeling real physical plasmas.
机译:我们提出了并行的单元格内粒子(PIC)代码Apar-T,更重要的是,解决了PIC模型,Vlasov-Maxwell理论与实际等离子体之间的关系的基本问题。首先,我们提出了四个验证测试:来自热等离子体模拟的光谱,相对论撕裂不稳定性和细丝不稳定性的线性增长率以及非线性细丝合并阶段。对于丝状失稳,我们表明,根据总能量测得的有效增长率与线性冷预测和最快的模拟模式相差50%以上。我们将这些差异链接到每个单元的超粒子数和场波动的水平。其次,我们详细介绍了一种用相对论体积速度和相对论温度初始加载麦克斯韦-于特纳粒子分布的新方法,并解释了为什么传统的采用单个粒子增强的方法失败的原因。相对论哈里斯平衡的公式被推广到任意的温度和质量比。撕裂不稳定性设置都需要这两者。第三,我们转向本文的重点,并仔细研究了通过PIC模型获得的对(弱耦合)物理等离子体的描述是什么。这些模型依赖于两个构建块:粗粒度,即将p10〜1010真实粒子的数量分组到单个计算机超粒子中,以及具有随后的有限超粒子尺寸的网格存储。我们介绍了粗粒度相关量的概念,即取决于p的量。它们来自PIC等离子体参数ΛPIC,我们证明它的行为为ΛPIC?∝?1 / p。我们探讨了两个重要含义。一个是,PIC碰撞和波动引起的热化时间预计会随着每个网格单元中超粒子的数量而变化,因此比实际等离子体中的小p?〜?1010,这是我们通过仿真确认的事实。另一个是电场起伏的水平定为1 / ΛPIC∝πp。考虑到有限的超微粒大小,我们提供了一个相应的精确表达式。我们通过仿真确认了两种期望。第四,我们将通常用于代码基准测试的Vlasov-Maxwell理论与PIC模型进行比较。前者描述了一种具有Λ?=?+?∞且没有相关性的相空间流体,而PIC等离子体与实际等离子体相比具有较小的Λ和较高的相关性。在根据Vlasov-Maxwell理论解释和验证PIC结果以及对实际物理等离子体建模时,必须牢记这些差异。

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