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arXiv 1409.6948cond-mat.stat-mech
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稠密硬球和高分子体系的事件链算法

Parallelized event chain algorithm for dense hard sphere and polymer systems

Tobias Alexander Kampmann, Horst-Holger Boltz, Jan Kierfeld

摘要:

本文将并行化与簇蒙特卡罗方法相结合,提出了一种适用于二维硬盘系统的并行事件链算法。对于并行化,我们使用空间分区的方法模拟细胞。我们发现,这是至关重要的正确性,以确保细致平衡的水平上的蒙特卡罗扫描绘制的起始球的事件链内的每个模拟单元与替换。我们分析的并行化事件链的性能收益,并找到一个标准的最佳程度的并行化。由于事件链移动的集群性质,大规模并行化将不是最佳的。最后,我们讨论了第一个应用程序的事件链算法的稠密聚合物系统,即,有吸引力的半柔性聚合物的形成溶液。

英文摘要:

We combine parallelization and cluster Monte Carlo for hard sphere systems and present a parallelized event chain algorithm for the hard disk system in two dimensions. For parallelization we use a spatial partitioning approach into simulation cells. We find that it is crucial for correctness to ensure detailed balance on the level of Monte Carlo sweeps by drawing the starting sphere of event chains within each simulation cell with replacement. We analyze the performance gains for the parallelized event chain and find a criterion for an optimal degree of parallelization. Because of the cluster nature of event chain moves massive parallelization will not be optimal. Finally, we discuss first applications of the event chain algorithm to dense polymer systems, i.e., bundle-forming solutions of attractive semiflexible polymers.

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