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arXiv 2204.04712cond-mat.stat-mechhep-lat
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减少统计物理模拟的临界慢化

Reduced critical slowing down for statistical physics simulations

Kurt Langfeld, Pavel Buividovich, P. E. L Rakow, James Roscoe

摘要:

Wang-Landau模拟提供了在集体坐标上显式积分的可能性,并在剩余的位形空间上随机积分。我们建议选择所谓的“慢模式”,这是负责大的自相关时间,从而临界放缓,集体整合。我们以伊辛模型和线性对数松弛(LLR)方法为仿真算法研究了这一方案。我们首先展示了超临界慢化的阶段,自发破缺对称性和热浴算法,自相关时间随系统大小呈指数增长。相比之下,使用集体坐标的磁化强度,我们提出的证据表明,超临界减速是不存在的。我们仍然观察到自相关时间随体积的多项式增加(临界减慢),然而,与局部更新技术相比,其数量级减少。

英文摘要:

Wang-Landau simulations offer the possibility to integrate explicitly over a collective coordinate and stochastically over the remainder of configuration space. We propose to choose the so-called "slow mode", which is responsible for large autocorrelation times and thus critical slowing down, for collective integration. We study this proposal for the Ising model and the linear-log-relaxation (LLR) method as simulation algorithm. We firstly demonstrate super critical slowing down in a phase with spontaneously broken symmetry and for the heatbath algorithms, for which autocorrelation times grow exponentially with system size. By contrast, using the magnetisation as collective coordinate, we present evidence that super critical slowing down is absent. We still observe a polynomial increase of the autocorrelation time with volume (critical slowing down), which is however reduced by orders of magnitude when compared to local update techniques.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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