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北美退伍军人节(Veterans Day),12 日无更新
arXiv 1709.01665cond-mat.stat-mechphysics.comp-ph
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经典XY模型提升事件在事件链Monte Carlo中的反常扩散分析

Anomalous diffusion analysis of the lifting events in the event-chain Monte Carlo for the classical XY models

Kenji Kimura, Saburo Higuchi

摘要:

我们介绍了一种新的随机游走模型,出现在事件链蒙特卡罗(ECMC)的自旋系统。在ECMC中,指定要更新的自旋的提升变量将其值更改为其相互作用的相邻自旋之一。这种运动可以被看作是在具有反馈的随机环境中的随机行走。我们在1,2和3维的经典XY模型的情况下,研究这种随机行走的数值发现,它是超扩散附近的临界点的基础自旋系统。这表明ECMC的性能改善与这种异常行为有关。

英文摘要:

We introduce a novel random walk model that emerges in the event-chain Monte Carlo (ECMC) of spin systems. In the ECMC, the lifting variable specifying the spin to be updated changes its value to one of its interacting neighbor spins. This movement can be regarded as a random walk in a random environment with a feedback. We investigate this random walk numerically in the case of the classical XY model in 1,2, and 3 dimensions to find that it is superdiffusive near the critical point of the underlying spin system. It is suggested that the performance improvement of the ECMC is related to this anomalous behavior.

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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