Suppr超能文献

通过快速实现枢轴算法准确估计自回避行走的临界指数 nu。

Accurate estimate of the critical exponent nu for self-avoiding walks via a fast implementation of the pivot algorithm.

机构信息

ARC Centre of Excellence for Mathematics and Statistics of Complex Systems, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010, Australia.

出版信息

Phys Rev Lett. 2010 Feb 5;104(5):055702. doi: 10.1103/PhysRevLett.104.055702. Epub 2010 Feb 1.

Abstract

We introduce a fast implementation of the pivot algorithm for self-avoiding walks, which we use to obtain large samples of walks on the cubic lattice of up to 33x10{6} steps. Consequently the critical exponent nu for three-dimensional self-avoiding walks is determined to great accuracy; the final estimate is nu=0.587 597(7). The method can be adapted to other models of polymers with short-range interactions, on the lattice or in the continuum.

摘要

我们引入了一种快速实现自回避行走枢轴算法的方法,该方法可用于获得多达 33x10{6}步的立方晶格上的行走的大样本。因此,可以非常准确地确定三维自回避行走的临界指数 nu;最终的估计值为 nu=0.587 597(7)。该方法可以适用于具有短程相互作用的其他聚合物模型,无论是在晶格上还是在连续体中。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验