ARC Centre of Excellence for Mathematics and Statistics of Complex Systems, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010, Australia.
Phys Rev Lett. 2010 Feb 5;104(5):055702. doi: 10.1103/PhysRevLett.104.055702. Epub 2010 Feb 1.
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.
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。