期刊
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
卷 53, 期 26, 页码 -出版社
IOP PUBLISHING LTD
DOI: 10.1088/1751-8121/ab8ff7
关键词
PERM and flatPERM algorithm; parallel computing; Rosenbluth method; self-avoiding walk
资金
- NSERC (Canada) [RGPIN-2019-06303, PGSD3-535625-2019]
We develop and implement a parallel flatPERM algorithm (Grassberger 1997Phys. Rev. E563682-3693, Prellberg and Krawczyk 2004Phys. Rev. Lett.92120602) with mutually interacting parallel flatPERM sequences and use it to sample self-avoiding walks in two and three dimensions. Our data show that the parallel implementation accelerates the convergence of the flatPERM algorithm. Moreover, increasing the number of interacting flatPERM sequences (rather than running longer simulations) improves the rate of convergence. This suggests that a more efficient implementation of flatPERM will be a massively parallel implementation, rather than long simulations of one, or a few parallel sequences. We also use the algorithm to estimate the growth constant of the self-avoiding walk in two and in three dimensions using simulations over 12 parallel sequences. Our best results are mu(d) = {2.6381585(1), if d = 2; 4.684039(1), if d = 3.
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