Current browse context:
cond-mat
Change to browse by:
References & Citations
Condensed Matter > Statistical Mechanics
Title: Nonreversible Markov chain Monte Carlo algorithm for efficient generation of Self-Avoiding Walks
(Submitted on 24 Jul 2021 (v1), last revised 10 Dec 2021 (this version, v2))
Abstract: We introduce an efficient nonreversible Markov chain Monte Carlo algorithm to generate self-avoiding walks with a variable endpoint. In two dimensions, the new algorithm slightly outperforms the two-move nonreversible Berretti-Sokal algorithm introduced by H.~Hu, X.~Chen, and Y.~Deng in \cite{old}, while for three-dimensional walks, it is 3--5 times faster. The new algorithm introduces nonreversible Markov chains that obey global balance and allows for three types of elementary moves on the existing self-avoiding walk: shorten, extend or alter conformation without changing the walk's length.
Submission history
From: Marija Vucelja [view email][v1] Sat, 24 Jul 2021 06:16:14 GMT (85kb,D)
[v2] Fri, 10 Dec 2021 02:01:31 GMT (2177kb,D)
Link back to: arXiv, form interface, contact.