AUTHOR=Zhao Hanqing , Vucelja Marija 

TITLE=Nonreversible Markov Chain Monte Carlo Algorithm for Efficient Generation of Self-Avoiding Walks

JOURNAL=Frontiers in Physics

VOLUME=9

YEAR=2022

URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2021.782156

DOI=10.3389/fphy.2021.782156

ISSN=2296-424X

ABSTRACT=<p>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 <italic>two-move nonreversible Berretti-Sokal algorithm</italic> introduced by H. Hu, X. Chen, and Y. Deng, while for three-dimensional walks, it is 3–5 times faster. The new algorithm introduces nonreversible Markov chains that obey global balance and allow for three types of elementary moves on the existing self-avoiding walk: shorten, extend or alter conformation without changing the length of the walk.</p>