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arXiv · 2107.11542

Nonreversible Markov chain Monte Carlo algorithm for efficient generation of Self-Avoiding Walks

Hanqing Zhao·Marija Vucelja
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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.

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Hanqing Zhao, Marija Vucelja. 2021-07-24. Nonreversible Markov chain Monte Carlo algorithm for efficient generation of Self-Avoiding Walks. https://arxiv.org/abs/2107.11542

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