Qin Hoellmer Krauth 2020

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L. Qin, P. Hoellmer, W. Krauth Fast sequential Markov chains arXiv:2007.15615 (2020)

Abstract We discuss non-reversible Markov chains that generalize the sweeps commonly used in particle systems and spin models towards a sequential choice from a set of directions of motion. For a simplified dipole model, we show that direction sweeps leave the stationary probability distribution unchanged, but profoundly modify the trajectory of the Markov chain. Choosing a larger direction set can lead to much shorter mixing times. The sequential order is faster than the random sampling from the set. We discuss possible applications of sequential Monte Carlo in polymer physics and molecular simulation.

Electronic version (from arXiv)

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