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Event-chain Monte Carlo and the true self-avoiding walk

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arxiv 2410.08694 v1 pith:GNJ375O3 submitted 2024-10-11 physics.comp-ph

A.C. Maggs This is my paper · ORCID
classification physics.comp-ph
keywords algorithmsbalancecarlomonteself-avoidingtruewalkchain
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We study the large-scale dynamics of event chain Monte Carlo algorithms in one dimension, and their relation to the true self-avoiding walk. In particular, we study the influence of stress, and different forms of interaction on the equilibration and sampling properties of algorithms with global balance, but no local balance.

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  1. Hamiltonian Monte Carlo vs. event-chain Monte Carlo: an appraisal of sampling strategies beyond the diffusive regime

    cond-mat.stat-mech 2024-11 conditional novelty 5.0 of 10

    For the 1D harmonic chain, event-chain Monte Carlo at the zero-pressure point reaches O(N^{3/2}) autocorrelation-time scaling, beating Hamiltonian Monte Carlo's O(N^{9/4}) and local Metropolis's O(N^3).

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