On the swapping algorithm
Copyright policy )On the swapping algorithm
AbstractThe Metropolis‐coupled Markov chain method (or “Swapping Algorithm”) is an empirically successful hybrid Monte Carlo algorithm. It alternates between standard transitions on parallel versions of the system at different parameter values, and swapping two versions. We prove rapid mixing for two bimodal examples, including the mean‐field Ising model. © 2002 Wiley Periodicals, Inc. Random Struct. Alg., 22: 66–97, 2002
- Keele University United Kingdom
- York University Canada
Markov chain Monte Carlo, spectral gap, Metropolis-coupled Markov chains, Numerical methods of time-dependent statistical mechanics, Interacting random processes; statistical mechanics type models; percolation theory, Dynamic lattice systems (kinetic Ising, etc.) and systems on graphs in time-dependent statistical mechanics, mean-field Ising model decomposition
Markov chain Monte Carlo, spectral gap, Metropolis-coupled Markov chains, Numerical methods of time-dependent statistical mechanics, Interacting random processes; statistical mechanics type models; percolation theory, Dynamic lattice systems (kinetic Ising, etc.) and systems on graphs in time-dependent statistical mechanics, mean-field Ising model decomposition
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