Rapid mixing of Swendsen–Wang dynamics in two dimensions
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Publication:5496948
DOI10.4064/dm502-0-1zbMath1315.60113arXiv1212.4908OpenAlexW3098007057MaRDI QIDQ5496948
Publication date: 29 January 2015
Published in: Dissertationes Mathematicae (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1212.4908
Markov chain Monte Carlo methodspectral gapIsing modelPotts modelrandom cluster modelrapid mixingSwendsen-Wang dynamics
Monte Carlo methods (65C05) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Dynamic lattice systems (kinetic Ising, etc.) and systems on graphs in time-dependent statistical mechanics (82C20)
Related Items (19)
Random-cluster dynamics in \(\mathbb {Z}^2\) ⋮ Entropy decay in the Swendsen-Wang dynamics on \(\mathbb{Z}^d\) ⋮ Random cluster dynamics for the Ising model is rapidly mixing ⋮ Mixing of the Glauber dynamics for the ferromagnetic Potts model ⋮ The effect of boundary conditions on mixing of 2D Potts models at discontinuous phase transitions ⋮ Algorithmic Pirogov-Sinai theory ⋮ The Swendsen–Wang dynamics on trees ⋮ Unnamed Item ⋮ Unnamed Item ⋮ Comparison of hit-and-run, slice sampler and random walk Metropolis ⋮ Swendsen‐Wang algorithm on the mean‐field Potts model ⋮ Structure and eigenvalues of heat-bath Markov chains ⋮ The worm process for the Ising model is rapidly mixing ⋮ Quantitative spectral gap estimate and Wasserstein contraction of simple slice sampling ⋮ Random-cluster dynamics on random regular graphs in tree uniqueness ⋮ Rapid Mixing and Markov Bases ⋮ Ferromagnetic Potts Model: Refined #BIS-hardness and Related Results ⋮ On mixing of Markov chains: coupling, spectral independence, and entropy factorization ⋮ The hit-and-run version of top-to-random
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