Analyzing Glauber dynamics by comparison of Markov chains
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Publication:2737887
DOI10.1063/1.533199zbMath0974.60052OpenAlexW2000597435MaRDI QIDQ2737887
Publication date: 30 August 2001
Published in: Journal of Mathematical Physics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1063/1.533199
Markov chain Monte Carlo algorithmrandom triangulationsplanar tilingsestimating mixing rates of Markov chainssingle-point update algorithms
Combinatorics in computer science (68R05) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics (82C31)
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Cites Work
- Geometric bounds for eigenvalues of Markov chains
- Approximate counting, uniform generation and rapidly mixing Markov chains
- The basic contact processes
- Comparison theorems for reversible Markov chains
- Comparison techniques for random walk on finite groups
- Approximating the number of monomer-dimer coverings of a lattice.
- Logarithmic Sobolev inequalities for finite Markov chains
- Random sampling for the monomer–dimer model on a lattice
- Polynomial-Time Approximation Algorithms for the Ising Model
- Conway's Tiling Groups
- Approximating the Permanent
- Generating a random permutation with random transpositions
- Fast convergence of the Glauber dynamics for sampling independent sets
- A very simple algorithm for estimating the number of k‐colorings of a low‐degree graph
