Singular relaxation of a random walk in a box with a Metropolis Monte Carlo dynamics

DOI10.1088/1751-8121/acd829arXiv2303.08535OpenAlexW4377694344MaRDI QIDQ6162532

Satya N. Majumdar, Alexei D. Chepelianskii, Emmanuel Trizac, Hendrik Schawe

Publication date: 15 June 2023

Published in: Journal of Physics A: Mathematical and Theoretical (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2303.08535

zbMATH Keywords

Monte CarloMetropolis algorithmrelaxation of Markov chains

Mathematics Subject Classification ID

Quantum theory (81-XX) Statistical mechanics, structure of matter (82-XX)

Cites Work

• Gibbs/Metropolis algorithms on a convex polytope
• Geometric analysis for the Metropolis algorithm on Lipschitz domains
• Escape of a uniform random walk from an interval
• General state space Markov chains and MCMC algorithms
• Micro-local analysis for the Metropolis algorithm
• Weak convergence and optimal scaling of random walk Metropolis algorithms
• Optimal scaling for the transient phase of the random walk Metropolis algorithm: the mean-field limit
• A brief review of optimal scaling of the main MCMC approaches and optimal scaling of additive TMCMC under non-regular cases
• Optimum Monte-Carlo sampling using Markov chains
• The Markov chain Monte Carlo revolution
• Optimum Monte Carlo simulations: some exact results
• Numerical Results for the Metropolis Algorithm
• A Guide to Monte Carlo Simulations in Statistical Physics
• Quantum Monte Carlo Approaches for Correlated Systems
• The Monte Carlo Method
• One-dimensional Monte Carlo dynamics at zero temperature
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