2009/06/04 by Vinay Ambegaokar, Matthias Troyer · 63 citations
Mathematics · Physics and Astronomy · #Algorithm #Applied mathematics #Computer science #Dynamic Monte Carlo method #Hybrid Monte Carlo #Markov Chains and Monte Carlo Methods #Markov chain Monte Carlo #Mathematics #Monte Carlo integration #Monte Carlo method #Monte Carlo method in statistical physics #Monte Carlo molecular modeling #Optics #Physics #Quantum many-body systems #Sampling (signal processing) #Statistical physics #Statistics #Theoretical and Computational Physics #cond-mat.stat-mech #hep-lat #physics.comp-ph #physics.data-an
paper · pdf · doi:10.1119/1.3247985
published in American Journal of Physics 78(2), 150-157 (American Institute of Physics)
arxiv created 2009/06/04 · openalex publication_date 2010/01/12 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
We use the Ehrenfest urn model to illustrate the subtleties of error estimation in Monte Carlo simulations. We discuss how the smooth results of correlated sampling in Markov chains can fool one’s perception of the accuracy of the data and show via numerical and analytical methods how to obtain reliable error estimates from correlated samples.