Estimating errors reliably in Monte Carlo simulations of the Ehrenfest model

Abstract

Using the Ehrenfest urn model we 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.

References in corpus (1)

• The ALPS project release 1.3: open source software for strongly correlated systems

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