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Monte Carlo Transition Dynamics and Variance Reduction

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Abstract

For Metropolis Monte Carlo simulations in statistical physics, efficient, easy- to-implement, and unbiased statistical estimators of thermodynamic properties are based on the transition dynamics. Using an Ising model example, we demonstrate (problem-specific) variance reductions compared to conventional histogram estimators. A proof of variance reduction in a microstate limit is presented.

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Authors and Affiliations

  1. Los Alamos National Laboratory, Los Alamos, New Mexico, 87545

    M. Fitzgerald

  2. Los Alamos National Laboratory, Los Alamos, New Mexico, 87545

    R. R. Picard

  3. Los Alamos National Laboratory, Los Alamos, New Mexico, 87545

    R. N. Silver

Authors
  1. M. Fitzgerald
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  2. R. R. Picard
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  3. R. N. Silver
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Fitzgerald, M., Picard, R.R. & Silver, R.N. Monte Carlo Transition Dynamics and Variance Reduction. Journal of Statistical Physics 98, 321–345 (2000). https://doi.org/10.1023/A:1018635108073

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