Monte Carlo without chains

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Abstract

A sampling method for spin systems is presented. The spin lattice is written as the union of a nested sequence of sublattices, all but the last with conditionally independent spins, which are sampled in succession using their marginals. The marginals are computed concurrently by a fast algorithm; errors in the evaluation of the marginals are offset by weights. There are no Markov chains and each sample is independent of the previous ones; the cost of a sample is proportional to the number of spins (but the number of samples needed for good statistics may grow with array size). The examples include the Edwards-Anderson spin glass in three dimensions.

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APA

Chorin, A. J. (2008). Monte Carlo without chains. Communications in Applied Mathematics and Computational Science, 3(1), 77–93. https://doi.org/10.2140/camcos.2008.3.77

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