Parallelization of Markov chain generation and its application to the multicanonical method

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Sugihara, Takanori
Higo, Junichi
Nakamura, Haruki
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Abstract
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We develop a simple algorithm to parallelize generation processes of Markov chains. In this algorithm, multiple Markov chains are generated in parallel and jointed together to make a longer Markov chain. The joints between the constituent Markov chains are processed using the detailed balance. We apply the parallelization algorithm to multicanonical calculations of the two-dimensional Ising model and demonstrate accurate estimation of multicanonical weights.
Comment: 15 pages, 5 figures, uses elsart.cls
Keywords
Condensed Matter - Statistical Mechanics, High Energy Physics - Lattice, Physics - Biological Physics, Physics - Computational Physics
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