Hybrid Multicanonical Cluster Algorithm for Efficient Simulations of Long-Range Spin Models

Abstract : An efficient, flat histogram Monte Carlo algorithm is proposed that simulates long-range spin models in the multicanonical ensemble with very low dynamic exponents and drastically reduced computational effort. The method combines a random-walk in energy space with cluster updates, where bond weights depend continuously on the lattice energy. Application to $q$-state Potts chains with power-law decaying interactions is considered. Lattice sizes as high as $2^{16}$ spins, unattainable with conventional flat histogram algorithms, are investigated. Numerical results demonstrate the remarkable performance of the method over a wide spectrum of model parameters.
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Computer Physics Communications, Elsevier, 2005, 169, pp.243. <10.1016/j.cpc.2005.03.056>
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Contributeur : Sylvain Reynal <>
Soumis le : jeudi 6 octobre 2005 - 22:28:50
Dernière modification le : mardi 17 janvier 2017 - 15:35:54
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Sylvain Reynal, Hung-The Diep. Hybrid Multicanonical Cluster Algorithm for Efficient Simulations of Long-Range Spin Models. Computer Physics Communications, Elsevier, 2005, 169, pp.243. <10.1016/j.cpc.2005.03.056>. <hal-00009617>

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