Efficient simulation of the random-cluster model

E.M. Elçi, Martin Weigel

    Research output: Contribution to journalArticle

    10 Citations (Scopus)
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    Abstract

    The simulation of spin models close to critical points of continuous phase transitions is heavily impeded by the occurrence of critical slowing down. A number of cluster algorithms, usually based on the Fortuin-Kasteleyn representation of the Potts model, and suitable generalizations for continuous-spin models have been used to increase simulation efficiency. The first algorithm making use of this representation, suggested by Sweeny in 1983, has not found widespread adoption due to problems in its implementation. However, it has been recently shown that it is indeed more efficient in reducing critical slowing down than the more well-known algorithm due to Swendsen and Wang. Here, we present an efficient implementation of Sweeny's approach for the random-cluster model using recent algorithmic advances in dynamic connectivity algorithms.
    Original languageEnglish
    Article number33303
    JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
    Volume88
    Issue number3
    DOIs
    Publication statusPublished - 2013

    Fingerprint

    Random-cluster Model
    Critical Slowing down
    Spin Models
    Cluster Algorithm
    Simulation
    simulation
    Potts Model
    Number of Clusters
    Efficient Implementation
    Critical point
    Connectivity
    Phase Transition
    critical point
    occurrences

    Bibliographical note

    © 2013 American Physical Society

    Keywords

    • spin models
    • continuous-spin models
    • random-cluster model

    Cite this

    Efficient simulation of the random-cluster model. / Elçi, E.M.; Weigel, Martin.

    In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 88, No. 3, 33303, 2013.

    Research output: Contribution to journalArticle

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