Cluster Monte Carlo and dynamical scaling for long-range interactions

Emilio Flores-Sola, Martin Weigel, Ralph Kenna, Bertrand Berche

    Research output: Contribution to journalArticlepeer-review

    11 Citations (Scopus)
    35 Downloads (Pure)

    Abstract

    Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each update from O($N^2$) to O($N\ln N$) or even O($N$), thus promising an even more dramatic computational speed-up. Here, we review the available algorithms and propose a new and particularly efficient single-cluster variant. The efficiency and dynamical scaling of the available algorithms are investigated for the Ising model with power-law decaying interactions.
    Original languageEnglish
    Pages (from-to)581 - 594
    Number of pages14
    JournalThe European Physical Journal Special Topics
    Volume226
    Issue number4
    DOIs
    Publication statusPublished - 5 Apr 2017

    Keywords

    • cond-mat.stat-mech
    • hep-lat
    • physics.comp-ph

    Fingerprint

    Dive into the research topics of 'Cluster Monte Carlo and dynamical scaling for long-range interactions'. Together they form a unique fingerprint.

    Cite this