Nonlocal Monte Carlo algorithm for self-avoiding walks with fixed endpoints

Sergio Caracciolo, Andrea Pelissetto, Alan D. Sokal

    Research output: Contribution to journalArticlepeer-review

    Abstract

    We study a new Monte Carlo algorithm for generating self-avoiding walks with variable length (controlled by a fugacity β) and fixed endpoints. The algorithm is a hybrid of local (BFACF) and nonlocal (cut-and-paste) moves. We find that the critical slowing-down, measured in units of computer time, is reduced compared to the pure BFACF algorithm:τCPU∼ 〈N〉≈2.3 versus 〈N〉≈3.0. We also prove some rigorous bounds on the autocorrelation time for these and related Monte Carlo algorithms.

    Original languageEnglish (US)
    Pages (from-to)1-53
    Number of pages53
    JournalJournal of Statistical Physics
    Volume60
    Issue number1-2
    DOIs
    StatePublished - Jul 1990

    Keywords

    • BFACF algorithm
    • Monte Carlo
    • Self-avoiding walk
    • critical exponent
    • cut-and-paste
    • pivot algorithm
    • polymer

    ASJC Scopus subject areas

    • Statistical and Nonlinear Physics
    • Mathematical Physics

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