Dynamic critical exponent of the BFACF algorithm for self-avoiding walks

Sergio Caracciolo; Andrea Pelissetto; Alan D. Sokal

doi:10.1007/BF01029987

Dynamic critical exponent of the BFACF algorithm for self-avoiding walks

Sergio Caracciolo, Andrea Pelissetto, Alan D. Sokal

Research output: Contribution to journal › Article › peer-review

Abstract

We study the dynamic critical behavior of the BFACF algorithm for generating self-avoiding walks with variable length and fixed endpoints. We argue theoretically, and confirm by Monte Carlo simulations in dimensions 2, 3, and 4, that the autocorrelation time scales as τ_{int, N}R~ξ⁴R~〈N> ^{4 v}.

Original language	English (US)
Pages (from-to)	857-865
Number of pages	9
Journal	Journal of Statistical Physics
Volume	63
Issue number	5-6
DOIs	https://doi.org/10.1007/BF01029987
State	Published - Jun 1991

Keywords

BFACF algorithm
Monte Carlo
Self-avoiding walk
dynamic critical exponent
polymer

ASJC Scopus subject areas

Statistical and Nonlinear Physics
Mathematical Physics

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10.1007/BF01029987

Cite this

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title = "Dynamic critical exponent of the BFACF algorithm for self-avoiding walks",

abstract = "We study the dynamic critical behavior of the BFACF algorithm for generating self-avoiding walks with variable length and fixed endpoints. We argue theoretically, and confirm by Monte Carlo simulations in dimensions 2, 3, and 4, that the autocorrelation time scales as τint, NR~ξ4R~〈N> 4 v.",

keywords = "BFACF algorithm, Monte Carlo, Self-avoiding walk, dynamic critical exponent, polymer",

author = "Sergio Caracciolo and Andrea Pelissetto and Sokal, {Alan D.}",

year = "1991",

month = jun,

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AU - Caracciolo, Sergio

AU - Pelissetto, Andrea

AU - Sokal, Alan D.

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N2 - We study the dynamic critical behavior of the BFACF algorithm for generating self-avoiding walks with variable length and fixed endpoints. We argue theoretically, and confirm by Monte Carlo simulations in dimensions 2, 3, and 4, that the autocorrelation time scales as τint, NR~ξ4R~〈N> 4 v.

AB - We study the dynamic critical behavior of the BFACF algorithm for generating self-avoiding walks with variable length and fixed endpoints. We argue theoretically, and confirm by Monte Carlo simulations in dimensions 2, 3, and 4, that the autocorrelation time scales as τint, NR~ξ4R~〈N> 4 v.

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KW - Monte Carlo

KW - Self-avoiding walk

KW - dynamic critical exponent

KW - polymer

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ER -

Dynamic critical exponent of the BFACF algorithm for self-avoiding walks

Abstract

Keywords

ASJC Scopus subject areas

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