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Citation bot (talk | contribs) Add: pmid. | Use this bot. Report bugs. | Suggested by Abductive | Category:Statistical mechanics | #UCB_Category 232/278 |
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The '''Wolff algorithm''',<ref>{{Cite journal|last=Wolff|first=Ulli|date=1989-01-23|title=Collective Monte Carlo Updating for Spin Systems|url=https://link.aps.org/doi/10.1103/PhysRevLett.62.361|journal=Physical Review Letters|volume=62|issue=4|pages=361–364|doi=10.1103/PhysRevLett.62.361|pmid=10040213}}</ref> named after [[Ulli Wolff]], is an [[algorithm]] for [[Monte Carlo simulation]] of the [[Ising model]] and [[Potts model]] in which the unit to be flipped is not a single spin (as in the [[Glauber dynamics|heat bath]] or [[Metropolis–Hastings algorithm|Metropolis algorithms]]) but a cluster of them. This cluster is defined as the set of connected spins sharing the same spin states, based on the [[Random cluster model|Fortuin-Kasteleyn representation]].
The Wolff algorithm is similar to the [[Swendsen–Wang algorithm]], but different in that the former only flips one randomly chosen cluster with probability 1, while the latter flip every cluster independently with probability 1/2. It is shown numerically that flipping only one cluster decreases the [[autocorrelation]] time of the spin statistics.
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