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{{Notability|date=March 2009}}
The '''Swendsen–Wang algorithm''' is an [[algorithm]] for [[Monte Carlo simulation]] of the [[Ising model]] in which the entire sample is divided into equal-spin clusters. Each cluster is then assigned a new random spin value. Compare the [[Wolff algorithm]].
It has been generalized by Barbu and Zhu (2005) to sampling arbitrary probabilities by viewing it as a [[Metropolis–Hastings algorithm]] and computing the acceptance probability of the proposed Monte Carlo move.
==References==
*Swendsen, R. H., and Wang, J. ''Nonuniversal critical dynamics in Monte Carlo simulations'', Phys. Rev. Lett., 58(2):86–88, 1987.
*Barbu, A., Zhu, S. C. ''Generalizing Swendsen-Wang to sampling arbitrary posterior probabilities'', IEEE Trans Patt. Anal. Mach. Intell., 27(8):1239-1253, 2005.
==External links==
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