Fortuin–Kasteleyn random cluster model

E906308

The Fortuin–Kasteleyn random cluster model is a unifying probabilistic framework in statistical mechanics that represents spin systems and percolation models, notably providing a graphical reformulation of the Potts model.

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Predicate Object
instanceOf lattice model in statistical mechanics
percolation-type model
probabilistic model
alsoKnownAs FK random cluster model NERFINISHED
random cluster model
associatedWith FKG inequality NERFINISHED
basedOn configurations of open and closed edges on a graph
connectedTo Gibbs measures NERFINISHED
graph theory
percolation clusters
definedOn finite graphs
lattices such as Z^d
field mathematical physics
probability theory
statistical mechanics
frameworkFor unified treatment of spin and percolation models
generalizes Bernoulli bond percolation
hasApplication Monte Carlo algorithms for Potts and Ising models
hasContinuumLimitRelatedTo Schramm–Loewner evolution in two dimensions GENERATED
hasParameter cluster weight q
edge occupation probability p
hasProperty positively associated for q ≥ 1
hasVariant free boundary conditions
wired boundary conditions
importantFor conformal invariance studies in 2D
inspired cluster algorithms such as Swendsen–Wang
introducedInContextOf graphical representations of spin systems
namedAfter Cornelis M. Fortuin NERFINISHED
Pieter W. Kasteleyn NERFINISHED
probabilityWeightProportionalTo (1-p)^{number of closed edges}
p^{number of open edges}
q^{number of connected components}
provides graphical reformulation of the Potts model
reducesTo Bernoulli bond percolation when q = 1
relatedTo Ising model as the q = 2 case
q-state Potts model NERFINISHED
studiedFor correlation inequalities
critical phenomena
phase transitions
unifies Ising model NERFINISHED
Potts model NERFINISHED
percolation theory
usedIn rigorous study of Potts model phase diagram
study of percolation of FK clusters
usedToConstruct random-cluster measures on infinite graphs
uses cluster representation of spin systems

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Potts model relatedTo Fortuin–Kasteleyn random cluster model