A random-cluster model on a finite graph is a measure on the measurable
space
defined as follows. Let , whose members are vectors , and let be the sigma-algebra
of all subsets of . For each , set
(1)
where here,
and
are parameters , is the so-called partition function
(2)
and
denotes the number of connected components
of the graph
where
(3)
The connected components of are called open clusters.
For a positive integer and , the substitution identifies , up to the factor , with the -state Potts model partition
function.
In the above setting, the case corresponds to a model in which graph
edges are open (i.e., ) or closed (i.e., ) independently
of one another, a scenario which can be used as an alternative definition for the
term percolation . For cases , the random-cluster model models dependent
percolation .
See also AB Percolation,
Bernoulli Percolation Model ,
Bond Percolation ,
Boolean
Model ,
Boolean-Poisson Model ,
Bootstrap
Percolation ,
Cayley Tree ,
Cluster ,
Cluster Perimeter ,
Continuum
Percolation Theory ,
Dependent Percolation ,
Discrete Percolation Theory ,
Disk
Model ,
First-Passage Percolation ,
Germ-Grain Model ,
Inhomogeneous
Percolation Model ,
Lattice Animal ,
Long-Range
Percolation Model ,
Mixed Percolation Model ,
Oriented Percolation Model ,
Percolation ,
Percolation Theory ,
Percolation
Threshold ,
Polyomino ,
Potts
Model ,
Random-Connection Model ,
Random Walk ,
s -Cluster,
s -Run,
Site Percolation
This entry contributed by Christopher
Stover
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References Grimmett, G. R. The Random-Cluster Model. Berlin: Springer-Verlag, 2009. Referenced
on Wolfram|Alpha Random-Cluster Model
Cite this as:
Weisstein, Eric W. , with contributions by Christopher Stover . "Random-Cluster Model." From MathWorld --A
Wolfram Resource. https://mathworld.wolfram.com/Random-ClusterModel.html
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