Deterministic and stochastic models for coalescence (aggregation and coagulation): a review of the mean-field theory for probabilists
Aldous, David J.
Bernoulli, Tome 5 (1999) no. 6, p. 3-48 / Harvested from Project Euclid
Consider N particles, which merge into clusters according to the following rule: a cluster of size x and a cluster of size y merge at stochastic rate K(x,y)/N, where K is a specified rate kernel. This Marcus-Lushnikov model of stochastic coalescence and the underlying deterministic approximation given by the Smoluchowski coagulation equations have an extensive scientific literature. Some mathematical literature (Kingman's coalescent in population genetics; component sizes in random graphs) implicitly studies the special cases K(x,y)=1 and K(x,y)=xy. We attempt a wide-ranging survey. General kernels are only now starting to be studied rigorously; so many interesting open problems appear.
Publié le : 1999-02-14
Classification:  branching process,  coalescence,  continuum tree,  density-dependent Markov process,  gelation,  random graph,  random tree,  Smoluchowski coagulation equation
@article{1173707093,
     author = {Aldous, David J.},
     title = {Deterministic and stochastic models for coalescence (aggregation and coagulation): a review of the mean-field theory for probabilists},
     journal = {Bernoulli},
     volume = {5},
     number = {6},
     year = {1999},
     pages = { 3-48},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1173707093}
}
Aldous, David J. Deterministic and stochastic models for coalescence (aggregation and coagulation): a review of the mean-field theory for probabilists. Bernoulli, Tome 5 (1999) no. 6, pp.  3-48. http://gdmltest.u-ga.fr/item/1173707093/