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February 1999 Deterministic and stochastic models for coalescence (aggregation and coagulation): a review of the mean-field theory for probabilists
David J. Aldous
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Bernoulli 5(1): 3-48 (February 1999).

Abstract

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.

Citation

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David J. Aldous. "Deterministic and stochastic models for coalescence (aggregation and coagulation): a review of the mean-field theory for probabilists." Bernoulli 5 (1) 3 - 48, February 1999.

Information

Published: February 1999
First available in Project Euclid: 12 March 2007

zbMATH: 0930.60096
MathSciNet: MR1673235

Keywords: branching process , Coalescence , continuum tree , density-dependent Markov process , gelation , random graph , Random tree , Smoluchowski coagulation equation

Rights: Copyright © 1999 Bernoulli Society for Mathematical Statistics and Probability

Vol.5 • No. 1 • February 1999
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