English

Coagulation processes with Gibbsian time evolution

Probability 2012-04-17 v2

Abstract

We prove that time dynamics of a stochastic process of pure coagulation is given by a time dependent Gibbs distribution if and only if rates of single coagulations have the form ψ(i,j)=if(j)+jf(i)\psi(i,j)=if(j)+jf(i), where ff is an arbitrary nonnegative function on the set of integers 1\ge 1. We also obtained a recurrence relation for weights of these Gibbs distributions, that allowed explicit solutions in three particular cases of the function ff. For the three corresponding models, we study the probability of coagulation into one giant cluster, at time t>0.t>0.

Keywords

Cite

@article{arxiv.1008.1027,
  title  = {Coagulation processes with Gibbsian time evolution},
  author = {Boris Granovsky and Alexander Kryvoshaev},
  journal= {arXiv preprint arXiv:1008.1027},
  year   = {2012}
}

Comments

22 pages. Changes made implementing referee's suggestions and remarks.This is a final version to be published in the Advances of Applied probability

R2 v1 2026-06-21T15:57:32.147Z