English

Escape of mass in zero-range processes with random rates

Probability 2007-09-12 v2 Mathematical Physics math.MP

Abstract

We consider zero-range processes in Zd{\mathbb{Z}}^d with site dependent jump rates. The rate for a particle jump from site xx to yy in Zd{\mathbb{Z}}^d is given by λxg(k)p(yx)\lambda_xg(k)p(y-x), where p()p(\cdot) is a probability in Zd{\mathbb{Z}}^d, g(k)g(k) is a bounded nondecreasing function of the number kk of particles in xx and λ={λx}\lambda =\{\lambda_x\} is a collection of i.i.d. random variables with values in (c,1](c,1], for some c>0c>0. For almost every realization of the environment λ\lambda the zero-range process has product invariant measures {νλ,v:0vc}\{{\nu_{\lambda, v}}:0\le v\le c\} parametrized by vv, the average total jump rate from any given site. The density of a measure, defined by the asymptotic average number of particles per site, is an increasing function of vv. There exists a product invariant measure νλ,c{\nu _{\lambda, c}}, with maximal density. Let μ\mu be a probability measure concentrating mass on configurations whose number of particles at site xx grows less than exponentially with x\|x\|. Denoting by Sλ(t)S_{\lambda}(t) the semigroup of the process, we prove that all weak limits of {μSλ(t),t0}\{\mu S_{\lambda}(t),t\ge 0\} as tt\to \infty are dominated, in the natural partial order, by νλ,c{\nu_{\lambda, c}}. In particular, if μ\mu dominates νλ,c{\nu _{\lambda, c}}, then μSλ(t)\mu S_{\lambda}(t) converges to νλ,c{\nu_{\lambda, c}}. The result is particularly striking when the maximal density is finite and the initial measure has a density above the maximal.

Keywords

Cite

@article{arxiv.math/0609469,
  title  = {Escape of mass in zero-range processes with random rates},
  author = {Pablo A. Ferrari and Valentin V. Sisko},
  journal= {arXiv preprint arXiv:math/0609469},
  year   = {2007}
}

Comments

Published at http://dx.doi.org/10.1214/074921707000000300 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)

R2 v1 2026-07-22T17:42:34.343Z