16,397 research outputs found

    Mixing of the symmetric exclusion processes in terms of the corresponding single-particle random walk

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    We prove an upper bound for the ε\varepsilon-mixing time of the symmetric exclusion process on any graph G, with any feasible number of particles. Our estimate is proportional to TRW(G)ln(V/ε)\mathsf{T}_{\mathsf{RW}(G)}\ln(|V|/\varepsilon), where |V| is the number of vertices in G, and TRW(G)\mathsf{T}_{\mathsf{RW}(G)} is the 1/4-mixing time of the corresponding single-particle random walk. This bound implies new results for symmetric exclusion on expanders, percolation clusters, the giant component of the Erdos-Renyi random graph and Poisson point processes in Rd\mathbb{R}^d. Our technical tools include a variant of Morris's chameleon process.Comment: Published in at http://dx.doi.org/10.1214/11-AOP714 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

    On the coalescence time of reversible random walks

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    Consider a system of coalescing random walks where each individual performs random walk over a finite graph G, or (more generally) evolves according to some reversible Markov chain generator Q. Let C be the first time at which all walkers have coalesced into a single cluster. C is closely related to the consensus time of the voter model for this G or Q. We prove that the expected value of C is at most a constant multiple of the largest hitting time of an element in the state space. This solves a problem posed by Aldous and Fill and gives sharp bounds in many examples, including all vertex-transitive graphs. We also obtain results on the expected time until only k>1 clusters remain. Our proof tools include a new exponential inequality for the meeting time of a reversible Markov chain and a deterministic trajectory, which we believe to be of independent interest.Comment: 29 pages in 11pt font with 3/2 line spacing. v2 has an extra reference and corrects a minor error in the proof of the last claim. To appear in Transactions of the AM

    Mean field conditions for coalescing random walks

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    The main results in this paper are about the full coalescence time C\mathsf{C} of a system of coalescing random walks over a finite graph GG. Letting m(G)\mathsf{m}(G) denote the mean meeting time of two such walkers, we give sufficient conditions under which E[C]2m(G)\mathbf{E}[\mathsf{C}]\approx 2\mathsf{m}(G) and C/m(G)\mathsf{C}/\mathsf{m}(G) has approximately the same law as in the "mean field" setting of a large complete graph. One of our theorems is that mean field behavior occurs over all vertex-transitive graphs whose mixing times are much smaller than m(G)\mathsf{m}(G); this nearly solves an open problem of Aldous and Fill and also generalizes results of Cox for discrete tori in d2d\geq2 dimensions. Other results apply to nonreversible walks and also generalize previous theorems of Durrett and Cooper et al. Slight extensions of these results apply to voter model consensus times, which are related to coalescing random walks via duality. Our main proof ideas are a strengthening of the usual approximation of hitting times by exponential random variables, which give results for nonstationary initial states; and a new general set of conditions under which we can prove that the hitting time of a union of sets behaves like a minimum of independent exponentials. In particular, this will show that the first meeting time among kk random walkers has mean \approx\mathsf{m}(G)/\bigl({\matrix{k 2}}\bigr).Comment: Published in at http://dx.doi.org/10.1214/12-AOP813 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org
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