A quantitative Burton-Keane estimate under strong FKG condition
Abstract
We consider translationally-invariant percolation models on satisfying the finite energy and the FKG properties. We provide explicit upper bounds on the probability of having two distinct clusters going from the endpoints of an edge to distance (this corresponds to a finite size version of the celebrated Burton-Keane [Comm. Math. Phys. 121 (1989) 501-505] argument proving uniqueness of the infinite-cluster). The proof is based on the generalization of a reverse Poincar\'{e} inequality proved in Chatterjee and Sen (2013). As a consequence, we obtain upper bounds on the probability of the so-called four-arm event for planar random-cluster models with cluster-weight .
Keywords
Cite
@article{arxiv.1409.5199,
title = {A quantitative Burton-Keane estimate under strong FKG condition},
author = {Hugo Duminil-Copin and Dmitry Ioffe and Yvan Velenik},
journal= {arXiv preprint arXiv:1409.5199},
year = {2016}
}
Comments
Published at http://dx.doi.org/10.1214/15-AOP1049 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)