{ "id": "1901.08294", "version": "v1", "published": "2019-01-24T09:09:09.000Z", "updated": "2019-01-24T09:09:09.000Z", "title": "Renormalization of crossing probabilities in the planar random-cluster model", "authors": [ "Hugo Duminil-Copin", "Vincent Tassion" ], "comment": "28 pages", "categories": [ "math.PR", "math-ph", "math.MP" ], "abstract": "The study of crossing probabilities - i.e. probabilities of existence of paths crossing rectangles - has been at the heart of the theory of two-dimensional percolation since its beginning. They may be used to prove a number of results on the model, including speed of mixing, tails of decay of the connectivity probabilities, scaling relations, etc. In this article, we develop a renormalization scheme for crossing probabilities in the two-dimensional random-cluster model. The outcome of the process is a precise description of an alternative between four behaviors: - Subcritical: Crossing probabilities, even with favorable boundary conditions, converge exponentially fast to 0. - Supercritical: Crossing probabilities, even with unfavorable boundary conditions, converge exponentially fast to 1. - Critical discontinuous: Crossing probabilities converge to 0 exponentially fast with unfavorable boundary conditions and to 1 with favorable boundary conditions. - Critical continuous: Crossing probabilities remain bounded away from 0 and 1 uniformly in the boundary conditions. The approach does not rely on self-duality, enabling it to apply in a much larger generality, including the random-cluster model on arbitrary graphs with sufficient symmetry, but also other models like certain random height models.", "revisions": [ { "version": "v1", "updated": "2019-01-24T09:09:09.000Z" } ], "analyses": { "keywords": [ "crossing probabilities", "planar random-cluster model", "probabilities remain bounded away", "renormalization", "unfavorable boundary conditions" ], "note": { "typesetting": "TeX", "pages": 28, "language": "en", "license": "arXiv", "status": "editable" } } }