An exposition to information percolation for the Ising model

DOI10.5802/AFST.1462zbMATH Open1333.60207arXiv1501.00128OpenAlexW2963793591MaRDI QIDQ5963351

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Publication date: 19 February 2016

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Abstract: Information percolation is a new method for analyzing stochastic spin systems through classifying and controlling the clusters of information-flow in the space-time slab. It yielded sharp mixing estimates (cutoff with an $O(1)$-window) for the Ising model on $Z^d$ up to the critical temperature, as well as results on the effect of initial conditions on mixing. In this expository note we demonstrate the method on lattices (more generally, on any locally-finite transitive graph) at very high temperatures.

Full work available at URL: https://arxiv.org/abs/1501.00128

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