Open Access
February 2021 Optimal corrector estimates on percolation cluster
Paul Dario
Author Affiliations +
Ann. Appl. Probab. 31(1): 377-431 (February 2021). DOI: 10.1214/20-AAP1593

Abstract

We prove optimal quantitative estimates on the first-order correctors on supercritical percolation clusters: we show that they are bounded in dimension larger than 3 and have logarithmic growth in dimension 2 in the sense of stretched exponential moments. The main ingredients are a renormalization scheme of the supercritical percolation cluster, following the works of Pisztora (Probab. Theory Related Fields 104 (1996) 427–466); large-scale regularity estimates developed by Armstrong and the author in (Comm. Pure Appl. Math. 71 (2018) 1717–1849); and a nonlinear concentration inequality of the Efron–Stein type which is used to transfer quantitative information from the environment to the correctors.

Citation

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Paul Dario. "Optimal corrector estimates on percolation cluster." Ann. Appl. Probab. 31 (1) 377 - 431, February 2021. https://doi.org/10.1214/20-AAP1593

Information

Received: 1 April 2019; Revised: 1 February 2020; Published: February 2021
First available in Project Euclid: 8 March 2021

Digital Object Identifier: 10.1214/20-AAP1593

Subjects:
Primary: 35B27 , 60K35 , 60K37

Keywords: Stochastic homogenization , Supercritical percolation

Rights: Copyright © 2021 Institute of Mathematical Statistics

Vol.31 • No. 1 • February 2021
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