English

Optimal corrector estimates on percolation clusters

Probability 2020-05-15 v2 Analysis of PDEs

Abstract

We prove optimal quantitative estimates on the first-order correctors on supercritical percolation clusters: we show that they are bounded in d3d\geq 3 and have logarithmic growth in d=2d = 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 and Barlow; large-scale regularity estimates developed in the previous paper; and a nonlinear concentration inequality of Efron-Stein type which is used to transfer quantitative information from the environment to the correctors.

Keywords

Cite

@article{arxiv.1805.00902,
  title  = {Optimal corrector estimates on percolation clusters},
  author = {Paul Dario},
  journal= {arXiv preprint arXiv:1805.00902},
  year   = {2020}
}

Comments

51 pages; revised version, accepted for publication in Annals of Applied Probability

R2 v1 2026-06-23T01:43:03.428Z