Quantitative stochastic homogenization and large-scale regularity
Abstract
This is a preliminary version of a book which presents the quantitative homogenization and large-scale regularity theory for elliptic equations in divergence-form. The self-contained presentation gives new and simplified proofs of the core results proved in the last several years, including the algebraic convergence rate for the variational subadditive quantities, the large-scale Lipschitz and higher regularity estimates and Liouville-type results, optimal quantitative estimates on the first-order correctors and their scaling limit to a Gaussian free field. There are several chapters containing new results, such as: quantitative estimates for the Dirichlet problem, including optimal quantitative estimates of the homogenization error and the two-scale expansion; optimal estimates for the homogenization of the parabolic and elliptic Green functions; and -type estimates for two-scale expansions.
Cite
@article{arxiv.1705.05300,
title = {Quantitative stochastic homogenization and large-scale regularity},
author = {Scott Armstrong and Tuomo Kuusi and Jean-Christophe Mourrat},
journal= {arXiv preprint arXiv:1705.05300},
year = {2019}
}
Comments
504 pages, 14 figures