An informal introduction to quantitative stochastic homogenization
arXiv:1901.05035 · doi:10.1063/1.5089210
Abstract
Divergence-form operators with random coefficients homogenize over large scales. Over the last decade, an intensive research effort focused on turning this asymptotic statement into quantitative estimates. The goal of this note is to review one approach for doing so based on the idea of renormalization. The discussion is highly informal, with pointers to mathematically precise statements.
18 pages, 9 figures, proceedings of ICMP 2018
References in corpus (5)
- An optimal error estimate in stochastic homogenization of discrete elliptic equations
- An optimal variance estimate in stochastic homogenization of discrete elliptic equations
- Quantitative results on the corrector equation in stochastic homogenization
- Elliptic regularity and quantitative homogenization on percolation clusters
- Quantitative stochastic homogenization of convex integral functionals