We establish an optimal, linear rate of convergence for the stochastic homogenization of discrete linear elliptic equations. We consider the model problem of independent and identically distributed coefficients on a discretized unit torus. We show that the difference between the solution to the random problem on the discretized torus and the first two terms of the two-scale asymptotic expansion has the same scaling as in the periodic case. In particular the L2-norm in probability of the H1-norm in space of this error scales like ε, where ε is the discretization parameter of the unit torus. The proof makes extensive use of previous results by the authors, and of recent annealed estimates on the Green's function by Marahrens and the third aut...
Cette thèse est consacrée à l’homogénéisation stochastique, qui cherche à étudier le comportement d’...
optimal error estimate in stochastic homogenization of discrete elliptic equation
This article is concerned with numerical methods to approximate effective coefficients in stochastic...
We establish an optimal, linear rate of convergence for the stochastic homogenization of discrete li...
An optimal quantitative two-scale expansion in stochastic homogenization of discrete elliptic equati...
International audienceWe establish a rate of convergence of the two scale expansion (in the sense of...
We introduce and analyze a numerical strategy to approximate effective coefficients in stochastic ho...
We introduce and analyze a numerical strategy to approximate effective coefficients in stochastic h...
Abstract. We consider a discrete elliptic equation on the d-dimensional lattice Zd with random coeff...
We derive optimal estimates in stochastic homogenization of linear elliptic equations in divergence ...
We are concerned with the homogenization of second-order linear elliptic equations with random coeff...
International audienceWe investigate the global fluctuations of solutions to elliptic equations with...
301 pages, 12 figuresThis is a preliminary version of a book which presents the quantitative homogen...
We establish quantitative results on the periodic approximation of the corrector equation ...
International audienceWe study quantitatively the effective large-scale behavior of discrete ellipti...
Cette thèse est consacrée à l’homogénéisation stochastique, qui cherche à étudier le comportement d’...
optimal error estimate in stochastic homogenization of discrete elliptic equation
This article is concerned with numerical methods to approximate effective coefficients in stochastic...
We establish an optimal, linear rate of convergence for the stochastic homogenization of discrete li...
An optimal quantitative two-scale expansion in stochastic homogenization of discrete elliptic equati...
International audienceWe establish a rate of convergence of the two scale expansion (in the sense of...
We introduce and analyze a numerical strategy to approximate effective coefficients in stochastic ho...
We introduce and analyze a numerical strategy to approximate effective coefficients in stochastic h...
Abstract. We consider a discrete elliptic equation on the d-dimensional lattice Zd with random coeff...
We derive optimal estimates in stochastic homogenization of linear elliptic equations in divergence ...
We are concerned with the homogenization of second-order linear elliptic equations with random coeff...
International audienceWe investigate the global fluctuations of solutions to elliptic equations with...
301 pages, 12 figuresThis is a preliminary version of a book which presents the quantitative homogen...
We establish quantitative results on the periodic approximation of the corrector equation ...
International audienceWe study quantitatively the effective large-scale behavior of discrete ellipti...
Cette thèse est consacrée à l’homogénéisation stochastique, qui cherche à étudier le comportement d’...
optimal error estimate in stochastic homogenization of discrete elliptic equation
This article is concerned with numerical methods to approximate effective coefficients in stochastic...