An optimal quantitative two-scale expansion in stochastic homogenization of discrete elliptic equations
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
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 author.
Details
Original language | English |
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Pages (from-to) | 325-346 |
Number of pages | 22 |
Journal | ESAIM: Mathematical Modelling and Numerical Analysis |
Volume | 48 |
Issue number | 2 |
Publication status | Published - Mar 2014 |
Peer-reviewed | Yes |
Externally published | Yes |
External IDs
Scopus | 84894650089 |
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Keywords
Keywords
- Homogenization error, Quantitative estimate, Stochastic homogenization