Central Limits and Homogenization in Random Media
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TLDR
In this paper, the rescaled difference between the perturbed and unperturbed solutions may be written asymptotically as explicit Gaussian processes, and the results are derived for more general elliptic equations with random coefficients in one dimension of space.Abstract:
We consider the perturbation of elliptic pseudodifferential operators $P(\mathbf{x},\mathbf{D})$ with more than square integrable Green's functions by random, rapidly varying, sufficiently mixing, potentials of the form $q(\frac{\mathbf{x}}{\varepsilon},\omega)$. We analyze the source and spectral problems associated with such operators and show that the rescaled difference between the perturbed and unperturbed solutions may be written asymptotically as $\varepsilon \to 0$ as explicit Gaussian processes. Such results may be seen as central limit corrections to homogenization (law of large numbers). Similar results are derived for more general elliptic equations with random coefficients in one dimension of space. The results are based on the availability of a rapidly converging integral formulation for the perturbed solutions and on the use of classical central limit results for random processes with appropriate mixing conditions.read more
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Random integrals and correctors in homogenization
TL;DR: Derivations are based on a careful analysis of random oscillatory integrals of processes with long-range correlations and it is shown that the longer the range of the correlations, the larger is the amplitude of the corrector.
Journal Article
Estimates in probability of the residual between the random and the homogenized solutions of one‐dimensional second‐order operator
TL;DR: In this article, the authors considered the problem of homogenization of a one-dimensional second-order elliptic operator with random coefficients satisfying strong or uniform mixing conditions and obtained several sharp estimates in terms of the corresponding mixing coefficient.