Quantitative Estimates in Stochastic Homogenization of Elliptic Equations and Systems

Quantitative Estimates in Stochastic Homogenization of Elliptic Equations and Systems
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Book Synopsis Quantitative Estimates in Stochastic Homogenization of Elliptic Equations and Systems by : Nicolas Clozeau

Download or read book Quantitative Estimates in Stochastic Homogenization of Elliptic Equations and Systems written by Nicolas Clozeau and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This PhD thesis aims at a better understanding of the quantitative theory of the stochastic homogenization of elliptic equations and systems. In Chapter 2, we investigate the case of linear elliptic systems with random coefficients and long-range correlation. We adopt a parabolic approach and, by combining tools from probability (in the form of logarithmic Sobolev inequalities) and regularity theory, we optimally quantify the time decay of the parabolic semigroup with an explicit dependence on the correlation length. In Chapter 3, we turn to the analysis of nonlinear elliptic equations and systems with strongly monotone coefficients. Under a short-range correlation assumption, we prove optimal estimates on the correctors and the two-scale expansion, by developing new perturbative large-scale estimates for the linearized operator. In Chapter 4 and 5 we prove estimates on the bias in the Representative Volume Element method applied to linear elliptic equations. Using a periodization in law of the coefficients instead of considering a more classical method based on “snapshot” of the media, we establish the optimal rate of convergence of the method with respect to the size of the box by performing the first order expansion of the error. This result is obtained by combining a general formula from Gaussian calculus in the form of Price's formula that we generalise in the infinite-dimensional setting (in Chapter 4) and a two-scale expansion result of the Green's function of the random linear elliptic operator together with stochastic estimates on the correctors (in Chapter 5).


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