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Asymptotic analysis for periodic structures

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TLDR
In this article, the authors give a systematic introduction of multiple scale methods for partial differential equations, including their original use for rigorous mathematical analysis in elliptic, parabolic, and hyperbolic problems, and with the use of probabilistic methods when appropriate.
Abstract
This is a reprinting of a book originally published in 1978. At that time it was the first book on the subject of homogenization, which is the asymptotic analysis of partial differential equations with rapidly oscillating coefficients, and as such it sets the stage for what problems to consider and what methods to use, including probabilistic methods. At the time the book was written the use of asymptotic expansions with multiple scales was new, especially their use as a theoretical tool, combined with energy methods and the construction of test functions for analysis with weak convergence methods. Before this book, multiple scale methods were primarily used for non-linear oscillation problems in the applied mathematics community, not for analyzing spatial oscillations as in homogenization. In the current printing a number of minor corrections have been made, and the bibliography was significantly expanded to include some of the most important recent references. This book gives systematic introduction of multiple scale methods for partial differential equations, including their original use for rigorous mathematical analysis in elliptic, parabolic, and hyperbolic problems, and with the use of probabilistic methods when appropriate. The book continues to be interesting and useful to readers of different backgrounds, both from pure and applied mathematics, because of its informal style of introducing the multiple scale methodology and the detailed proofs.

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Journal Article

Variance Reduction in Stochastic Homogenization Using Antithetic Variables

TL;DR: In this article, theoretical issues related to the problem of variance reduction in numerical approaches for stochastic homogenization are examined, and it is demonstrated theoretically that a tech- nique based on antithetic variables can indeed reduce the variance of the output of the computation, and decrease the overall computational cost of such a mul- tiscale problem.
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Diffractive behavior of the wave equation in periodic media: weak convergence analysis

TL;DR: In this article, the homogenization and singular perturbation of the wave equation in a periodic media for long times of the order of the inverse of the period was studied and the solution was approximately equal to two waves propagating in opposite directions at a high group velocity with envelope functions which obey a Schrodinger type equation.
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UNIFORM W 1;p ESTIMATES FOR SYSTEMS OF LINEAR ELASTICITY IN A PERIODIC MEDIUM

TL;DR: In this article, the uniform W 1, p estimate was obtained for a family of elliptic systems of linear elasticity with rapidly oscillating periodic coefficients in a Lipschitz domain in R n for solutions to the Dirichlet problem.
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Homogenization for nonlinear PDEs in general domains with oscillatory Neumann boundary data

TL;DR: In this paper, the authors investigate averaging properties of fully nonlinear PDEs in bounded domains with oscillatory Neumann boundary data and show that the homogenized Neumann data is continuous with respect to the normal direction of the boundary.
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A quantitative central limit theorem for the random walk among random conductances

TL;DR: In this article, the authors considered the random walk among random conductances on the Euclidean plane, and obtained a quantitative version of the central limit theorem for this random walk, which takes the form of a Berry-Esseen estimate with speed $t^{-1/10}$ for $d \le 2, and speed$t^{ − 1/5} for$d \ge 3, up to logarithmic corrections.
References
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Measurable eigenvectors for Hermitian matrix-valued polynomials☆

TL;DR: In this article, a polynomial Hermitian matrices over the complex number field C are considered and the relative eigenvalue problem is formulated as a linear combination of the repeated eigenvalues of the matrix A(p)x = λEx, x ϵ Cm.