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Quantitative Stochastic Homogenization and Large-Scale Regularity

Quantitative Stochastic Homogenization and Large-Scale Regularity PDF Author: Scott Armstrong
Publisher: Springer
ISBN: 3030155455
Category : Mathematics
Languages : en
Pages : 518

Book Description
The focus of this book is the large-scale statistical behavior of solutions of divergence-form elliptic equations with random coefficients, which is closely related to the long-time asymptotics of reversible diffusions in random media and other basic models of statistical physics. Of particular interest is the quantification of the rate at which solutions converge to those of the limiting, homogenized equation in the regime of large scale separation, and the description of their fluctuations around this limit. This self-contained presentation gives a complete account of the essential ideas and fundamental results of this new theory of quantitative stochastic homogenization, including the latest research on the topic, and is supplemented with many new results. The book serves as an introduction to the subject for advanced graduate students and researchers working in partial differential equations, statistical physics, probability and related fields, as well as a comprehensive reference for experts in homogenization. Being the first text concerned primarily with stochastic (as opposed to periodic) homogenization and which focuses on quantitative results, its perspective and approach are entirely different from other books in the literature.

Quantitative Stochastic Homogenization and Large-Scale Regularity

Quantitative Stochastic Homogenization and Large-Scale Regularity PDF Author: Scott Armstrong
Publisher: Springer
ISBN: 3030155455
Category : Mathematics
Languages : en
Pages : 518

Book Description
The focus of this book is the large-scale statistical behavior of solutions of divergence-form elliptic equations with random coefficients, which is closely related to the long-time asymptotics of reversible diffusions in random media and other basic models of statistical physics. Of particular interest is the quantification of the rate at which solutions converge to those of the limiting, homogenized equation in the regime of large scale separation, and the description of their fluctuations around this limit. This self-contained presentation gives a complete account of the essential ideas and fundamental results of this new theory of quantitative stochastic homogenization, including the latest research on the topic, and is supplemented with many new results. The book serves as an introduction to the subject for advanced graduate students and researchers working in partial differential equations, statistical physics, probability and related fields, as well as a comprehensive reference for experts in homogenization. Being the first text concerned primarily with stochastic (as opposed to periodic) homogenization and which focuses on quantitative results, its perspective and approach are entirely different from other books in the literature.

Quantitative Estimates in Stochastic Homogenization of Elliptic Equations and Systems

Quantitative Estimates in Stochastic Homogenization of Elliptic Equations and Systems PDF Author: Nicolas Clozeau
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

Book Description
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).

Variational Convergence And Stochastic Homogenization Of Nonlinear Reaction-diffusion Problems

Variational Convergence And Stochastic Homogenization Of Nonlinear Reaction-diffusion Problems PDF Author: Omar Anza Hafsa
Publisher: World Scientific
ISBN: 9811258503
Category : Mathematics
Languages : en
Pages : 321

Book Description
A substantial number of problems in physics, chemical physics, and biology, are modeled through reaction-diffusion equations to describe temperature distribution or chemical substance concentration. For problems arising from ecology, sociology, or population dynamics, they describe the density of some populations or species. In this book the state variable is a concentration, or a density according to the cases. The reaction function may be complex and include time delays terms that model various situations involving maturation periods, resource regeneration times, or incubation periods. The dynamics may occur in heterogeneous media and may depend upon a small or large parameter, as well as the reaction term. From a purely formal perspective, these parameters are indexed by n. Therefore, reaction-diffusion equations give rise to sequences of Cauchy problems.The first part of the book is devoted to the convergence of these sequences in a sense made precise in the book. The second part is dedicated to the specific case when the reaction-diffusion problems depend on a small parameter ∊ₙ intended to tend towards 0. This parameter accounts for the size of small spatial and randomly distributed heterogeneities. The convergence results obtained in the first part, with additionally some probabilistic tools, are applied to this specific situation. The limit problems are illustrated through biological invasion, food-limited or prey-predator models where the interplay between environment heterogeneities in the individual evolution of propagation species plays an essential role. They provide a description in terms of deterministic and homogeneous reaction-diffusion equations, for which numerical schemes are possible.

Harmonic Analysis and Applications

Harmonic Analysis and Applications PDF Author: Carlos E. Kenig
Publisher: American Mathematical Soc.
ISBN: 1470461277
Category : Education
Languages : en
Pages : 345

Book Description
The origins of the harmonic analysis go back to an ingenious idea of Fourier that any reasonable function can be represented as an infinite linear combination of sines and cosines. Today's harmonic analysis incorporates the elements of geometric measure theory, number theory, probability, and has countless applications from data analysis to image recognition and from the study of sound and vibrations to the cutting edge of contemporary physics. The present volume is based on lectures presented at the summer school on Harmonic Analysis. These notes give fresh, concise, and high-level introductions to recent developments in the field, often with new arguments not found elsewhere. The volume will be of use both to graduate students seeking to enter the field and to senior researchers wishing to keep up with current developments.

Flowing Matter

Flowing Matter PDF Author: Federico Toschi
Publisher: Springer Nature
ISBN: 3030233707
Category : Science
Languages : en
Pages : 309

Book Description
This open access book, published in the Soft and Biological Matter series, presents an introduction to selected research topics in the broad field of flowing matter, including the dynamics of fluids with a complex internal structure -from nematic fluids to soft glasses- as well as active matter and turbulent phenomena. Flowing matter is a subject at the crossroads between physics, mathematics, chemistry, engineering, biology and earth sciences, and relies on a multidisciplinary approach to describe the emergence of the macroscopic behaviours in a system from the coordinated dynamics of its microscopic constituents. Depending on the microscopic interactions, an assembly of molecules or of mesoscopic particles can flow like a simple Newtonian fluid, deform elastically like a solid or behave in a complex manner. When the internal constituents are active, as for biological entities, one generally observes complex large-scale collective motions. Phenomenology is further complicated by the invariable tendency of fluids to display chaos at the large scales or when stirred strongly enough. This volume presents several research topics that address these phenomena encompassing the traditional micro-, meso-, and macro-scales descriptions, and contributes to our understanding of the fundamentals of flowing matter. This book is the legacy of the COST Action MP1305 “Flowing Matter”.

Periodic Homogenization of Elliptic Systems

Periodic Homogenization of Elliptic Systems PDF Author: Zhongwei Shen
Publisher: Springer
ISBN: 3319912143
Category : Mathematics
Languages : en
Pages : 291

Book Description
This monograph surveys the theory of quantitative homogenization for second-order linear elliptic systems in divergence form with rapidly oscillating periodic coefficients in a bounded domain. It begins with a review of the classical qualitative homogenization theory, and addresses the problem of convergence rates of solutions. The main body of the monograph investigates various interior and boundary regularity estimates that are uniform in the small parameter e>0. Additional topics include convergence rates for Dirichlet eigenvalues and asymptotic expansions of fundamental solutions, Green functions, and Neumann functions. The monograph is intended for advanced graduate students and researchers in the general areas of analysis and partial differential equations. It provides the reader with a clear and concise exposition of an important and currently active area of quantitative homogenization.

Random Graphs, Phase Transitions, and the Gaussian Free Field

Random Graphs, Phase Transitions, and the Gaussian Free Field PDF Author: Martin T. Barlow
Publisher: Springer Nature
ISBN: 3030320111
Category : Mathematics
Languages : en
Pages : 421

Book Description
The 2017 PIMS-CRM Summer School in Probability was held at the Pacific Institute for the Mathematical Sciences (PIMS) at the University of British Columbia in Vancouver, Canada, during June 5-30, 2017. It had 125 participants from 20 different countries, and featured two main courses, three mini-courses, and twenty-nine lectures. The lecture notes contained in this volume provide introductory accounts of three of the most active and fascinating areas of research in modern probability theory, especially designed for graduate students entering research: Scaling limits of random trees and random graphs (Christina Goldschmidt) Lectures on the Ising and Potts models on the hypercubic lattice (Hugo Duminil-Copin) Extrema of the two-dimensional discrete Gaussian free field (Marek Biskup) Each of these contributions provides a thorough introduction that will be of value to beginners and experts alike.

Research in Mathematics of Materials Science

Research in Mathematics of Materials Science PDF Author: Malena I. Español
Publisher: Springer Nature
ISBN: 3031044967
Category : Mathematics
Languages : en
Pages : 514

Book Description
This volume highlights contributions of women mathematicians in the study of complex materials and includes both original research papers and reviews. The featured topics and methods draw on the fields of Calculus of Variations, Partial Differential Equations, Functional Analysis, Differential Geometry and Topology, as well as Numerical Analysis and Mathematical Modelling. Areas of applications include foams, fluid-solid interactions, liquid crystals, shape-memory alloys, magnetic suspensions, failure in solids, plasticity, viscoelasticity, homogenization, crystallization, grain growth, and phase-field models.

Homogenization Theory for Multiscale Problems

Homogenization Theory for Multiscale Problems PDF Author: Xavier Blanc
Publisher: Springer Nature
ISBN: 3031218337
Category : Mathematics
Languages : en
Pages : 469

Book Description
The book provides a pedagogic and comprehensive introduction to homogenization theory with a special focus on problems set for non-periodic media. The presentation encompasses both deterministic and probabilistic settings. It also mixes the most abstract aspects with some more practical aspects regarding the numerical approaches necessary to simulate such multiscale problems. Based on lecture courses of the authors, the book is suitable for graduate students of mathematics and engineering.

Stochastic Optimization for Large-scale Machine Learning

Stochastic Optimization for Large-scale Machine Learning PDF Author: Vinod Kumar Chauhan
Publisher: CRC Press
ISBN: 1000505618
Category : Computers
Languages : en
Pages : 189

Book Description
Advancements in the technology and availability of data sources have led to the `Big Data' era. Working with large data offers the potential to uncover more fine-grained patterns and take timely and accurate decisions, but it also creates a lot of challenges such as slow training and scalability of machine learning models. One of the major challenges in machine learning is to develop efficient and scalable learning algorithms, i.e., optimization techniques to solve large scale learning problems. Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research directions to tackle the challenge. Developed optimisation techniques are also explored to improve machine learning algorithms based on data access and on first and second order optimisation methods. Key Features: Bridges machine learning and Optimisation. Bridges theory and practice in machine learning. Identifies key research areas and recent research directions to solve large-scale machine learning problems. Develops optimisation techniques to improve machine learning algorithms for big data problems. The book will be a valuable reference to practitioners and researchers as well as students in the field of machine learning.