Overview
- Provides an in-depth examination of random matrices with applications over a vast variety of domains, including multivariate statistics, random growth models, and many others
- Applies the theory of integrable systems, a source of powerful analytic methods, to the solution of fundamental problems in random systems and processes
- Features an interdisciplinary approach that sheds new light on a dynamic topic of current research
- Explains and develops the phenomenon of "universality," in particular, the occurrence of the Tracy-Widom distribution for eigenvalues at the "edge of the spectrum," in the longest increasing subsequence of a random permutation and a variety of critical phenomena in the double scaling limit
Part of the book series: CRM Series in Mathematical Physics (CRM)
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About this book
This book explores the remarkable connections between two domains that, a priori, seem unrelated: Random matrices (together with associated random processes) and integrable systems. The relations between random matrix models and the theory of classical integrable systems have long been studied. These appear mainly in the deformation theory, when parameters characterizing the measures or the domain of localization of the eigenvalues are varied. The resulting differential equations determining the partition function and correlation functions are, remarkably, of the same type as certain equations appearing in the theory of integrable systems. They may be analyzed effectively through methods based upon the Riemann-Hilbert problem of analytic function theory and by related approaches to the study of nonlinear asymptotics in the large N limit. Associated with studies of matrix models are certain stochastic processes, the "Dyson processes", and their continuum diffusion limits, which govern the spectrum in random matrix ensembles, and may also be studied by related methods.
Random Matrices, Random Processes and Integrable Systems provides an in-depth examination of random matrices with applications over a vast variety of domains, including multivariate statistics, random growth models, and many others. Leaders in the field apply the theory of integrable systems to the solution of fundamental problems in random systems and processes using an interdisciplinary approach that sheds new light on a dynamic topic of current research.
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Keywords
Table of contents (7 chapters)
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Random Matrices, Random Processes and Integrable Models
Reviews
From the reviews:
“The present volume consists of seven introductory articles originating from an intensive series of advanced courses given by the authors at the CRM in Montréal … . All articles are well-written by leading experts and the whole volume is an ideal starting point for anyone interested in this fascinating and modern topic at the intersection of mathematics and physics.” (G. Teschl, Monatshefte für Mathematik, Vol. 171 (3-4), September, 2013)
“This volume, written by the leading experts … provides a detailed look at many of the mathematical connections, ideas, directions, and methods that have come about since the early papers of Tracy and Widom. … this is a very nice collection of topics, especially for someone who wants to have all the RMT basics and also the basic computations and approaches that lead to other fields at hand. It should serve as a very valuable resource.” (Estelle L. Basor, Mathematical Reviews, February, 2013)
Editors and Affiliations
Bibliographic Information
Book Title: Random Matrices, Random Processes and Integrable Systems
Editors: John Harnad
Series Title: CRM Series in Mathematical Physics
DOI: https://doi.org/10.1007/978-1-4419-9514-8
Publisher: Springer New York, NY
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Hardcover ISBN: 978-1-4419-9513-1Published: 11 May 2011
Softcover ISBN: 978-1-4614-2877-0Published: 15 July 2013
eBook ISBN: 978-1-4419-9514-8Published: 06 May 2011
Series ISSN: 2627-7654
Series E-ISSN: 2627-7662
Edition Number: 1
Number of Pages: XVIII, 526
Topics: Theoretical, Mathematical and Computational Physics, Probability Theory and Stochastic Processes