Volume: 171; 2011; 632 pp; Hardcover
MSC: Primary 60; 15;
Print ISBN: 978-0-8218-5285-9
Product Code: SURV/171
List Price: $117.00
AMS Member Price: $93.60
MAA Member Price: $105.30
Electronic ISBN: 978-1-4704-1398-9
Product Code: SURV/171.E
List Price: $110.00
AMS Member Price: $88.00
MAA Member Price: $99.00
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Supplemental Materials
Eigenvalue Distribution of Large Random Matrices
Share this pageLeonid Pastur; Mariya Shcherbina
Random matrix theory is a wide and growing
field with a variety of concepts, results, and techniques and a vast
range of applications in mathematics and the related sciences. The
book, written by well-known experts, offers beginners a fairly
balanced collection of basic facts and methods (Part 1 on classical
ensembles) and presents experts with an exposition of recent advances
in the subject (Parts 2 and 3 on invariant ensembles and ensembles
with independent entries).
The text includes many of the authors' results and methods on
several main aspects of the theory, thus allowing them to present a
unique and personal perspective on the subject and to cover many
topics using a unified approach essentially based on the Stieltjes
transform and orthogonal polynomials. The exposition is supplemented
by numerous comments, remarks, and problems. This results in a book
that presents a detailed and self-contained treatment of the basic
random matrix ensembles and asymptotic regimes.
This book will be an important reference for researchers in a
variety of areas of mathematics and mathematical physics. Various
chapters of the book can be used for graduate courses; the main
prerequisite is a basic knowledge of calculus, linear algebra, and
probability theory.
Readership
Graduate students and research mathematicians interested in random matrix theory and its applications.
Reviews & Endorsements
While a wide variety of ensembles are studied in this text, the methods are coherently focused, relying heavily in particular on Stieltjes transform based tools. This gives a slightly different perspective on the subject from other recent texts which often focus on other methods.
-- Mathematical Reviews
Table of Contents
Table of Contents
Eigenvalue Distribution of Large Random Matrices
- Cover Cover11 free
- Title page iii4 free
- Contents v6 free
- Preface ix10 free
- Introduction 116 free
- Part I. Classical ensembles 3348 free
- Gaussian Ensembles: Semicircle law 3550
- Gaussian Ensembles: Central Limit Theorem for linear eigenvalue statistics 6984
- Gaussian Ensembles: Joint eigenvalue distribution and related results 101116
- Gaussian Unitary Ensemble 129144
- Gaussian Orthogonal Ensemble 159174
- Wishart and Laguerre Ensembles 177192
- Classical compact groups ensembles: Global regime 211226
- Classical compact group ensembles: Local regime 249264
- Law of addition of random matrices 275290
- Part II. Matrix Models 315330
- Matrix Models: Global regime 317332
- Bulk universality for hermitian Matrix Models 369384
- Universality for special points of hermitian Matrix Models 385400
- Jacobi matrices and limiting laws for linear eigenvalue statistics 437452
- Universality for real symmetric Matrix Models 469484
- Unitary Matrix Models 485500
- Part III. Ensembles with independent and weakly dependent entries 499514
- Matrices with Gaussian correlated entries 501516
- Wigner Ensembles 525540
- Sample covariance and related matrices 583598
- Bibliography 611626
- Index 631646 free
- Back Cover Back Cover1650