Hardcover ISBN: | 978-0-8218-5285-9 |
Product Code: | SURV/171 |
List Price: | $129.00 |
MAA Member Price: | $116.10 |
AMS Member Price: | $103.20 |
eBook ISBN: | 978-1-4704-1398-9 |
Product Code: | SURV/171.E |
List Price: | $125.00 |
MAA Member Price: | $112.50 |
AMS Member Price: | $100.00 |
Hardcover ISBN: | 978-0-8218-5285-9 |
eBook: ISBN: | 978-1-4704-1398-9 |
Product Code: | SURV/171.B |
List Price: | $254.00 $191.50 |
MAA Member Price: | $228.60 $172.35 |
AMS Member Price: | $203.20 $153.20 |
Hardcover ISBN: | 978-0-8218-5285-9 |
Product Code: | SURV/171 |
List Price: | $129.00 |
MAA Member Price: | $116.10 |
AMS Member Price: | $103.20 |
eBook ISBN: | 978-1-4704-1398-9 |
Product Code: | SURV/171.E |
List Price: | $125.00 |
MAA Member Price: | $112.50 |
AMS Member Price: | $100.00 |
Hardcover ISBN: | 978-0-8218-5285-9 |
eBook ISBN: | 978-1-4704-1398-9 |
Product Code: | SURV/171.B |
List Price: | $254.00 $191.50 |
MAA Member Price: | $228.60 $172.35 |
AMS Member Price: | $203.20 $153.20 |
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Book DetailsMathematical Surveys and MonographsVolume: 171; 2011; 632 ppMSC: Primary 60; 15
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.
ReadershipGraduate students and research mathematicians interested in random matrix theory and its applications.
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Table of Contents
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Chapters
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1. Introduction
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Part 1. Classical ensembles
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2. Gaussian ensembles: Semicircle law
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3. Gaussian ensembles: Central Limit Theorem for linear eigenvalue statistics
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4. Gaussian ensembles: Joint eigenvalue distribution and related results
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5. Gaussian unitary ensemble
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6. Gaussian orthogonal ensemble
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7. Wishart and Laguerre ensembles
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8. Classical compact groups ensembles: Global regime
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9. Classical compact group ensembles: Further results
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10. Law of addition of random matrices
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Part 2. Matrix models
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11. Matrix models: Global regime
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12. Bulk universality for Hermitian matrix models
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13. Universality for special points of Hermitian matrix models
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14. Jacobi matrices and limiting laws for linear eigenvalue statistics
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15. Universality for real symmetric matrix models
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16. Unitary matrix models
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Part 3. Ensembles with independent and weakly dependent entries
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17. Matrices with Gaussian correlated entries
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18. Wigner ensembles
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19. Sample covariance and related matrices
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Additional Material
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Reviews
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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
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RequestsReview Copy – for publishers of book reviewsPermission – for use of book, eBook, or Journal contentAccessibility – to request an alternate format of an AMS title
- Book Details
- Table of Contents
- Additional Material
- Reviews
- Requests
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.
Graduate students and research mathematicians interested in random matrix theory and its applications.
-
Chapters
-
1. Introduction
-
Part 1. Classical ensembles
-
2. Gaussian ensembles: Semicircle law
-
3. Gaussian ensembles: Central Limit Theorem for linear eigenvalue statistics
-
4. Gaussian ensembles: Joint eigenvalue distribution and related results
-
5. Gaussian unitary ensemble
-
6. Gaussian orthogonal ensemble
-
7. Wishart and Laguerre ensembles
-
8. Classical compact groups ensembles: Global regime
-
9. Classical compact group ensembles: Further results
-
10. Law of addition of random matrices
-
Part 2. Matrix models
-
11. Matrix models: Global regime
-
12. Bulk universality for Hermitian matrix models
-
13. Universality for special points of Hermitian matrix models
-
14. Jacobi matrices and limiting laws for linear eigenvalue statistics
-
15. Universality for real symmetric matrix models
-
16. Unitary matrix models
-
Part 3. Ensembles with independent and weakly dependent entries
-
17. Matrices with Gaussian correlated entries
-
18. Wigner ensembles
-
19. Sample covariance and related matrices
-
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