An Introduction to Random Matrices

Greg W. Anderson, Alice Guionnet, Ofer Zeitouni

ISBN 10: 0521194520 / ISBN 13: 9780521194525

Published by Cambridge University Press, GB, 2009

About this Item

The theory of random matrices plays an important role in many areas of pure mathematics and employs a variety of sophisticated mathematical tools (analytical, probabilistic and combinatorial). This diverse array of tools, while attesting to the vitality of the field, presents several formidable obstacles to the newcomer, and even the expert probabilist. This rigorous introduction to the basic theory is sufficiently self-contained to be accessible to graduate students in mathematics or related sciences, who have mastered probability theory at the graduate level, but have not necessarily been exposed to advanced notions of functional analysis, algebra or geometry. Useful background material is collected in the appendices and exercises are also included throughout to test the reader's understanding. Enumerative techniques, stochastic analysis, large deviations, concentration inequalities, disintegration and Lie algebras all are introduced in the text, which will enable readers to approach the research literature with confidence.

Seller Inventory # LU-9780521194525

Bibliographic Details

• Title: An Introduction to Random Matrices
• Publisher: Cambridge University Press, GB
• Publication Date: 2009
• Language: English
• ISBN 10: 0521194520
• ISBN 13: 9780521194525
• Binding: Hardback
• Condition: New

About this title

Synopsis

The theory of random matrices plays an important role in many areas of pure mathematics and employs a variety of sophisticated mathematical tools (analytical, probabilistic and combinatorial). This diverse array of tools, while attesting to the vitality of the field, presents several formidable obstacles to the newcomer, and even the expert probabilist. This rigorous introduction to the basic theory is sufficiently self-contained to be accessible to graduate students in mathematics or related sciences, who have mastered probability theory at the graduate level, but have not necessarily been exposed to advanced notions of functional analysis, algebra or geometry. Useful background material is collected in the appendices and exercises are also included throughout to test the reader's understanding. Enumerative techniques, stochastic analysis, large deviations, concentration inequalities, disintegration and Lie algebras all are introduced in the text, which will enable readers to approach the research literature with confidence.

About the Authors

Greg W. Anderson is Professor in the School of Mathematics at the University of Minnesota.

Alice Guionnet is Director of Research at the Ecole Normale Supérieure in Lyon and the Centre National de la Recherche Scientifique (CNRS).

Ofer Zeitouni is Professor of Mathematics at both the University of Minnesota and the Weizmann Institute of Science, Israel.