Large Random Matrices: Lectures on Macroscopic Asymptotics

• Wigner matrices and moments estimates.- Wigner#x2019;s theorem.- Wigner's matrices; more moments estimates.- Words in several independent Wigner matrices.- Wigner matrices and concentration inequalities.- Concentration inequalities and logarithmic Sobolev inequalities.- Generalizations.- Concentration inequalities for random matrices.- Matrix models.- Maps and Gaussian calculus.- First-order expansion.- Second-order expansion for the free energy.- Eigenvalues of Gaussian Wigner matrices and large deviations.- Large deviations for the law of the spectral measure of Gaussian Wigner's matrices.- Large Deviations of the Maximum Eigenvalue.- Stochastic calculus.- Stochastic analysis for random matrices.- Large deviation principle for the law of the spectral measure of shifted Wigner matrices.- Asymptotics of Harish-Chandra-Itzykson-Zuber integrals and of Schur polynomials.- Asymptotics of some matrix integrals.- Free probability.- Free probability setting.- Freeness.- Free entropy.- Basics of matrices.- Basics of probability theory.

From the reviews: "This book is a set of lecture notes on eigenvalues of large random matrices. ... useful to all mathematicians and statisticians who are interested in Wigner matrices. ... In summary, the book is very much worth perusal." (Vladislav Kargin, Mathematical Reviews, Issue 2010 d)