Introduction to Random Matrices

Abstract

These notes provide an introduction to the theory of random matrices. The central quantity studied is τ(a)= det(1-K) where K is the integral operator with kernel 1/π π(x-y) x-y I(y). Here I=j(a2j-1,a2j) and I(y) is the characteristic function of the set I. In the Gaussian Unitary Ensemble (GUE) the probability that no eigenvalues lie in I is equal to τ(a). Also τ(a) is a tau-function and we present a new simplified derivation of the system of nonlinear completely integrable equations (the aj's are the independent variables) that were first derived by Jimbo, Miwa, M\ori, and Sato in 1980. In the case of a single interval these equations are reducible to a Painlev\'e V equation. For large s we give an asymptotic formula for E2(n;s), which is the probability in the GUE that exactly n eigenvalues lie in an interval of length s.

0

Turn this paper into a full lesson

ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.

Discussion (0)

Sign in to join the discussion.

Loading comments…