Gaussian Fluctuation in Random Matrices

Abstract

Let $N(L)$ be the number of eigenvalues, in an interval of length $L$, of a matrix chosen at random from the Gaussian orthogonal, unitary, or symplectic ensembles of $N$ by $N$ matrices, in the limit $N\ensuremath{\rightarrow}\ensuremath{\infty}$. We prove that $[N(L)\ensuremath{-}〈N(L)〉]/\sqrt{\mathrm{ln}L}$ has a Gaussian distribution when $L\ensuremath{\rightarrow}\ensuremath{\infty}$. This theorem, which requires control of all the higher moments of the distribution, elucidates numerical and exact results on chaotic quantum systems and on the statistics of zeros of the Riemann zeta function.