Fluctuations of extreme eigenvalues of sparse Erdos-R\'enyi graphs

Abstract

We consider a class of sparse random matrices which includes the adjacency matrix of the Erdos-R\'enyi graph G(N,p). We show that if N ≤ Np ≤ N1/3- then all nontrivial eigenvalues away from 0 have asymptotically Gaussian fluctuations. These fluctuations are governed by a single random variable, which has the interpretation of the total degree of the graph. This extends the result [19] on the fluctuations of the extreme eigenvalues from Np ≥ N2/9 + down to the optimal scale Np ≥ N. The main technical achievement of our proof is a rigidity bound of accuracy N-1/2- \, (Np)-1/2 for the extreme eigenvalues, which avoids the (Np)-1-expansions from [9,19,24]. Our result is the last missing piece, added to [8, 12, 19, 24], of a complete description of the eigenvalue fluctuations of sparse random matrices for Np ≥ N.

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