Random matrices: Sharp concentration of eigenvalues

Abstract

Let $W_n=\frac{1}{\sqrt{n}}{M}_n$ be a Wigner matrix whose entries have vanishing third moment, normalized so that the spectrum is concentrated in the interval $[-2,2]$. We prove a concentration bound for $N_I=N_I(W_n)$, the number of eigenvalues of $W_n$ in an interval $I$. Our result shows that $N_I$ decays exponentially with standard deviation at most $O({\log }^{O(1)}n)$. This is best possible up to the constant exponent in the logarithmic term. As a corollary, the bulk eigenvalues are localized to an interval of width $O({\log }^{O(1)}n/n)$; again, this is optimal up to the exponent. These results strengthen recent results of Erdos, Yau and Yin (under the extra assumption of vanishing third

28 pages, no figures, to appear, Random Matrices: Theory and Applications. This is the final version, incorporating the referee suggestions

References in corpus (2)

• Local semicircle law and complete delocalization for Wigner random matrices
• Concentration of norms and eigenvalues of random matrices

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