English

Random matrices: Sharp concentration of eigenvalues

Probability 2013-08-13 v4

Abstract

Let Wn=1nMnW_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][-2,2]. We prove a concentration bound for NI=NI(Wn)N_I = N_I(W_n), the number of eigenvalues of WnW_n in an interval II. Our result shows that NIN_I decays exponentially with standard deviation at most O(logO(1)n)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(logO(1)n/n)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

Keywords

Cite

@article{arxiv.1201.4789,
  title  = {Random matrices: Sharp concentration of eigenvalues},
  author = {Terence Tao and Van Vu},
  journal= {arXiv preprint arXiv:1201.4789},
  year   = {2013}
}

Comments

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

R2 v1 2026-06-21T20:08:33.680Z