Semicircle law on short scales and delocalization of eigenvectors for Wigner random matrices
László Erdős, Benjamin Schlein, and Horng-Tzer Yau
Source: Ann. Probab.
Volume 37, Number 3
(2009), 815-852.
Abstract
We consider N×N Hermitian random matrices with i.i.d. entries. The matrix is normalized so that the average spacing between consecutive eigenvalues is of order 1/N. We study the connection between eigenvalue statistics on microscopic energy scales η≪1 and (de)localization properties of the eigenvectors. Under suitable assumptions on the distribution of the single matrix elements, we first give an upper bound on the density of states on short energy scales of order η∼log N/N. We then prove that the density of states concentrates around the Wigner semicircle law on energy scales η≫N−2/3. We show that most eigenvectors are fully delocalized in the sense that their ℓp-norms are comparable with N1/p−1/2 for p≥2, and we obtain the weaker bound N2/3(1/p−1/2) for all eigenvectors whose eigenvalues are separated away from the spectral edges. We also prove that, with a probability very close to one, no eigenvector can be localized. Finally, we give an optimal bound on the second moment of the Green function.
Primary Subjects: 15A52, 82B44
Keywords: Semicircle law; Wigner random matrix; random Schrödinger operator; density of states; localization; extended states
Full-text: Access denied (no subscription detected)
We're sorry, but we are unable to provide you with the full text of this article because we are not able to identify you as a subscriber.
If you have a personal subscription to this journal, then please login. If you are already logged in, then you may need to update your profile to register your subscription.
Read more about accessing full-text
Links and Identifiers
Permanent link to this document: http://projecteuclid.org/euclid.aop/1245434021
Digital Object Identifier: doi:10.1214/08-AOP421
References
[1] Bai, Z. D. (1993). Convergence rate of expected spectral distributions of large random matrices. I. Wigner matrices. Ann. Probab. 21 625–648.
[2] Bai, Z. D., Miao, B. and Tsay, J. (2002). Convergence rates of the spectral distributions of large Wigner matrices. Int. Math. J. 1 65–90.
[3] Bourgain, J. Private communication.
[4] Boutet de Monvel, A. and Khorunzhy, A. (1999). Asymptotic distribution of smoothed eigenvalue density. II. Wigner random matrices. Random Oper. Stochastic Equations 7 149–168.
[5] Brascamp, H. J. and Lieb, E. H. (1976). On extensions of the Brunn–Minkowski and Prékopa–Leindler theorems, including inequalities for log concave functions, and with an application to the diffusion equation. J. Funct. Anal. 22 366–389.
[6] Deift, P. A. (1999). Orthogonal Polynomials and Random Matrices: A Riemann–Hilbert Approach. Courant Lecture Notes in Mathematics 3. New York Univ. Courant Institute of Mathematical Sciences, New York.
[7] den Boer, A. F., van der Hofstad, R. and Klok, M. J. (2007). Large deviations for eigenvalues of sample covariance matrices. Preprint.
[8] Guionnet, A. (2009). Large Random Matrices: Lectures on Macroscopic Asymptotics. École d’Eté de Probabilités de Saint-Flour XXXVI 2006. Lecture Notes in Mathematics. Springer.
[9] Guionnet, A. and Zeitouni, O. (2000). Concentration of the spectral measure for large matrices. Electron. Comm. Probab. 5 119–136.
[10] Johansson, K. (2001). Universality of the local spacing distribution in certain ensembles of Hermitian Wigner matrices. Comm. Math. Phys. 215 683–705.
[11] Khorunzhy, A. (1997). On smoothed density of states for Wigner random matrices. Random Oper. Stochastic Equations 5 147–162.