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May 2020 Large deviations for the largest eigenvalue of Rademacher matrices
Alice Guionnet, Jonathan Husson
Ann. Probab. 48(3): 1436-1465 (May 2020). DOI: 10.1214/19-AOP1398

Abstract

In this article, we consider random Wigner matrices, that is, symmetric matrices such that the subdiagonal entries of $X_{n}$ are independent, centered and with variance one except on the diagonal where the entries have variance two. We prove that, under some suitable hypotheses on the laws of the entries, the law of the largest eigenvalue satisfies a large deviation principle with the same rate function as in the Gaussian case. The crucial assumption is that the Laplace transform of the entries must be bounded above by the Laplace transform of a centered Gaussian variable with same variance. This is satisfied by the Rademacher law and the uniform law on $[-\sqrt{3},\sqrt{3}]$. We extend our result to complex entries Wigner matrices and Wishart matrices.

Citation

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Alice Guionnet. Jonathan Husson. "Large deviations for the largest eigenvalue of Rademacher matrices." Ann. Probab. 48 (3) 1436 - 1465, May 2020. https://doi.org/10.1214/19-AOP1398

Information

Received: 1 October 2018; Revised: 1 August 2019; Published: May 2020
First available in Project Euclid: 17 June 2020

zbMATH: 07226366
MathSciNet: MR4112720
Digital Object Identifier: 10.1214/19-AOP1398

Subjects:
Primary: 60B20 , 60F10

Keywords: large deviations , random matrices

Rights: Copyright © 2020 Institute of Mathematical Statistics

Vol.48 • No. 3 • May 2020
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