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Large deviations principle for the largest eigenvalue of Wigner matrices without Gaussian tails

Probability 2016-10-11 v3

Abstract

We prove a large deviation principle for the largest eigenvalue of Wigner matrices without Gaussian tails, namely such that the distribution tails P(X1,1>t)\mathbb{P}( |X_{1,1}|>t) and P(X1,2>t)\mathbb{P}(|X_{1,2}|>t) behave like ebtαe^{-bt^{\alpha}} and eatαe^{-at^{\alpha}} respectively for some a,b(0,+)a,b\in (0,+\infty) and α(0,2)\alpha\in (0,2). The large deviation principle is of speed Nα/2N^{\alpha/2} and with a good rate function depending only on the tail distribution of the entries.

Keywords

Cite

@article{arxiv.1502.07983,
  title  = {Large deviations principle for the largest eigenvalue of Wigner matrices without Gaussian tails},
  author = {Fanny Augeri},
  journal= {arXiv preprint arXiv:1502.07983},
  year   = {2016}
}
R2 v1 2026-06-22T08:39:56.065Z