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Poisson convergence for the largest eigenvalues of heavy tailed random matrices

Antonio Auffinger; Gérard Ben Arous; Sandrine Péché — 2009

Annales de l'I.H.P. Probabilités et statistiques

We study the statistics of the largest eigenvalues of real symmetric and sample covariance matrices when the entries are heavy tailed. Extending the result obtained by Soshnikov in ( (2004) 82–91), we prove that, in the absence of the fourth moment, the asymptotic behavior of the top eigenvalues is determined by the behavior of the largest entries of the matrix.

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