The spectrum of heavy-tailed random matrices

dc.creatorArous, Gerard Ben
dc.creatorGuionnet, Alice
dc.date2007-07-14
dc.date.accessioned2026-07-07T08:18:27Z
dc.date.available2026-07-07T08:18:27Z
dc.descriptionLet $X_N$ be an $N\ts N$ random symmetric matrix with independent equidistributed entries. If the law $P$ of the entries has a finite second moment, it was shown by Wigner \cite{wigner} that the empirical distribution of the eigenvalues of $X_N$, once renormalized by $\sqrt{N}$, converges almost surely and in expectation to the so-called semicircular distribution as $N$ goes to infinity. In this paper we study the same question when $P$ is in the domain of attraction of an $α$-stable law. We prove that if we renormalize the eigenvalues by a constant $a_N$ of order $N^{\frac{1}α}$, the corresponding spectral distribution converges in expectation towards a law $μ_α$ which only depends on $α$. We characterize $μ_α$ and study some of its properties; it is a heavy-tailed probability measure which is absolutely continuous with respect to Lebesgue measure except possibly on a compact set of capacity zero.
dc.identifierhttps://arxiv.org/abs/0707.2159
dc.identifierhttp://arxiv.org/abs/0707.2159
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/134436
dc.subjectProbability
dc.subjectMathematical Physics
dc.subject15A52; 60E07
dc.titleThe spectrum of heavy-tailed random matrices
dc.typetext

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