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Consider an n x n Hermitian random matrix with, above the diagonal, independent entries with alpha-stable symmetric distribution and 0 < alpha < 2. We establish new bounds on the rate of convergence of the empirical spectral distribution of…

Probability · Mathematics 2012-02-01 Charles Bordenave , Alice Guionnet

We prove that an n by n random matrix G with independent entries is completely delocalized. Suppose the entries of G have zero means, variances uniformly bounded below, and a uniform tail decay of exponential type. Then with high…

Probability · Mathematics 2015-11-04 Mark Rudelson , Roman Vershynin

We consider some random band matrices with band-width $N^\mu$ whose entries are independent random variables with distribution tail in $x^{-\alpha}$. We consider the largest eigenvalues and the associated eigenvectors and prove the…

Probability · Mathematics 2015-06-25 Florent Benaych-Georges , Sandrine Péché

We prove that with high probability, every eigenvector of a random matrix is delocalized in the sense that any subset of its coordinates carries a non-negligible portion of its $\ell_2$ norm. Our results pertain to a wide class of random…

Probability · Mathematics 2016-12-23 Mark Rudelson , Roman Vershynin

Improving upon results of Rudelson and Vershynin, we establish delocalization bounds for eigenvectors of independent-entry random matrices. In particular, we show that with high probability every eigenvector is delocalized, meaning any…

Probability · Mathematics 2019-02-01 Kyle Luh , Sean O'Rourke

We investigate delocalization phenomena for eigenvectors of real random matrices that are invariant by orthogonal transformations. A specific phenomenon with these ensembles is that an eigenvector is typically more localized when its…

Probability · Mathematics 2026-02-12 Lucas Benigni , Simon Coste , Guillaume Dubach

We prove delocalization of eigenvectors of vertex-transitive graphs via elementary estimates of the spectral projector. We recover in this way known results which were formerly proved using representation theory. Similar techniques show…

Spectral Theory · Mathematics 2025-10-15 Nicolas Burq , Cyril Letrouit

We study the eigenvectors of generalized Wigner matrices with subexponential entries and prove that they delocalize at the optimal rate with overwhelming probability. We also prove high probability delocalization bounds with sharp…

Probability · Mathematics 2021-09-10 Lucas Benigni , Patrick Lopatto

We consider a general class of $n\times n$ random band matrices with bandwidth $W$. When $W^2\ll n$, we prove that with high probability the eigenvectors of such matrices are localized and decay exponentially at the sharp scale $W^2$.…

Probability · Mathematics 2025-08-29 Reuben Drogin

We present an analytical technique to compute the probability of rare events in which the largest eigenvalue of a random matrix is atypically large (i.e.\ the right tail of its large deviations). The results also transfer to the left tail…

Statistical Mechanics · Physics 2021-05-26 Antoine Maillard

Let $x \in S^{n-1}$ be a unit eigenvector of an $n \times n$ random matrix. This vector is delocalized if it is distributed roughly uniformly over the real or complex sphere. This intuitive notion can be quantified in various ways. In these…

Probability · Mathematics 2017-07-27 Mark Rudelson

Consider a real diagonal deterministic matrix $X_n$ of size $n$ with spectral measure converging to a compactly supported probability measure. We perturb this matrix by adding a random finite rank matrix, with delocalized eigenvectors. We…

Probability · Mathematics 2011-06-21 Florent Benaych-Georges , Alice Guionnet , Mylène Maïda

In this text, we consider an N by N random matrix X such that all but o(N) rows of X have W non identically zero entries, the other rows having lass than $W$ entries (such as, for example, standard or cyclic band matrices). We always…

Probability · Mathematics 2014-01-21 Florent Benaych-Georges , Sandrine Péché

In contrast to the neatly bounded spectra of densely populated large random matrices, sparse random matrices often exhibit unbounded eigenvalue tails on the real and imaginary axis, called Lifshitz tails. In the case of asymmetric matrices,…

Disordered Systems and Neural Networks · Physics 2025-11-07 Pietro Valigi , Joseph W. Baron , Izaak Neri , Giulio Biroli , Chiara Cammarota

We consider large random matrices with a general slowly decaying correlation among its entries. We prove universality of the local eigenvalue statistics and optimal local laws for the resolvent away from the spectral edges, generalizing the…

Probability · Mathematics 2020-06-01 László Erdős , Torben Krüger , Dominik Schröder

This work provide a thorough study of L\'evy or heavy-tailed random matrices (LM). By analysing the self-consistent equation on the probability distribution of the diagonal elements of the resolvent we establish the equation determining the…

Disordered Systems and Neural Networks · Physics 2016-01-26 Elena Tarquini , Giulio Biroli , Marco Tarzia

In this work we consider deterministic, symmetric matrices with heavy-tailed noise imposed on entries within a fixed distance $K$ to the diagonal. The most important example is discrete 1d random Schr\"odinger operator defined on…

Probability · Mathematics 2025-07-01 Yi Han

We consider Hermitian and symmetric random band matrices $H = (h_{xy})$ in $d \geq 1$ dimensions. The matrix entries $h_{xy}$, indexed by $x,y \in (\bZ/L\bZ)^d$, are independent, centred random variables with variances $s_{xy} = \E…

Probability · Mathematics 2015-06-05 Laszlo Erdos , Antti Knowles , Horng-Tzer Yau , Jun Yin

We consider $N\times N$ self-adjoint Gaussian random matrices defined by an arbitrary deterministic sparsity pattern with $d$ nonzero entries per row. We show that such random matrices exhibit a canonical localization-delocalization…

Probability · Mathematics 2024-01-03 Laura Shou , Ramon van Handel

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 \cite{Sos1}, we prove that, in the absence of the fourth…

Probability · Mathematics 2008-05-07 Antonio Auffinger , Gerard Ben Arous , Sandrine Peche
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