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Related papers: No-gaps delocalization for general random matrices

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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

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

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 prove that the eigenvectors associated to small enough eigenvalues of an heavy-tailed symmetric random matrix are delocalized with probability tending to one as the size of the matrix grows to infinity. The delocalization is measured…

Probability · Mathematics 2017-08-23 Charles Bordenave , Alice Guionnet

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 delocalization of null vectors and eigenvectors of random matrices with i.i.d entries. Let $A$ be an $n\times n$ random matrix with i.i.d real subgaussian entries of zero mean and unit variance. We show that with probability at…

Probability · Mathematics 2019-09-19 Anna Lytova , Konstantin Tikhomirov

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 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

The empirical eigenvalue distribution of the elliptic random matrix ensemble tends to the uniform measure on an ellipse in the complex plane as its dimension tends to infinity. We show this convergence on all mesoscopic scales slightly…

Probability · Mathematics 2021-02-08 Johannes Alt , Torben Krüger

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

In this paper we establish eigenvector delocalization and bulk universality for L\'{e}vy matrices, which are real, symmetric, $N \times N$ random matrices $\textbf{H}$ whose upper triangular entries are independent, identically distributed…

Probability · Mathematics 2019-11-13 Amol Aggarwal , Patrick Lopatto , Horng-Tzer Yau

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

It is shown that certain ensembles of random matrices with entries that vanish outside a band around the diagonal satisfy a localization condition on the resolvent which guarantees that eigenvectors have strong overlap with a vanishing…

Mathematical Physics · Physics 2010-06-29 Jeffrey Schenker

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

We obtain general, exact formulas for the overlaps between the eigenvectors of large correlated random matrices, with additive or multiplicative noise. These results have potential applications in many different contexts, from quantum…

Statistical Mechanics · Physics 2018-12-05 Joël Bun , Jean-Philippe Bouchaud , Marc Potters

We consider $N\times N$ symmetric or hermitian random matrices with independent, identically distributed entries where the probability distribution for each matrix element is given by a measure $\nu$ with a subexponential decay. We prove…

Mathematical Physics · Physics 2017-08-23 Laszlo Erdos

The diagonalization of matrices may be the top priority in the application of modern physics. In this paper, we numerically demonstrate that, for real symmetric random matrices with non-positive off-diagonal elements, a universal scaling…

Quantum Physics · Physics 2020-11-06 Wei Pan , Jing Wang , Deyan Sun

Consider $N\times N$ symmetric one-dimensional random band matrices with general distribution of the entries and band width $W \geq N^{3/4+\varepsilon}$ for any $\varepsilon>0$. In the bulk of the spectrum and in the large $N$ limit, we…

Probability · Mathematics 2018-07-05 Paul Bourgade , Horng-Tzer Yau , Jun Yin

We prove an optimal order delocalization estimate for the eigenvectors of general $N \times N$ non-Hermitian matrices $X$: $\| {\bf v } \|_\infty \leq C \sqrt{\frac{\log N}{N}}$ with very high probability, for any right or left eigenvector…

Probability · Mathematics 2025-09-19 Giorgio Cipolloni , Benjamin Landon
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