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Related papers: Optimal decay of eigenvector overlap for non-Hermi…

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Consider the normalized adjacency matrices of random $d$-regular graphs on $N$ vertices with fixed degree $d\geq 3$, and denote the eigenvalues as $\lambda_1=d/\sqrt{d-1}\geq \lambda_2\geq\lambda_3\cdots\geq \lambda_N$. We prove that the…

Probability · Mathematics 2024-05-21 Jiaoyang Huang , Theo McKenzie , Horng-Tzer Yau

Statistical properties of non--symmetric real random matrices of size $M$, obtained as truncations of random orthogonal $N\times N$ matrices are investigated. We derive an exact formula for the density of eigenvalues which consists of two…

Statistical Mechanics · Physics 2010-10-21 Boris A. Khoruzhenko , Hans-Juergen Sommers , Karol Zyczkowski

We study Hermitian random matrix models with an external source matrix which has equispaced eigenvalues, and with an external field such that the limiting mean density of eigenvalues is supported on a single interval as the dimension tends…

Mathematical Physics · Physics 2013-06-25 Tom Claeys , Dong Wang

We consider large non-Hermitian real or complex random matrices $X$ with independent, identically distributed centred entries. We prove that their local eigenvalue statistics near the spectral edge, the unit circle, coincide with those of…

Probability · Mathematics 2023-01-11 Giorgio Cipolloni , László Erdős , Dominik Schröder

We consider $N\times N$ random matrices of the form $H = W + V$ where $W$ is a real symmetric Wigner matrix and $V$ a random or deterministic, real, diagonal matrix whose entries are independent of $W$. We assume subexponential decay for…

Probability · Mathematics 2015-09-29 Ji Oon Lee , Kevin Schnelli

We study the exponential relaxation of observables, propagated with a non-Hermitian transfer matrix, an example being out-of-time-ordered correlations (OTOC) in brickwall (BW) random quantum circuits. Until a time that scales as the system…

Quantum Physics · Physics 2023-12-25 Jaš Bensa

We continue the study of the Hermitian random matrix ensemble with external source $\frac{1}{Z_n} e^{-n \Tr({1/2}M^2 -AM)} dM$ where $A$ has two distinct eigenvalues $\pm a$ of equal multiplicity. This model exhibits a phase transition for…

Mathematical Physics · Physics 2010-07-29 Alexander I. Aptekarev , Pavel M. Bleher , Arno B. J. Kuijlaars

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

We consider a diffusive matrix process $(X_t)_{t\ge 0}$ defined as $X_t:=A+H_t$ where $A$ is a given deterministic Hermitian matrix and $(H_t)_{t\ge 0}$ is a Hermitian Brownian motion. The matrix $A$ is the "external source" that one would…

Probability · Mathematics 2015-01-21 Romain Allez , Joël Bun , Jean-Philippe Bouchaud

For general large non-Hermitian random matrices $X$ and deterministic normal deformations $A$, we prove that the local eigenvalue statistics of $A+X$ close to the critical edge points of its spectrum are universal. This concludes the proof…

Probability · Mathematics 2025-07-14 Giorgio Cipolloni , László Erdős , Hong Chang Ji

We propose a second-order accurate method to estimate the eigenvectors of extremely large matrices thereby addressing a problem of relevance to statisticians working in the analysis of very large datasets. More specifically, we show that…

Numerical Analysis · Mathematics 2010-02-05 Noureddine El Karoui , Alexandre d'Aspremont

We present a new algorithm for solving an eigenvalue problem for a real symmetric matrix which is a rank-one modification of a diagonal matrix. The algorithm computes each eigenvalue and all components of the corresponding eigenvector with…

Numerical Analysis · Mathematics 2015-09-22 Nevena Jakovcevic Stor , Ivan Slapnicar , Jesse L. Barlow

We compute the limiting eigenvalue statistics at the edge of the spectrum of large Hermitian random matrices perturbed by the addition of small rank deterministic matrices. To be more precise, we consider random Hermitian matrices with…

Probability · Mathematics 2007-05-23 Sandrine Péché

We consider $N\times N$ Hermitian random matrices $H$ consisting of blocks of size $M\geq N^{6/7}$. The matrix elements are i.i.d. within the blocks, close to a Gaussian in the four moment matching sense, but their distribution varies from…

Probability · Mathematics 2015-03-27 Zhigang Bao , Laszlo Erdos

Let $W_n= \frac{1}{\sqrt n} M_n$ be a Wigner matrix whose entries have vanishing third moment, normalized so that the spectrum is concentrated in the interval $[-2,2]$. We prove a concentration bound for $N_I = N_I(W_n)$, the number of…

Probability · Mathematics 2013-08-13 Terence Tao , Van Vu

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

Consider a $n\times n$ sparse non-Hermitian random matrix $X_n$ defined as the Hadamard product between a random matrix with centered independent and identically distributed entries and a sparse Bernoulli matrix with success probability…

Probability · Mathematics 2026-02-25 Walid Hachem , Michail Louvaris , Jamal Najim

We prove that a very general class of $N\times N$ Hermitian random band matrices is in the delocalized phase when the band width $W$ exceeds the critical threshold, $W\gg \sqrt{N}$. In this regime, we show that, in the bulk spectrum, the…

Probability · Mathematics 2025-06-10 László Erdős , Volodymyr Riabov

Let $\mathcal A$ be the adjacency matrix of the Erd\H{o}s-R\'{e}nyi directed graph $\mathscr G(N,p)$. We denote the eigenvalues of $\mathcal A$ by $\lambda_1^{\cal A},...,\lambda^{\cal A}_N$, and $|\lambda_1^{\cal A}|=\max_i|\lambda_i^{\cal…

Probability · Mathematics 2025-09-16 Yukun He

We propose a new method for computing the eigenvalue decomposition of a dense real normal matrix $A$ through the decomposition of its skew-symmetric part. The method relies on algorithms that are known to be efficiently implemented, such as…

Numerical Analysis · Mathematics 2026-03-31 Simon Mataigne , Kyle A. Gallivan