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Statistical properties of eigenvectors in non-Hermitian random matrix ensembles are discussed, with an emphasis on correlations between left and right eigenvectors. Two approaches are described. One is an exact calculation for Ginibre's…

Disordered Systems and Neural Networks · Physics 2015-06-25 B. Mehlig , J. T. Chalker

The time evolution of spatial fluctuations in inhomogeneous d-dimensional biological systems is analyzed. A single species continuous growth model, in which the population disperses via diffusion and convection is considered.…

Disordered Systems and Neural Networks · Physics 2009-10-30 David R. Nelson , Nadav M. Shnerb

We study the eigenvalues and the eigenvectors of $N\times N$ structured random matrices of the form $H = W\tilde{H}W+D$ with diagonal matrices $D$ and $W$ and $\tilde{H}$ from the Gaussian Unitary Ensemble. Using the supersymmetry technique…

Mathematical Physics · Physics 2018-08-20 Kevin Truong , Alexander Ossipov

Non-Hermitian random matrices provide a useful framework for understanding universal characteristics of dissipative quantum chaotic systems with loss or gain. We consider a model of two such system represented by two independent $N\times N$…

Mathematical Physics · Physics 2026-04-28 Margherita Disertori , Yan V. Fyodorov

We study the statistics of the local resolvent and non-ergodic properties of eigenvectors for a generalised Rosenzweig-Porter $N\times N$ random matrix model, undergoing two transitions separated by a delocalised non-ergodic phase.…

Disordered Systems and Neural Networks · Physics 2016-09-29 Davide Facoetti , Pierpaolo Vivo , Giulio Biroli

Consider a Hermitian matrix model under an external potential with spiked external source. When the external source is of rank one, we compute the limiting distribution of the largest eigenvalue for general, regular, analytic potential for…

Mathematical Physics · Physics 2010-12-21 Jinho Baik , Dong Wang

We consider large non-Hermitian $N\times N$ matrices with an additive independent, identically distributed (i.i.d.) noise for each matrix elements. We show that already a small noise of variance $1/N$ completely thermalises the bulk…

Probability · Mathematics 2024-01-12 Giorgio Cipolloni , László Erdős , Joscha Henheik , Dominik Schröder

We prove localization with high probability on sets of size of order $N/\log N$ for the eigenvectors of non-Hermitian finitely banded $N\times N$ Toeplitz matrices $P_N$ subject to small random perturbations, in a very general setting. As…

Spectral Theory · Mathematics 2023-08-02 Anirban Basak , Martin Vogel , Ofer Zeitouni

We consider a constant-size subset of left and right eigenvectors of an $N\times N$ i.i.d. complex non-Hermitian matrix associated with the eigenvalues with pairwise distances at least $N^{-\frac12+\epsilon}$. We show that arbitrary…

Probability · Mathematics 2024-03-29 Sofiia Dubova , Kevin Yang , Horng-Tzer Yau , Jun Yin

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

The eigenvalues and eigenvectors of nonnormal matrices can be unstable under perturbations of their entries. This renders an obstacle to the analysis of numerical algorithms for non-Hermitian eigenvalue problems. A recent technique to…

Probability · Mathematics 2026-04-14 Rikhav Shah , Nikhil Srivastava , Edward Zeng

Consider a $N\times n$ matrix $\Sigma_n=\frac{1}{\sqrt{n}}R_n^{1/2}X_n$, where $R_n$ is a nonnegative definite Hermitian matrix and $X_n$ is a random matrix with i.i.d. real or complex standardized entries. The fluctuations of the linear…

Probability · Mathematics 2016-06-29 Jamal Najim , Jianfeng Yao

The perturbed GUE corners ensemble is the joint distribution of eigenvalues of all principal submatrices of a matrix $G+\mathrm{diag}(\mathbf{a})$, where $G$ is the random matrix from the Gaussian Unitary Ensemble (GUE), and…

Probability · Mathematics 2021-07-30 Leonid Petrov , Mikhail Tikhonov

As an extension of the theory of Dyson's Brownian motion models for the standard Gaussian random-matrix ensembles, we report a systematic study of hermitian matrix-valued processes and their eigenvalue processes associated with the chiral…

Mathematical Physics · Physics 2007-05-23 Makoto Katori , Hideki Tanemura

We study the universality of spectral statistics of large random matrices. We consider $N\times N$ symmetric, hermitian or quaternion self-dual random matrices with independent, identically distributed entries (Wigner matrices) where the…

Mathematical Physics · Physics 2015-05-18 Laszlo Erdos

We consider a sparse i.i.d.\ non-Hermitian random matrix model $X_n$ (with sparsity parameter $K_n$) and a deterministic finite-rank perturbation $E_n$. Assuming biorthogonality for $E_n$ and a growth condition on $K_n$, we outline a…

Probability · Mathematics 2026-03-05 Miltiadis Galanis , Michail Louvaris

We consider the random matrix ensemble with an external source \[ \frac{1}{Z_n} e^{-n \Tr({1/2}M^2 -AM)} dM \] defined on $n\times n$ Hermitian matrices, where $A$ is a diagonal matrix with only two eigenvalues $\pm a$ of equal…

Mathematical Physics · Physics 2009-11-10 Pavel M. Bleher , Arno B. J. Kuijlaars

We investigate the overlap matrix between the eigenvectors of a Wigner matrix $H_{N+K}$ of size $(N+K)\times(N+K)$ and those of its principal minor $H_N$ of size $N\times N$, for both the real symmetric ($\beta=1$) and complex Hermitian…

Probability · Mathematics 2025-11-18 Antonin Barbe , Benjamin De Bruyne , Romain Allez

We study joint eigenvector distributions for large symmetric matrices in the presence of weak noise. Our main result asserts that every submatrix in the orthogonal matrix of eigenvectors converges to a multidimensional Gaussian…

Probability · Mathematics 2020-05-19 Jake Marcinek , Horng-Tzer Yau

Consider sample covariance matrices of the form $Q:=\Sigma^{1/2} X X^\top \Sigma^{1/2}$, where $X=(x_{ij})$ is an $n\times N$ random matrix whose entries are independent random variables with mean zero and variance $N^{-1}$, and $\Sigma$ is…

Probability · Mathematics 2023-06-09 Fan Yang