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We study the images of the complex Ginibre eigenvalues under the power maps $\pi_M: z \mapsto z^M$, for any integer $M$. We establish the following equality in distribution, $$ {\rm{Gin}}(N)^M \stackrel{d}{=} \bigcup_{k=1}^M {\rm{Gin}}…

Probability · Mathematics 2019-11-05 Guillaume Dubach

We study the overlaps between eigenvectors of nonnormal matrices. They quantify the stability of the spectrum, and characterize the joint eigenvalues increments under Dyson-type dynamics. Well known work by Chalker and Mehlig calculated the…

Probability · Mathematics 2021-02-03 Paul Bourgade , Guillaume Dubach

We study the eigenvalue correlations of random Hermitian $n\times n$ matrices of the form $S=M+\epsilon H$, where $H$ is a GUE matrix, $\epsilon>0$, and $M$ is a positive-definite Hermitian random matrix, independent of $H$, whose…

Mathematical Physics · Physics 2017-08-14 Tom Claeys , Antoine Doeraene

We describe Generalized Hermitian matrices ensemble sometimes called Chiral ensemble. We give global asymptotic of the density of eigenvalues or the statistical density. We will calculate a Laplace transform of such a density for finite…

Probability · Mathematics 2014-09-02 Mohamed Bouali

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

We explore the limiting empirical eigenvalue distributions arising from matrices of the form \[A_{n+1} = \begin{bmatrix} A_n & I\\ I & A_n \end{bmatrix} , \]where $A_0$ is the adjacency matrix of a $k$-regular graph. We find that for…

Discrete Mathematics · Computer Science 2018-07-23 Clark Alexander , Tara Nenninger , Danielle Tucker

Using Grassmann variables and an analogy with two dimensional electrostatics, we obtain the average eigenvalue distribution $\rho(\omega)$ of ensembles of $N \times N$ asymmetrically diluted Hopfield matrices in the limit $N \rightarrow…

Condensed Matter · Physics 2016-08-31 D. A. Stariolo , E. M. F. Curado , F. A. Tamarit

The Ginibre ensemble of complex random Hamiltonian matrices $H$ is considered. Each quantum system described by $H$ is a dissipative system and the eigenenergies $Z_{i}$ of the Hamiltonian are complex-valued random variables. For generic…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

Consider a random matrix of size $N$ as an additive deformation of the complex Ginibre ensemble under a deterministic matrix $X_0$ with a finite rank, independent of $N$. When some eigenvalues of $X_0$ separate from the unit disk, outlier…

Probability · Mathematics 2022-06-30 Dang-Zheng Liu , Lu Zhang

For each $n$, let $A_n=(\sigma_{ij})$ be an $n\times n$ deterministic matrix and let $X_n=(X_{ij})$ be an $n\times n$ random matrix with i.i.d. centered entries of unit variance. We study the asymptotic behavior of the empirical spectral…

Probability · Mathematics 2020-08-03 Nicholas A. Cook , Walid Hachem , Jamal Najim , David Renfrew

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 introduce a new random matrix model called distance covariance matrix in this paper, whose normalized trace is equivalent to the distance covariance. We first derive a deterministic limit for the eigenvalue distribution of the distance…

Statistics Theory · Mathematics 2021-05-18 Weiming Li , Qinwen Wang , Jianfeng Yao

We derive the mean eigenvalue density for symmetric Gaussian random N x N matrices in the limit of large N, with a constraint implying that the row sum of matrix elements should vanish. The result is shown to be equivalent to a result found…

Disordered Systems and Neural Networks · Physics 2009-11-10 J. Staering , B. Mehlig , Yan V. Fyodorov , J. M. Luck

Consider an $N\times N$ hermitian random matrix with independent entries, not necessarily Gaussian, a so called Wigner matrix. It has been conjectured that the local spacing distribution, i.e. the distribution of the distance between…

Mathematical Physics · Physics 2009-10-31 Kurt Johansson

We consider the real eigenvalues of an $(N \times N)$ real elliptic Ginibre matrix whose entries are correlated through a non-Hermiticity parameter $\tau_N\in [0,1]$. In the almost-Hermitian regime where $1-\tau_N=\Theta(N^{-1})$, we obtain…

Probability · Mathematics 2022-03-22 Sung-Soo Byun , Nam-Gyu Kang , Ji Oon Lee , Jinyeop Lee

We investigate singular value statistics for products of independent rectangular complex Ginibre matrices. When the rectangularity parameters of the matrices converge to a common limit in the asymptotic regime, the limiting spectral density…

Probability · Mathematics 2025-10-21 Yandong Gu

We consider eigenvalues of a product of n non-Hermitian, independent random matrices. Each matrix in this product is of size N\times N with independent standard complex Gaussian variables. The eigenvalues of such a product form a…

Mathematical Physics · Physics 2015-06-12 Gernot Akemann , Eugene Strahov

We consider an ensemble of large non-Hermitian random matrices of the form $\hat{H}+i\hat{A}_s$, where $\hat{H}$ and $\hat{A}_s$ are Hermitian statistically independent random $N\times N$ matrices. We demonstrate the existence of a new…

Condensed Matter · Physics 2016-08-31 Yan V. Fyodorov , Boris A. Khoruzhenko , Hans-Juergen Sommers

The distribution of eigenvalues of N times N random matrices in the limit N to infinity is the solution to a variational principle that determines the ground state energy of a confined fluid of classical unit charges. This fact is a…

Mathematical Physics · Physics 2009-10-31 Michael K. -H. Kiessling , Herbert Spohn

The current work applies some recent combinatorial tools due to Jain to control the eigenvalue gaps of a matrix $M_n = M + N_n$ where $M$ is deterministic, symmetric with large operator norm and $N_n$ is a random symmetric matrix with…

Probability · Mathematics 2022-11-02 Kyle Luh , Ryan Vogel , Alan Yu
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