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We solve a family of Gaussian two-matrix models with rectangular Nx(N+v) matrices, having real asymmetric matrix elements and depending on a non-Hermiticity parameter mu. Our model can be thought of as the chiral extension of the real…

高能物理 - 理论 · 物理学 2010-05-07 G. Akemann , M. J. Phillips , H. -J. Sommers

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…

数学物理 · 物理学 2017-08-14 Tom Claeys , Antoine Doeraene

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 $N\times N$…

数学物理 · 物理学 2026-04-28 Margherita Disertori , Yan V. Fyodorov

. We study the statistical properties of the eigenvalues of non-Hermitian operators assoicated with the dissipative complex systems. By considering the Gaussian ensembles of such operators, a hierarchical relation between the correlators is…

统计力学 · 物理学 2024-12-11 Pragya Shukla

We present a five-step method for the calculation of eigenvalue correlation functions for various ensembles of real random matrices, based upon the method of (skew-) orthogonal polynomials. This scheme systematises existing methods and also…

数学物理 · 物理学 2012-02-07 Anthony Mays

Given a joint probability density function of $N$ real random variables, $\{x_j\}_{j=1}^{N},$ obtained from the eigenvector-eigenvalue decomposition of $N\times N$ random matrices, one constructs a random variable, the linear statistics,…

经典分析与常微分方程 · 数学 2019-12-18 Yang Chen , Chao Min

We analyze statistics for eigenvector entries of heavy-tailed random symmetric matrices (also called L\'{e}vy matrices) whose associated eigenvalues are sufficiently small. We show that the limiting law of any such entry is non-Gaussian,…

概率论 · 数学 2020-11-13 Amol Aggarwal , Patrick Lopatto , Jake Marcinek

This is part II of a review relating to the three classes of random non-Hermitian Gaussian matrices introduced by Ginibre in 1965. While part I restricted attention to the GinUE (Ginibre unitary ensemble) case of complex elements, in this…

数学物理 · 物理学 2023-01-13 Sung-Soo Byun , Peter J. Forrester

In the past 20 years, the study of real eigenvalues of non-symmetric real random matrices has seen important progress. Notwithstanding, central questions still remain open, such as the characterization of their asymptotic statistics and the…

数学物理 · 物理学 2016-05-03 Luis Carlos García del Molino , Khashayar Pakdaman , Jonathan Touboul

The eigenvalues of an arbitrary quaternionic matrix have a joint probability distribution function first derived by Ginibre. We show that there exists a mapping of this system onto a fermionic field theory and then use this mapping to…

无序系统与神经网络 · 物理学 2009-10-31 M. B. Hastings

Symmetries associated with complex conjugation and Hermitian conjugation, such as time-reversal symmetry and pseudo-Hermiticity, have great impact on eigenvalue spectra of non-Hermitian random matrices. Here, we show that time-reversal…

无序系统与神经网络 · 物理学 2022-12-21 Zhenyu Xiao , Kohei Kawabata , Xunlong Luo , Tomi Ohtsuki , Ryuichi Shindou

We introduce a powerful analytic method to study the statistics of the number $\mathcal{N}_{\textbf{A}}(\gamma)$ of eigenvalues inside any contour $\gamma \in \mathbb{C}$ for infinitely large non-Hermitian random matrices ${\textbf A}$. Our…

无序系统与神经网络 · 物理学 2021-06-09 Antonio Tonatiúh Ramos Sánchez , Edgar Guzmán-González , Isaac Pérez Castillo , Fernando L. Metz

We suggest a method of analyzing the joint probability density (JPD) ${\cal P}_N(z,{\bf v})$ of an eigenvalue $z$ and the associated right eigenvector ${\bf v}$ (normalized with ${\bf v}^*{\bf v}=1$) for non-Hermitian random matrices of a…

数学物理 · 物理学 2025-09-26 Yan V Fyodorov

The Ginibre unitary ensemble (GinUE) consists of $N \times N$ random matrices with independent complex standard Gaussian entries. This was introduced in 1965 by Ginbre, who showed that the eigenvalues form a determinantal point process with…

数学物理 · 物理学 2023-01-13 Sung-Soo Byun , Peter J. Forrester

The geometry of multi-parameter families of quantum states is important in numerous contexts, including adiabatic or nonadiabatic quantum dynamics, quantum quenches, and the characterization of quantum critical points. Here, we discuss the…

无序系统与神经网络 · 物理学 2021-05-25 Alexander-Georg Penner , Felix von Oppen , Gergely Zarand , Martin R. Zirnbauer

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…

统计力学 · 物理学 2010-10-21 Boris A. Khoruzhenko , Hans-Juergen Sommers , Karol Zyczkowski

The integrable structure of Ginibre's Orthogonal Ensemble of random matrices is looked at through the prism of the probability "p_{n,k}" to find exactly "k" real eigenvalues in the spectrum of an "n" by "n" real asymmetric Gaussian random…

数学物理 · 物理学 2007-05-23 Eugene Kanzieper , Gernot Akemann

We compute the gap probability that a circle of radius r around the origin contains exactly k complex eigenvalues. Four different ensembles of random matrices are considered: the Ginibre ensembles and their chiral complex counterparts, with…

数学物理 · 物理学 2015-05-13 G. Akemann , M. J. Phillips , L. Shifrin

Non-Hermitian PT-symmetric models have been extensively studied in recent years. Following the seminal work that reduced classical random matrix ensembles to a tridiagonal form, several efforts have aimed to generalize this framework to…

统计力学 · 物理学 2025-11-13 Cleverson Andrade Goulart , Gleb Oshanin , Mauricio Porto Pato

Random matrices formed from i.i.d. standard real Gaussian entries have the feature that the expected number of real eigenvalues is non-zero. This property persists for products of such matrices, independently chosen, and moreover it is…

数学物理 · 物理学 2016-08-16 P. J. Forrester , J. R. Ipsen