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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

Products and sums of random matrices have seen a rapid development in the past decade due to various analytical techniques available. Two of these are the harmonic analysis approach and the concept of polynomial ensembles. Very recently, it…

Probability · Mathematics 2023-02-02 Mario Kieburg

We consider random hermitian matrices made of complex blocks. The symmetries of these matrices force them to have pairs of opposite real eigenvalues, so that the average density of eigenvalues must vanish at the origin. These densities are…

Condensed Matter · Physics 2009-10-28 E. Brézin , S. Hikami , A. Zee

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 compute exact asymptotic of the statistical density of random matrices belonging to the Generalized Gaussian orthogonal, unitary and symplectic ensembles such that there no eigenvalues in the interval $[\sigma, +\infty[$. In particular,…

Probability · Mathematics 2015-01-27 Mohamed Bouali

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

By using the independence structure of points following a determinantal point process, we study the radii of the spherical ensemble, the truncation of the circular unitary ensemble and the product ensemble with parameter n and k. The…

Probability · Mathematics 2014-11-10 Tiefeng Jiang , Yongcheng Qi

We consider non-gaussian ensembles of random normal matrices with the constraint that the ensembles are invariant under unitary transformations. We show that the level density of eigenvalues exhibits disk to ring transition in the complex…

Mathematical Physics · Physics 2015-07-07 Ravi Prakash , Akhilesh Pandey

We explore the connections between dissipative quantum phase transitions and non-Hermitian random matrix theory. For this, we work in the framework of the dissipative Dicke model which is archetypal of symmetry-breaking phase transitions in…

Quantum Physics · Physics 2022-05-25 Mahaveer Prasad , Hari Kumar Yadalam , Camille Aron , Manas Kulkarni

We formulate gaussian and circular random-matrix models representing a coupled system consisting of an absorbing and an amplifying resonator, which are mutually related by a generalized time-reversal symmetry. Motivated by optical…

Quantum Physics · Physics 2012-12-21 Christopher Birchall , Henning Schomerus

We describe the distribution of the first finite number of eigenvalues in a newly-forming band of the spectrum of the random Hermitean matrix model. The method is rigorously based on the Riemann-Hilbert analysis of the corresponding…

Mathematical Physics · Physics 2016-09-08 M. Bertola , S. Y. Lee

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 introduce a complex-plane generalization of the consecutive level-spacing distribution, used to distinguish regular from chaotic quantum spectra. Our approach features the distribution of complex-valued ratios between nearest- and…

Statistical Mechanics · Physics 2020-07-15 Lucas Sá , Pedro Ribeiro , Tomaž Prosen

We investigate joint spectral characteristics of a family of matrices $\mathcal F $, associated with products in the semigroup generated by $\mathcal F$. In the literature, extremal measures such as the well-known joint spectral radius and…

Dynamical Systems · Mathematics 2026-04-27 Francesco Paolo Maiale , Anastasiia Trofimova , Nicola Guglielmi

This paper describes a set of rational filtering algorithms to compute a few eigenvalues (and associated eigenvectors) of non-Hermitian matrix pencils. Our interest lies in computing eigenvalues located inside a given disk, and the proposed…

Numerical Analysis · Mathematics 2021-03-10 Vassilis Kalantzis , Yuanzhe Xi , Lior Horesh

The distribution of the modulus of the extreme eigenvalues is investigated for the complex Ginibre and complex induced Ginibre ensembles in the limit of large dimensions of random matrices. The limiting distribution of the scaled spectral…

Probability · Mathematics 2026-05-22 Olivia V. Auster

We prove that in dimension one the non-real eigenvalues of the non-Hermitian Anderson (NHA) model with a selfaveraging potential are regularly spaced. The class of selfaveraging potentials which we introduce in this paper is very wide and…

Mathematical Physics · Physics 2009-11-07 I. Ya. Goldsheid , B. A. Khoruzhenko

A result of Zyczkowski and Sommers [J.Phys.A, 33, 2045--2057 (2000)] gives the eigenvalue probability density function for the top N x N sub-block of a Haar distributed matrix from U(N+n). In the case n \ge N, we rederive this result,…

Mathematical Physics · Physics 2015-05-13 Peter J. Forrester , Manjunath Krishnapur

We study the properties of the eigenvalues of real random matrices and their products. It is known that when the matrix elements are Gaussian-distributed independent random variables, the fraction of real eigenvalues tends to unity as the…

Mathematical Physics · Physics 2016-01-13 Sajna Hameed , Kavita Jain , Arul Lakshminarayan

We compute the limiting distributions of the largest eigenvalue of a complex Gaussian sample covariance matrix when both the number of samples and the number of variables in each sample become large. When all but finitely many, say $r$,…

Probability · Mathematics 2007-05-23 Jinho Baik , Gerard Ben Arous , Sandrine Peche