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A remarkable property of Hermitian ensembles is their universal behavior, that is, once properly rescaled the eigenvalue statistics does not depend on particularities of the ensemble. Recently, normal matrix ensembles have attracted…

Mathematical Physics · Physics 2009-09-21 Alexei M. Veneziani , Tiago Pereira , Domingos H. U. Marchetti

We study the correlations between eigenvalues of the large random matrices by a renormalization group approach. The results strongly support the universality of the correlations proposed by Br\'ezin and Zee. Then we apply the results to the…

Condensed Matter · Physics 2009-10-22 Y. Morita , Y. Hatsugai , M. Kohmoto

It was shown roughly thirty years ago that the density correlations of eigenvalues of large random matrices display a universal form, independent of most of the details of the distribution of the random matrix itself. We show that when the…

Statistical Mechanics · Physics 2025-11-11 Kirone Mallick , Gabriel Téllez , Frédéric van Wijland

We calculate smoothed correlators for a large random matrix model with a potential containing products of two traces $\tr W_1(M) \cdot \tr W_2(M)$ in addition to a single trace $\tr V(M)$. Connected correlation function of density…

Disordered Systems and Neural Networks · Physics 2009-10-30 Satoshi Iso , Andrew Kavalov

{Recently, we found that the correlation between the eigenvalues of random hermitean matrices exhibits universal behavior. Here we study this universal behavior and develop a diagrammatic approach which enables us to extend our previous…

Condensed Matter · Physics 2009-10-22 E. Brezin , A. Zee

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 prove that for Gaussian random normal matrices the correlation function has universal behavior. Using the technique of orthogonal polynomials and identities similar to the Christoffel-Darboux formula, we find that in the limit, as the…

Mathematical Physics · Physics 2013-12-03 Roman Riser

Signatures of universality are detected by comparing individual eigenvalue distributions and level spacings from financial covariance matrices to random matrix predictions. A chopping procedure is devised in order to produce a statistical…

Statistical Finance · Quantitative Finance 2015-05-13 Gernot Akemann , Jonit Fischmann , Pierpaolo Vivo

We consider large random matrices with a general slowly decaying correlation among its entries. We prove universality of the local eigenvalue statistics and optimal local laws for the resolvent away from the spectral edges, generalizing the…

Probability · Mathematics 2020-06-01 László Erdős , Torben Krüger , Dominik Schröder

We show that eigenvalue correlations in unitary-invariant ensembles of large random matrices adhere to novel universal laws that only depend on a multicriticality of the bulk density of states near the soft edge of the spectrum. Our…

chao-dyn · Physics 2009-10-30 E. Kanzieper , V. Freilikher

We study the universal properties of distributions of eigenvalues of random matrices in the large $N$ limit. The distributions fall in universality classes characterized entirely by the support of the spectral density.

Condensed Matter · Physics 2009-10-28 J. Ambjorn , G. Akemann

Properties of universality have essential relevance for the theory of random matrices usually called the Wigner ensemble. The issue was analysed up to recent years with detailed and relevant results. We present a slightly different view and…

Mathematical Physics · Physics 2025-05-07 Giovanni M. Cicuta , Mario Pernici

Eigenvalue correlations of random matrix ensembles as a function of an external perturbation are investigated vis the Dyson Brownian Motion Model in the situation where the level density has a hard edge singularity. By solving a linearized…

Condensed Matter · Physics 2009-10-22 Kasper Eriksen , Yang Chen

We consider two non-Gaussian ensembles of large Hermitian random matrices with strong level confinement and show that near the soft edge of the spectrum both scaled density of states and eigenvalue correlations follow so-called Airy laws…

chao-dyn · Physics 2009-10-30 E. Kanzieper , V. Freilikher

Spectral correlations in unitary invariant, non-Gaussian ensembles of large random matrices possessing an eigenvalue gap are studied within the framework of the orthogonal polynomial technique. Both local and global characteristics of…

Statistical Mechanics · Physics 2009-10-30 E. Kanzieper , V. Freilikher

We extend a recent theory of parametric correlations in the spectrum of random matrices to study the response to an external perturbation of eigenvalues near the soft edge of the support. We demonstrate by explicit non-perturbative…

Condensed Matter · Physics 2009-10-22 A. M. S. Macedo

We use methods of random matrix theory to analyze the cross-correlation matrix C of price changes of the largest 1000 US stocks for the 2-year period 1994-95. We find that the statistics of most of the eigenvalues in the spectrum of C agree…

Random contractions (sub-unitary random matrices) appear naturally when considering quantized chaotic maps within a general theory of open linear stationary systems with discrete time. We analyze statistical properties of complex…

Chaotic Dynamics · Physics 2009-10-31 Yan V. Fyodorov , H. -J. Sommmers

We apply random matrix theory to complex networks. We show that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world and random networks follow…

Adaptation and Self-Organizing Systems · Physics 2016-09-08 Jayendra N. Bandyopadhyay , Sarika Jalan

Random matrix theory allows one to deduce the eigenvalue spectrum of a large matrix given only statistical information about its elements. Such results provide insight into what factors contribute to the stability of complex dynamical…

Disordered Systems and Neural Networks · Physics 2025-01-30 Joseph W. Baron , Thomas Jun Jewell , Christopher Ryder , Tobias Galla
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