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Eigenvalues statistics of various many-body systems have been widely studied using the nearest neighbor spacing distribution under the random matrix theory framework. Here, we numerically analyze eigenvalue ratio statistics of multiplex…

Physics and Society · Physics 2023-05-24 Tanu Raghav , Sarika Jalan

We study the Anderson transition for three-dimensional (3D) $N \times N \times N$ tightly bound cubic lattices where both real and imaginary parts of onsite energies are independent random variables distributed uniformly between $-W/2$ and…

Disordered Systems and Neural Networks · Physics 2020-01-29 Yi Huang , B. I. Shklovskii

We study overlap of two different eigenfunctions as compared with self-overlap in the framework of an infinite-dimensional version of the disordered tight-binding model. Despite a very sparse structure of the eigenstates in the vicinity of…

Mesoscale and Nanoscale Physics · Physics 2009-10-28 Yan V. Fyodorov , Alexander D. Mirlin

Andersons groundbreaking discovery that the presence of stochastic imperfections in a crystal may result in a sudden breakdown of conductivity revolutionized our understanding of disordered media. After stimulating decades of lively…

It has been observed that the statistical distribution of the eigenvalues of random matrices possesses universal properties, independent of the probability law of the stochastic matrix. In this article we find the correlation functions of…

Condensed Matter · Physics 2009-10-30 B. Eynard

We study spectral properties of a non-Hermitian Hamiltonian describing a quantum particle propagating in a random imaginary scalar potential. Cast in the form of an effective field theory, we obtain an analytical expression for the ensemble…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. V. Izyumov , B. D. Simons

We explore the concept of eigenvalue avoidance, which is well understood for real symmetric and Hermitian matrices, for other classes of structured matrices. We adopt a differential geometric perspective and study the generic behaviour of…

Spectral Theory · Mathematics 2022-09-29 Yuji Nakatsukasa , Vanni Noferini

Recently, an analytic method was developed to study in the large $N$ limit non-hermitean random matrices that are drawn from a large class of circularly symmetric non-Gaussian probability distributions, thus extending the existing Gaussian…

Disordered Systems and Neural Networks · Physics 2015-06-24 Joshua Feinberg , R. Scalettar , A. Zee

We consider diagonal disordered one-dimensional Anderson models with an underlying periodicity. We assume the simplest periodicity, i.e., we have essentially two lattices, one that is composed of the random potentials and the other of…

Disordered Systems and Neural Networks · Physics 2009-10-30 Michael Hilke

Extremal spacings between eigenvalues of random unitary matrices of size N pertaining to circular ensembles are investigated. Explicit probability distributions for the minimal spacing for various ensembles are derived for N = 4. We study…

Mathematical Physics · Physics 2013-11-13 Marek Smaczynski , Tomasz Tkocz , Marek Kus , Karol Zyczkowski

We propose a technique for calculating and understanding the eigenvalue distribution of sums of random matrices from the known distribution of the summands. The exact problem is formidably hard. One extreme approximation to the true density…

Quantum Physics · Physics 2017-10-27 Ramis Movassagh , Alan Edelman

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

We present the first rigorous result on Anderson localization for interacting systems of quantum particles subject to a deterministic (e.g., almost periodic) disordered external potential. For a particular class of deterministic, fermionic,…

Mathematical Physics · Physics 2014-02-28 Victor Chulaevsky

We consider $N\times N$ Hermitian random matrices with i.i.d. entries. The matrix is normalized so that the average spacing between consecutive eigenvalues is of order $1/N$. We study the connection between eigenvalue statistics on…

Mathematical Physics · Physics 2009-06-25 László Erdős , Benjamin Schlein , Horng-Tzer Yau

This work is focused on the local eigenvalue statistics for the Anderson tight binding model with non-rank-one perturbations over the canopy tree, at large disorder. On the Hilbert space $\ell^2(\mathcal{C})$, where $ \mathcal{C} $ is the…

Spectral Theory · Mathematics 2017-06-09 Narayanan P. A.

The ordered eigenvalues define a Lipschitz map on the real vector space of Hermitian $d \times d$ matrices. We prove that this map acts continuously, but not uniformly continuously, by superposition on the Sobolev spaces $W^{1,q}$, for all…

Functional Analysis · Mathematics 2026-03-25 Adam Parusiński , Armin Rainer

Following our recent letter, we study in detail an entry-wise diffusion of non-hermitian complex matrices. We obtain an exact partial differential equation (valid for any matrix size $N$ and arbitrary initial conditions) for evolution of…

Mathematical Physics · Physics 2015-10-20 Zdzislaw Burda , Jacek Grela , Maciej A. Nowak , Wojciech Tarnowski , Piotr Warchoł

We derive a sufficient condition for a Hermitian $N \times N$ matrix $A$ to have at least $m$ eigenvalues (counting multiplicities) in the interval $(-\epsilon, \epsilon)$. This condition is expressed in terms of the existence of a…

Mathematical Physics · Physics 2014-03-12 Alexander Elgart , Daniel Schmidt

We study random points on the real line generated by the eigenvalues in unitary invariant random matrix ensembles or by more general repulsive particle systems. As the number of points tends to infinity, we prove convergence of the…

Probability · Mathematics 2015-11-11 Kristina Schubert , Martin Venker

Improving upon results of Rudelson and Vershynin, we establish delocalization bounds for eigenvectors of independent-entry random matrices. In particular, we show that with high probability every eigenvector is delocalized, meaning any…

Probability · Mathematics 2019-02-01 Kyle Luh , Sean O'Rourke
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