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In this paper we describe the asymptotic behaviour of the spectral norm of the product of two finite Toeplitz matrices as the matrix dimension goes to the infinity. These Toeplitz matrices are generated by positive functions with…

Spectral Theory · Mathematics 2012-10-30 Philippe Rambour

It is known that the generating function $f$ of a sequence of Toeplitz matrices $\{T_n(f)\}_n$ may not describe the asymptotic distribution of the eigenvalues of $T_n(f)$ if $f$ is not real. In this paper, we assume as a working hypothesis…

Numerical Analysis · Mathematics 2021-08-17 Sven-Erik Ekström

Conditional on the extended Riemann hypothesis, we show that with high probability, the characteristic polynomial of a random symmetric $\{\pm 1\}$-matrix is irreducible. This addresses a question raised by Eberhard in recent work. The main…

Probability · Mathematics 2021-06-09 Asaf Ferber , Vishesh Jain , Ashwin Sah , Mehtaab Sawhney

Let $T_N$ denote an $N\times N$ Toeplitz matrix with finite, $N$ independent symbol ${\bf a}$. For $E_N$ a noise matrix satisfying mild assumptions (ensuring, in particular, that $N^{-1/2}\|E_N\|_{{\rm HS}}\to_{N\to\infty} 0$ at a…

Probability · Mathematics 2019-11-14 Anirban Basak , Elliot Paquette , Ofer Zeitouni

Let $A$ be drawn uniformly at random from the set of all $n\times n$ symmetric matrices with entries in $\{-1,1\}$. We show that \[ \mathbb{P}( \det(A) = 0 ) \leq e^{-cn},\] where $c>0$ is an absolute constant, thereby resolving a…

Probability · Mathematics 2021-06-09 Marcelo Campos , Matthew Jenssen , Marcus Michelen , Julian Sahasrabudhe

Consider an n x n Hermitian random matrix with, above the diagonal, independent entries with alpha-stable symmetric distribution and 0 < alpha < 2. We establish new bounds on the rate of convergence of the empirical spectral distribution of…

Probability · Mathematics 2012-02-01 Charles Bordenave , Alice Guionnet

Random Schroedinger operators with imaginary vector potentials are studied in dimension one. These operators are non-Hermitian and their spectra lie in the complex plane. We consider the eigenvalue problem on finite intervals of length n…

Mathematical Physics · Physics 2007-05-23 I. Ya. Goldsheid , B. A. Khoruzhenko

Normalized eigenvalue counting measure of the sum of two Hermitian (or real symmetric) matrices $A_{n}$ and $B_{n}$ rotated independently with respect to each other by the random unitary (or orthogonal) Haar distributed matrix $U_{n}$ (i.e.…

Mathematical Physics · Physics 2016-08-15 L. Pastur , V. Vasilchuk

The classical infinite divisibility of distributions related to eigenvalues of some random matrix ensembles is investigated. It is proved that the $\beta$-Tracy-Widom distribution, which is the limiting distribution of the largest…

Probability · Mathematics 2016-01-13 J. Armando Domínguez-Molina

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…

Statistical Mechanics · Physics 2010-10-21 Boris A. Khoruzhenko , Hans-Juergen Sommers , Karol Zyczkowski

One of the major themes of random matrix theory is that many asymptotic properties of traditionally studied distributions of random matrices are universal. We probe the edges of universality by studying the spectral properties of random…

Probability · Mathematics 2014-06-30 Tobias Johnson

In this paper we consider ensemble of random matrices $\X_n$ with independent identically distributed vectors $(X_{ij}, X_{ji})_{i \neq j}$ of entries. Under assumption of finite fourth moment of matrix entries it is proved that empirical…

Probability · Mathematics 2012-08-07 Alexey Naumov

We present some results concerning the almost sure behaviour of the operator norm or random Toeplitz matrices, including the law of large numbers for the norm, normalized by its expectation (in the i.i.d. case). As tools we present some…

Probability · Mathematics 2008-03-24 Radosław Adamczak

In this article, we study microscopic properties of a two-dimensional eigenvalue ensemble near a conical singularity arising from insertion of a point charge in the bulk of the support of eigenvalues. In particular, we characterize all…

Mathematical Physics · Physics 2021-09-01 Yacin Ameur , Nam-Gyu Kang , Seong-Mi Seo

In this paper, we study the condition number of a random Toeplitz matrix. Since a Toeplitz matrix is a diagonal constant matrix, its rows or columns cannot be stochastically independent. This situation does not permit us to use the classic…

Probability · Mathematics 2020-09-30 Paulo Manrique--Mirón

We establish the relation between two objects: an integrable system related to Painlev\'e II equation, and the symplectic invariants of a certain plane curve S(TW). This curve describes the average eigenvalue density of a random hermitian…

Exactly Solvable and Integrable Systems · Physics 2010-12-14 Gaetan Borot , Bertrand Eynard

Toeplitz matrices arise naturally in harmonic analysis, operator theory, and numerical analysis. In this note we investigate Toeplitz matrices whose coefficients depend on the matrix size through a scaled kernel $a_k=f(k/n)$. We show that…

Probability · Mathematics 2026-03-25 Jean-Christophe Pain

Asymptotic expansion of the eigenvalues of a Toeplitz matrix with real symbol. This work provides two results obtained as a consequence of an inversion formula for Toeplitz matrices with real symbol. First we obtain an symptotic expression…

Classical Analysis and ODEs · Mathematics 2021-04-27 Philippe Rambour

The largest eigenvalue of a matrix is always larger or equal than its largest diagonal entry. We show that for a large class of random Laplacian matrices, this bound is essentially tight: the largest eigenvalue is, up to lower order terms,…

Probability · Mathematics 2015-07-28 Afonso S. Bandeira

We derive the limiting distribution for the largest eigenvalues of the adjacency matrix for a stochastic blockmodel graph when the number of vertices tends to infinity. We show that, in the limit, these eigenvalues are jointly multivariate…

Machine Learning · Statistics 2018-04-02 Minh Tang
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