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We estimate the size of the spectral gap at zero for some Hermitian block matrices. Included are quasi-definite matrices, quasi-semidefinite matrices (the closure of the set of the quasi-definite matrices) and some related block matrices…

Spectral Theory · Mathematics 2016-01-15 Ivan Veselic , Kresimir Veselic

In 1972 H. L. Montgomery announced a remarkable connection between the distribution of the zeros of the Riemann zeta-function and the distribution of eigenvalues of large random Hermitian matrices. Since then a number of startling…

Number Theory · Mathematics 2009-09-25 J. Brian Conrey

These expository notes are centered around the circular law theorem, which states that the empirical spectral distribution of a nxn random matrix with i.i.d. entries of variance 1/n tends to the uniform law on the unit disc of the complex…

Probability · Mathematics 2012-03-14 Charles Bordenave , Djalil Chafai

We obtain variance inequalities for quadratic forms of weakly dependent random variables with bounded fourth moments. We also discuss two application. Namely, we use these inequalities for deriving the limiting spectral distribution of a…

Probability · Mathematics 2016-03-07 Pavel Yaskov

Recently much effort has been made towards the introduction of non-Hermitian random matrix models respecting $PT$-symmetry. Here we show that there is a one-to-one correspondence between complex $PT$-symmetric matrices and split-complex and…

Mathematical Physics · Physics 2015-09-17 Eva-Maria Graefe , Steve Mudute-Ndumbe , Matthew Taylor

This work is concerned with finite range bounds on the variance of individual eigenvalues of Wigner random matrices, in the bulk and at the edge of the spectrum, as well as for some intermediate eigenvalues. Relying on the GUE example,…

Probability · Mathematics 2012-07-06 Sandrine Dallaporta

In this paper, a sum rule means a relationship between a functional defined on a subset of all probability measures on $\mathbb{R}$ involving the reverse Kullback-Leibler divergence with respect to a particular distribution and recursion…

Probability · Mathematics 2015-06-23 Fabrice Gamboa , Jan Nagel , Alain Rouault

We establish sharp estimates that adapt the polynomial method to arbitrary varieties. These include a partitioning theorem, estimates on polynomials vanishing on fixed sets and bounds for the number of connected components of real algebraic…

Algebraic Geometry · Mathematics 2020-06-15 Miguel N. Walsh

We analyze the spectral distribution of symmetric random matrices with correlated entries. While we assume that the diagonals of these random matrices are stochastically independent, the elements of the diagonals are taken to be correlated.…

Probability · Mathematics 2012-05-31 Olga Friesen , Matthias Löwe

Let $A \in \mathbb{R}^{n \times (n - d)}$ be a random matrix with independent uniformly anti-concentrated entries satisfying $\mathbb{E}\lvert A\rvert_{HS}^2 \leq Kn(n-d)$ and let $H$ be the subspace spanned by the columns of $A$. Let $X…

Probability · Mathematics 2025-07-28 Manuel Fernandez

We consider the joint distribution of real and imaginary parts of eigenvalues of random matrices with independent entries with mean zero and unit variance. We prove the convergence of this distribution to the uniform distribution on the…

Probability · Mathematics 2010-10-19 Friedrich Götze , Alexander Tikhomirov

In this paper, using techniques developed in our earlier works on the theory of mod-Gaussian convergence, we prove precise moderate and large deviation results for the logarithm of the characteristic polynomial of a random unitary matrix.…

Probability · Mathematics 2022-02-18 Pierre-Loïc Méliot , Ashkan Nikeghbali

By extending the methods in Peligrad et al. (2014a, b), we establish exact moderate and large deviation asymptotics for linear random fields with independent innovations. These results are useful for studying nonparametric regression with…

Probability · Mathematics 2021-07-01 Hailin Sang , Yimin Xiao

In this paper, it is shown that with large probability, the spectral radius of a large non-Hermitian random matrix with a general variance profile does not exceed the square root of the spectral radius of the variance profile matrix. A…

Probability · Mathematics 2025-10-10 Walid Hachem , Michail Louvaris

Starting with the large deviation principle (LDP) for the Erd\H{o}s-R\'enyi binomial random graph $\mathcal{G}(n,p)$ (edge indicators are i.i.d.), due to Chatterjee and Varadhan (2011), we derive the LDP for the uniform random graph…

Probability · Mathematics 2018-05-01 Amir Dembo , Eyal Lubetzky

We consider a random matrix whose entries are independent Gaussian variables taking values in the field of quaternions with variance $1/n$. Using logarithmic potential theory, we prove the almost sure convergence, as the dimension $n$ goes…

Probability · Mathematics 2011-09-05 Florent Benaych-Georges , Francois Chapon

We investigate the behavior of fractional derivatives of polynomials. In particular, we consider the locations and the asymptotic behaviour of their zeros and give bounds for their Mahler measure.

General Mathematics · Mathematics 2024-07-22 Torre Caparatta , Sebastian Pauli , Filip Saidak

Consider Ginibre's ensemble of $N \times N$ non-Hermitian random matrices in which all entries are independent complex Gaussians of mean zero and variance $\frac{1}{N}$. As $N \uparrow \infty$ the normalized counting measure of the…

Probability · Mathematics 2007-05-23 Brian Rider

We establish large deviation formulas for linear statistics on the $N$ transmission eigenvalues $\{T_i\}$ of a chaotic cavity, in the framework of Random Matrix Theory. Given any linear statistics of interest $A=\sum_{i=1}^N a(T_i)$, the…

Mesoscale and Nanoscale Physics · Physics 2015-05-14 Pierpaolo Vivo , Satya N. Majumdar , Oriol Bohigas

This paper studies the spectral behavior of large dimensional Chatterjee's rank correlation matrix when observations are independent draws from a high-dimensional random vector with independent continuous components. We show that the…

Statistics Theory · Mathematics 2025-10-09 Zhaorui Dong , Fang Han , Jianfeng Yao