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Analyzing the spectral behavior of random matrices with dependency among entries is a challenging problem. The adjacency matrix of the random $d$-regular graph is a prominent example that has attracted immense interest. A crucial spectral…

Probability · Mathematics 2023-06-07 Jaehun Lee , Kyeongsik Nam

We establish bounds on the spectral radii for a large class of sparse random matrices, which includes the adjacency matrices of inhomogeneous Erd\H{o}s-R\'enyi graphs. Our error bounds are sharp for a large class of sparse random matrices.…

Probability · Mathematics 2021-01-25 Florent Benaych-Georges , Charles Bordenave , Antti Knowles

In this note, we give a precise description of the limiting empirical spectral distribution (ESD) for the non-backtracking matrices for an Erd\H{o}s-R\'{e}nyi graph assuming $np/\log n$ tends to infinity. We show that derandomizing part of…

Probability · Mathematics 2024-01-01 Ke Wang , Philip Matchett Wood

We study the spectrum of a random multigraph with a degree sequence ${\bf D}_n=(D_i)_{i=1}^n$ and average degree $1 \ll \omega_n \ll n$, generated by the configuration model, and also the spectrum of the analogous random simple graph. We…

Probability · Mathematics 2020-05-15 Amir Dembo , Eyal Lubetzky , Yumeng Zhang

We consider a class of sparse random matrices, which includes the adjacency matrix of Erd\H{o}s-R\'enyi graph ${\bf G}(N,p)$. For $N^{-1+o(1)}\leq p\leq 1/2$, we show that the non-trivial edge eigenvectors are asymptotically jointly normal.…

Probability · Mathematics 2026-02-24 Yukun He , Jiaoyang Huang , Chen Wang

A large i.i.d. random matrix with deterministic low-rank perturbation has been extensively studied, particularly in the aspects of the ESD (Empirical Spectral Distribution) and the outliers of eigenvalues. In this work, we investigate the…

Information Theory · Computer Science 2025-06-24 Kun Chen , Zhihua Zhang

Spectral properties of random matrices play an important role in statistics, machine learning, communications, and many other areas. Engaging results regarding the convergence of the empirical spectral distribution (ESD) and the…

Statistics Theory · Mathematics 2025-07-08 Zeyan Zhuang , Xin Zhang , Dongfang Xu , Shenghui Song

We consider the ensemble of adjacency matrices of Erd{\H o}s-R\'enyi random graphs, i.e.\ graphs on $N$ vertices where every edge is chosen independently and with probability $p \equiv p(N)$. We rescale the matrix so that its bulk…

Probability · Mathematics 2015-05-27 Laszlo Erdos , Antti Knowles , Horng-Tzer Yau , Jun Yin

In this work, we study some statistical properties of the extreme eigenstates of the randomly-weighted adjacency matrices of random graphs. We focus on two random graph models: Erd\H{o}s-R\'{e}nyi (ER) graphs and random geometric graphs…

Disordered Systems and Neural Networks · Physics 2025-06-17 C. T Martínez Martínez , J. A. Méndez Bermúdez

In this paper, we study the convergence rates of empirical spectral distribution of large dimensional quaternion sample covariance matrix. Assume that the entries of $\mathbf X_n$ ($p\times n$) are independent quaternion random variables…

Probability · Mathematics 2013-12-30 Huiqin LI , Zhidong Bai

The eigenvector empirical spectral distribution (VESD) is a useful tool in studying the limiting behavior of eigenvalues and eigenvectors of covariance matrices. In this paper, we study the convergence rate of the VESD of sample covariance…

Probability · Mathematics 2020-08-19 Haokai Xi , Fan Yang , Jun Yin

We analyse the $\ell^2(\pi)$-convergence rate of irreducible and aperiodic Markov chains with $N$-band transition probability matrix $P$ and with invariant distribution $\pi$. This analysis is heavily based on: first the study of the…

Probability · Mathematics 2015-11-06 Loïc Hervé , James Ledoux

Consider an $n \times p$ data matrix $X$ whose rows are independently sampled from a population with covariance $\Sigma$. When $n,p$ are both large, the eigenvalues of the sample covariance matrix are substantially different from those of…

Numerical Analysis · Mathematics 2017-10-03 Edgar Dobriban

Let $\mathcal A$ be the adjacency matrix of a random $d$-regular graph on $N$ vertices, and we denote its eigenvalues by $\lambda_1\geq \lambda_2\cdots \geq \lambda_{N}$. For $N^{2/3}\ll d\leq N/2$, we prove optimal rigidity estimates of…

Probability · Mathematics 2024-08-01 Yukun He

We study a class of random matrices that appear in several communication and signal processing applications, and whose asymptotic eigenvalue distribution is closely related to the reconstruction error of an irregularly sampled bandlimited…

Information Theory · Computer Science 2008-06-24 Alessandro Nordio , Carla-Fabiana Chiasserini , Emanuele Viterbo

We analyse the $\ell^2(\pi)$-convergence rate of irreducible and aperiodic Markov chains with $N$-band transition probability matrix $P$ and with invariant distribution $\pi$. This analysis is heavily based on: first the study of the…

Probability · Mathematics 2016-01-15 Loïc Hervé , James Ledoux

The article considers an inhomogeneous Erd\H{o}s-R\"enyi random graph on $\{1,\ldots, N\}$, where an edge is placed between vertices $i$ and $j$ with probability $\varepsilon_N f(i/N,j/N)$, for $i\le j$, the choice being made independent…

Probability · Mathematics 2024-02-28 Arijit Chakrabarty , Sukrit Chakraborty , Rajat Subhra Hazra

Consider the normalized adjacency matrices of random $d$-regular graphs on $N$ vertices with fixed degree $d\geq3$. We prove that, with probability $1-N^{-1+{\varepsilon}}$ for any ${\varepsilon} >0$, the following two properties hold as $N…

Probability · Mathematics 2025-02-04 Jiaoyang Huang , Horng-Tzer Yau

We define the empirical spectral distribution (ESD) of a random matrix polynomial with invertible leading coefficient, and we study it for complex $n \times n$ Gaussian monic matrix polynomials of degree $k$. We obtain exact formulae for…

Probability · Mathematics 2022-07-20 Giovanni Barbarino , Vanni Noferini

The distribution $\mathsf{RGG}(n,\mathbb{S}^{d-1},p)$ is formed by sampling independent vectors $\{V_i\}_{i = 1}^n$ uniformly on $\mathbb{S}^{d-1}$ and placing an edge between pairs of vertices $i$ and $j$ for which $\langle V_i,V_j\rangle…

Probability · Mathematics 2024-08-05 Kiril Bangachev , Guy Bresler
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