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In this paper, we study the largest eigenvalues of sample covariance matrices with elliptically distributed data. We consider the sample covariance matrix $Q=YY^*,$ where the data matrix $Y \in \mathbb{R}^{p \times n}$ contains i.i.d.…

Probability · Mathematics 2023-04-24 Xiucai Ding , Jiahui Xie

Let $X$ be an $M\times N$ random matrix consisting of independent $M$-variate elliptically distributed column vectors $\mathbf{x}_{1},\dots,\mathbf{x}_{N}$ with general population covariance matrix $\Sigma$. In the literature, the quantity…

Statistics Theory · Mathematics 2021-06-03 Jun Wen , Jiahui Xie , Long Yu , Wang Zhou

We consider $N\times N$ Hermitian random matrices with independent identical distributed entries. The matrix is normalized so that the average spacing between consecutive eigenvalues is of order 1/N. Under suitable assumptions on the…

Mathematical Physics · Physics 2009-11-13 Laszlo Erdos , Benjamin Schlein , Horng-Tzer Yau

Let the sample correlation matrix be $W=YY^T$, where $Y=(y_{ij})_{p,n}$ with $y_{ij}=x_{ij}/\sqrt{\sum_{j=1}^nx_{ij}^2}$. We assume $\{x_{ij}: 1\leq i\leq p, 1\leq j\leq n\}$ to be a collection of independent symmetric distributed random…

Statistics Theory · Mathematics 2011-11-01 Zhigang Bao , Guangming Pan , Wang Zhou

Let $\bY =\bR+\bX$ be an $M\times N$ matrix, where $\bR$ is a rectangular diagonal matrix and $\bX$ consists of $i.i.d.$ entries. This is a signal-plus-noise type model. Its signal matrix could be full rank, which is rarely studied in…

Statistics Theory · Mathematics 2020-09-28 Zhixiang Zhang , Guangming Pan

For random $d$-regular graphs on $N$ vertices with $1 \ll d \ll N^{2/3}$, we develop a $d^{-1/2}$ expansion of the local eigenvalue distribution about the Kesten-McKay law up to order $d^{-3}$. This result is valid up to the edge of the…

Probability · Mathematics 2021-07-06 Roland Bauerschmidt , Jiaoyang Huang , Antti Knowles , Horng-Tzer Yau

We consider the statistics of extreme eigenvalues of random $d$-regular graphs, with $N^{\mathfrak c}\leq d\leq N^{1/3-{\mathfrak c}}$ for arbitrarily small ${\mathfrak c}>0$. We prove that in this regime, the fluctuations of extreme…

Probability · Mathematics 2023-06-12 Jiaoyang Huang , Horng-Tzer Yau

The spectral moments of ensembles of sparse random block matrices are analytically evaluated in the limit of large order. The structure of the sparse matrix corresponds to the Erd\"os-Renyi random graph. The blocks are i.i.d. random…

Mathematical Physics · Physics 2022-04-13 Giovanni M. Cicuta , Mario Pernici

The classical setting of community detection consists of networks exhibiting a clustered structure. To more accurately model real systems we consider a class of networks (i) whose edges may carry labels and (ii) which may lack a clustered…

Statistics Theory · Mathematics 2014-06-27 Jiaming Xu , Laurent Massoulié , Marc Lelarge

The ground-state energy E_0 of a spin glass is an example of an extreme statistic. We consider the large deviations of this energy for a variety of models when the number of spins N goes to infinity. In most cases, the behavior can be…

Disordered Systems and Neural Networks · Physics 2009-11-10 A. Andreanov , F. Barbieri , O. C. Martin

We prove a local law for the adjacency matrix of the Erd\H{o}s-R\'enyi graph $G(N, p)$ in the supercritical regime $ pN \geq C\log N$ where $G(N,p)$ has with high probability no isolated vertices. In the same regime, we also prove the…

Probability · Mathematics 2019-01-16 Yukun He , Antti Knowles , Matteo Marcozzi

Sparse graphs with bounded average degree form a rich class of discrete structures where local geometry strongly influences global behavior. The Benjamini-Schramm (BS) convergence offers a natural framework to describe their asymptotic…

Probability · Mathematics 2025-10-14 Charles Bordenave

Random spatial networks-that is, graphs whose connectivity is governed by geometric proximity-have emerged as fundamental models for systems constrained by an underlying spatial structure. A prototypical example is the random geometric…

Probability · Mathematics 2026-02-20 Christian Hirsch , Kyeongsik Nam , Moritz Otto

Although the spectra of random networks have been studied for a long time, the influence of network topology on the dense limit of network spectra remains poorly understood. By considering the configuration model of networks with four…

Disordered Systems and Neural Networks · Physics 2020-10-23 Fernando L. Metz , Jeferson D. Silva

We study the asymptotic behavior of eigenvalues of large complex correlated Wishart matrices at the edges of the limiting spectrum. In this setting, the support of the limiting eigenvalue distribution may have several connected components.…

Probability · Mathematics 2016-06-07 Walid Hachem , Adrien Hardy , Jamal Najim

We show that the fluctuations of the largest eigenvalue of any generalized Wigner matrix $H$ converge to the Tracy-Widom laws at a rate nearly $O(N^{-1/3})$, as the matrix dimension $N$ tends to infinity. We allow the variances of the…

Probability · Mathematics 2022-08-04 Kevin Schnelli , Yuanyuan Xu

We discuss the limiting spectral density of real symmetric random matrices. Other than in standard random matrix theory the upper diagonal entries are not assumed to be independent, but we will fill them with the entries of a stochastic…

Probability · Mathematics 2015-12-09 Matthias Löwe , Kristina Schubert

We consider extremal eigenvalues of sparse random matrices, a class of random matrices including the adjacency matrices of Erd\H{o}s-R\'{e}nyi graphs $\mathcal{G}(N,p)$. Recently, it was shown that the leading order fluctuations of extremal…

Probability · Mathematics 2023-06-08 Jaehun Lee

We analyze the performance of spectral clustering for community extraction in stochastic block models. We show that, under mild conditions, spectral clustering applied to the adjacency matrix of the network can consistently recover hidden…

Statistics Theory · Mathematics 2014-12-31 Jing Lei , Alessandro Rinaldo

We consider deformed sparse random matrices of the form $H= W+ \lambda V$, where $W$ is a real symmetric sparse random matrix, $V$ is a random or deterministic, real, diagonal matrix whose entries are independent of $W$, and $\lambda = O(1)…

Probability · Mathematics 2026-04-30 Ji Oon Lee , Inyoung Yeo