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The spectral and localization properties of heterogeneous random graphs are determined by the resolvent distributional equations, which have so far resisted an analytic treatment. We solve analytically the resolvent equations of random…

Disordered Systems and Neural Networks · Physics 2022-12-27 Jeferson D. Silva , Fernando L. Metz

For a large class of symmetric random matrices with correlated entries, selected from stationary random fields of centered and square integrable variables, we show that the limiting distribution of eigenvalue counting measure always exists…

Probability · Mathematics 2016-03-08 Costel Peligrad , Magda Peligrad

We present a generalization of the method of the local relaxation flow to establish the universality of local spectral statistics of a broad class of large random matrices. We show that the local distribution of the eigenvalues coincides…

Mathematical Physics · Physics 2010-08-20 Laszlo Erdos , Benjamin Schlein , Horng-Tzer Yau , Jun Yin

Within a random-matrix-theory approach, we use the nearest-neighbor energy level spacing distribution $P(s)$ and the entropic eigenfunction localization length $\ell$ to study spectral and eigenfunction properties (of adjacency matrices) of…

Physics and Society · Physics 2017-08-14 L. Alonso , J. A. Mendez-Bermudez , A. Gonzalez-Melendrez , Yamir Moreno

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 consider spectral properties of sparse sample covariance matrices, which includes biadjacency matrices of the bipartite Erd\H{o}s-R\'enyi graph model. We prove a local law for the eigenvalue density up to the upper spectral edge. Under a…

Probability · Mathematics 2018-08-06 Jong Yun Hwang , Ji Oon Lee , Kevin Schnelli

In Chung-Lu random graphs, a classic model for real-world networks, each vertex is equipped with a weight drawn from a power-law distribution, and two vertices form an edge independently with probability proportional to the product of their…

Discrete Mathematics · Computer Science 2018-11-06 Karl Bringmann , Ralph Keusch , Johannes Lengler

This paper examines the relationship between sparse random network architectures and neural network stability by examining the eigenvalue spectral distribution. Specifically, we generalise classical eigenspectral results to sparse…

Neurons and Cognition · Quantitative Biology 2023-10-12 Isabelle D Harris , Hamish Meffin , Anthony N Burkitt , Andre D. H Peterson

We consider random geometric graphs on the plane characterized by a non-uniform density of vertices. In particular, we introduce a graph model where $n$ vertices are independently distributed in the unit disc with positions, in polar…

Disordered Systems and Neural Networks · Physics 2022-04-06 C. T. Martinez-Martinez , J. A. Mendez-Bermudez , Francisco A. Rodrigues , Ernesto Estrada

We analyse the largest eigenvalue of the adjacency matrix of the configuration model with large degrees, where the latter are treated as hard constraints. In particular, we compute the expectation of the largest eigenvalue for degrees that…

We prove that the bulk eigenvectors of sparse random matrices, i.e. the adjacency matrices of Erd\H{o}s-R\'enyi graphs or random regular graphs, are asymptotically jointly normal, provided the averaged degree increases with the size of the…

Probability · Mathematics 2017-06-30 Paul Bourgade , Jiaoyang Huang , Horng-Tzer Yau

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

We analyze the spectral properties of the high-dimensional random geometric graph $G(n, d, p)$, formed by sampling $n$ i.i.d vectors $\{v_i\}_{i=1}^{n}$ uniformly on a $d$-dimensional unit sphere and connecting each pair $\{i,j\}$ whenever…

Probability · Mathematics 2026-02-11 Yifan Cao , Yizhe Zhu

This paper studies the eigenvalue distribution of the Watts-Strogatz random graph, which is known as the "small-world" random graph. The construction of the small-world random graph starts with a regular ring lattice of n vertices; each has…

Probability · Mathematics 2021-01-28 Poramate Nakkirt

In this paper we consider a dynamic version of the Chung-Lu random graph in which the edges alternate between being present and absent. The main contribution concerns a technique by which one can estimate the underlying dynamics from…

Probability · Mathematics 2025-07-29 Rajat Subhra Hazra , Michel Mandjes , Jiesen Wang

Let $A_n$ be an $n\times n$ matrix with iid entries distributed as Bernoulli random variables with parameter $p = p_n$. Rudelson and Tikhomirov, in a beautiful and celebrated paper, show that the distribution of eigenvalues of $A_n \cdot…

Probability · Mathematics 2025-01-09 Ashwin Sah , Julian Sahasrabudhe , Mehtaab Sawhney

This paper is the second chapter of three of the author's undergraduate thesis. In this paper, we consider the random matrix ensemble given by $(d_b, d_w)$-regular graphs on $M$ black vertices and $N$ white vertices, where $d_b \in…

Probability · Mathematics 2018-01-18 Kevin Yang

Let $\FF$ be an arbitrary field and $(\bm{G}_{n,d/n})_n$ be a sequence of sparse weighted Erd\H{o}s-R\'enyi random graphs on $n$ vertices with edge probability $d/n$, where weights from $\FF \setminus\{0\}$ are assigned to the edges…

Combinatorics · Mathematics 2023-01-31 Remco van der Hofstad , Noela Müller , Haodong Zhu

We consider $N\times N$ symmetric random matrices where the probability distribution for each matrix element is given by a measure $\nu$ with a subexponential decay. We prove that the eigenvalue spacing statistics in the bulk of the…

Mathematical Physics · Physics 2010-11-25 Laszlo Erdos , Benjamin Schlein , Horng-Tzer Yau

Let $\mathcal A$ be the adjacency matrix of the Erd\H{o}s-R\'{e}nyi directed graph $\mathscr G(N,p)$. We denote the eigenvalues of $\mathcal A$ by $\lambda_1^{\cal A},...,\lambda^{\cal A}_N$, and $|\lambda_1^{\cal A}|=\max_i|\lambda_i^{\cal…

Probability · Mathematics 2025-09-16 Yukun He