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We examine the empirical distribution of the eigenvalues and the eigenvectors of adjacency matrices of sparse regular random graphs. We find that when the degree sequence of the graph slowly increases to infinity with the number of…

Probability · Mathematics 2012-10-15 Ioana Dumitriu , Soumik Pal

We present a new notion of limits of weighted directed graphs of growing size based on convergence of their random quotients. These limits are specified in terms of random exchangeable measures on the unit square. We call our limits…

Combinatorics · Mathematics 2026-03-24 Eitan Levin , Venkat Chandrasekaran

The properties of eigenvalues of large dimensional random matrices have received considerable attention. One important achievement is the existence and identification of the limiting spectral distribution of the empirical spectral…

Combinatorics · Mathematics 2009-06-12 Wenxue Du , Xueliang Li , Yiyang Li

Eigenvalues of Wigner matrices has been a major topic of investigation. A particularly important subclass of such random matrices is formed by the adjacency matrix of an Erd\H{o}s-R\'{e}nyi graph $\mathcal{G}_{n,p}$ equipped with i.i.d.…

Probability · Mathematics 2022-06-15 Shirshendu Ganguly , Ella Hiesmayr , Kyeongsik Nam

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

The scaled standard Wigner matrix (symmetric with mean zero, variance one i.i.d. entries), and its limiting eigenvalue distribution, namely the semi-circular distribution, has attracted much attention. The $2k$th moment of the limit equals…

Probability · Mathematics 2021-03-18 Arup Bose , Koushik Saha , Arusharka Sen , Priyanka Sen

Consider the matrix $A_{\mathcal{G}}$ chosen uniformly at random from the finite set of all $N$-dimensional matrices of zero main-diagonal and binary entries, having each row and column of $A_{\mathcal{G}}$ sum to $d$. That is, the…

Probability · Mathematics 2025-07-31 Arka Adhikari , Amir Dembo

We study the properties of random graphs where for each vertex a {\it neighbourhood} has been previously defined. The probability of an edge joining two vertices depends on whether the vertices are neighbours or not, as happens in Small…

Disordered Systems and Neural Networks · Physics 2009-11-10 Sebastian Risau-Gusman

We study eigenvalue distribution of the adjacency matrix $A^{(N,p, \alpha)}$ of weighted random bipartite graphs $\Gamma= \Gamma_{N,p}$. We assume that the graphs have $N$ vertices, the ratio of parts is $\frac{\alpha}{1-\alpha}$ and the…

Mathematical Physics · Physics 2015-07-28 Valentin Vengerovsky

We consider sparse inhomogeneous Erd\H{o}s-R\'enyi random graph ensembles where edges are connected independently with probability $p_{ij}$. We assume that $p_{ij}= \varepsilon_N f(w_i, w_j)$ where $(w_i)_{i\ge 1}$ is a sequence of…

Probability · Mathematics 2023-12-06 Luca Avena , Rajat Subhra Hazra , Nandan Malhotra

Consider a random regular graph of fixed degree $d$ with $n$ vertices. We study spectral properties of the adjacency matrix and of random Schr\"odinger operators on such a graph as $n$ tends to infinity. We prove that the integrated density…

Mathematical Physics · Physics 2014-05-09 Leander Geisinger

Consider d uniformly random permutation matrices on n labels. Consider the sum of these matrices along with their transposes. The total can be interpreted as the adjacency matrix of a random regular graph of degree 2d on n vertices. We…

Probability · Mathematics 2019-09-25 Ioana Dumitriu , Tobias Johnson , Soumik Pal , Elliot Paquette

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

Suppose that $\{G_n\}$ is a sequence of finite graphs such that each $G_n$ is the tangency graph of a sphere packing in $\mathbb{R}^d$. Let $\rho_n$ be a uniformly random vertex of $G_n$ and suppose that $(G,\rho)$ is the distributional…

Metric Geometry · Mathematics 2018-02-13 James R. Lee

Statistical field theory methods have been very successful with a number of random graph and random matrix problems, but it is challenging to apply these methods to graphs with prescribed degree sequences due to the extensive number of…

Statistical Mechanics · Physics 2025-05-20 Pawat Akara-pipattana , Oleg Evnin

We define a graph to be $S$-regular if it contains an equitable partition given by a matrix $S$. These graphs are generalizations of both regular and bipartite, biregular graphs. An $S$-regular matrix is defined then as a matrix on an…

Combinatorics · Mathematics 2023-11-15 Matthew B. Crawford , David J. Marchette , William Maxwell , Samuel S. Mendelson

We consider the random reversible Markov kernel K obtained by assigning i.i.d. nonnegative weights to the edges of the complete graph over n vertices and normalizing by the corresponding row sum. The weights are assumed to be in the domain…

Probability · Mathematics 2012-11-19 Charles Bordenave , Pietro Caputo , Djalil Chafaï

Let $(G,w)$ be a weighted graph with a weight-function $w: E(G)\to \mathbb R\backslash\{0\}$. A weighted graph $(G,w)$ is invertible to a new weighted graph if its adjacency matrix is invertible. A graph inverse has combinatorial interest…

Combinatorics · Mathematics 2015-06-15 Dong Ye , Yujun Yang , Bholanath Mandal , Douglas J. Klein

We study random graphs with arbitrary distributions of expected degree and derive expressions for the spectra of their adjacency and modularity matrices. We give a complete prescription for calculating the spectra that is exact in the limit…

Social and Information Networks · Computer Science 2013-02-04 Raj Rao Nadakuditi , M. E. J. Newman

For each $N\geq 1$, let $G_N$ be a simple random graph on the set of vertices $[N]=\{1,2, ..., N\}$, which is invariant by relabeling of the vertices. The asymptotic behavior as $N$ goes to infinity of correlation functions: $$ \mathfrak…

Probability · Mathematics 2014-10-30 Camille Male , Sandrine Péché