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In this work we perform a detailed statistical analysis of topological and spectral properties of random geometric graphs (RGGs); a graph model used to study the structure and dynamics of complex systems embedded in a two dimensional space.…

Disordered Systems and Neural Networks · Physics 2020-10-21 R. Aguilar-Sanchez , J. A. Mendez-Bermudez , Francisco A. Rodrigues , Jose M. Sigarreta

We propose the following model of a random graph on n vertices. Let F be a distribution in R_+^{n(n-1)/2} with a coordinate for every pair i$ with 1 \le i,j \le n. Then G_{F,p} is the distribution on graphs with n vertices obtained by…

Combinatorics · Mathematics 2011-08-09 Alan Frieze , Santosh Vempala , Juan Vera

Random graphs defined by an occurrence probability that is invariant under node aggregation have been identified recently in the context of network renormalization. The invariance property requires that edges are drawn with a specific…

Spectral Theory · Mathematics 2025-09-18 Alessio Catanzaro , Rajat Subhra Hazra , Diego Garlaschelli

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

For a graph representation of a dataset, a straightforward normality measure for a sample can be its graph degree. Considering a weighted graph, degree of a sample is the sum of the corresponding row's values in a similarity matrix. The…

Machine Learning · Computer Science 2018-02-06 Caglar Aytekin , Francesco Cricri , Lixin Fan , Emre Aksu

We propose a distribution-free approach to the study of random geometric graphs. The distribution of vertices follows a Poisson point process with intensity function $nf(\cdot)$, where $n\in \mathbb{N}$, and $f$ is a probability density…

Probability · Mathematics 2012-10-22 Srikanth K. Iyer , Debleena Thacker

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

We consider the random geometric graph on $n$ vertices drawn uniformly from a $d$--dimensional sphere. We focus on the sparse regime, when the expected degree is constant independent of $d$ and $n$. We show that, when $d$ is larger than $n$…

Probability · Mathematics 2021-10-22 Elliot Paquette , Andrew Vander Werf

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short range correlations in the level spacings of the…

Physics and Society · Physics 2017-06-08 Carl P. Dettmann , Orestis Georgiou , Georgie Knight

This paper deals with the problem of detecting non-isotropic high-dimensional geometric structure in random graphs. Namely, we study a model of a random geometric graph in which vertices correspond to points generated randomly and…

Statistics Theory · Mathematics 2020-02-25 Ronen Eldan , Dan Mikulincer

Random geometric graphs consist of randomly distributed nodes (points), with pairs of nodes within a given mutual distance linked. In the usual model the distribution of nodes is uniform on a square, and in the limit of infinitely many…

Disordered Systems and Neural Networks · Physics 2018-09-27 Carl P. Dettmann

Let $G_n$ be a random geometric graph with vertex set $[n]$ based on $n$ i.i.d.\ random vectors $X_1,\ldots,X_n$ drawn from an unknown density $f$ on $\R^d$. An edge $(i,j)$ is present when $\|X_i -X_j\| \le r_n$, for a given threshold…

Machine Learning · Statistics 2023-11-23 Caelan Atamanchuk , Luc Devroye , Gabor Lugosi

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 revisit the problem of designing sublinear algorithms for estimating the average degree of an $n$-vertex graph. The standard access model for graphs allows for the following queries: sampling a uniform random vertex, the degree of a…

Data Structures and Algorithms · Computer Science 2025-10-24 Lorenzo Beretta , Deeparnab Chakrabarty , C. Seshadhri

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

This work addresses a modification of the random geometric graph (RGG) model by considering a set of points uniformly and independently distributed on the surface of a $(d-1)$-sphere with radius $r$ in a $d-$dimensional Euclidean space,…

Physics and Society · Physics 2018-10-03 Alfonso Allen-Perkins

Recently, Bollob\'as, Janson and Riordan introduced a very general family of random graph models, producing inhomogeneous random graphs with $\Theta(n)$ edges. Roughly speaking, there is one model for each {\em kernel}, i.e., each symmetric…

Combinatorics · Mathematics 2010-06-29 B. Bollobas , O. Riordan

Consider the geometric graph on $n$ independent uniform random points in a connected compact region $A$ of ${\bf R}^d, d \geq 2$, with $C^2$ boundary, or in the unit square, with distance parameter $r_n$. Let $K_n$ be the number of…

Probability · Mathematics 2026-04-09 Mathew D. Penrose , Xiaochuan Yang

We investigate some topological and spectral properties of Erd\H{o}s-R\'{e}nyi (ER) random digraphs $D(n,p)$. In terms of topological properties, our primary focus lies in analyzing the number of non-isolated vertices $V_x(D)$ as well as…

Disordered Systems and Neural Networks · Physics 2023-11-15 C. T. Martínez-Martínez , J. A. Méndez-Bermúdez , José M. Sigarreta

Random geometric graphs (RGGs) are commonly used to model networked systems that depend on the underlying spatial embedding. We concern ourselves with the probability distribution of an RGG, which is crucial for studying its random…

Information Theory · Computer Science 2018-01-16 Mihai-Alin Badiu , Justin P. Coon
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