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We consider a formal discretisation of Euclidean quantum gravity defined by a statistical model of random $3$-regular graphs and making using of the Ollivier curvature, a coarse analogue of the Ricci curvature. Numerical analysis shows that…

High Energy Physics - Theory · Physics 2021-03-09 Christy Kelly , Carlo Trugenberger , Fabio Biancalana

A concentration of measure result is proved for the number of isolated vertices $Y$ in the Erd\H{o}s-R\'{e}nyi random graph model on $n$ edges with edge probability $p$. When $\mu$ and $\sigma^2$ denote the mean and variance of $Y$…

Probability · Mathematics 2011-06-02 Subhankar Ghosh , Larry Goldstein , Martin Raic

In this paper we study the random geometric graph $\mathsf{RGG}(n,\mathbb{T}^d,\mathsf{Unif},\sigma^q_p,p)$ with $L_q$ distance where each vertex is sampled uniformly from the $d$-dimensional torus and where the connection radius is chosen…

Statistics Theory · Mathematics 2023-10-24 Kiril Bangachev , Guy Bresler

We study the systole of a random surface, where by a random surface we mean a surface constructed by randomly gluing together an even number of triangles. We study two types of metrics on these surfaces, the first one coming from using…

Differential Geometry · Mathematics 2017-05-17 Bram Petri

We obtain non-asymptotic Gaussian concentration bounds for the difference between the invariant measure $\nu$ of an ergodic Brownian diffusion process and the empirical distribution of an approximating scheme with decreasing time step along…

Probability · Mathematics 2018-05-28 Igor Honoré , Stephane Menozzi , Gilles Pagès

This paper presents an empirical study of the relationship between the density of small-medium sized random graphs and their planarity. It is well known that, when the number of vertices tends to infinite, there is a sharp transition…

Discrete Mathematics · Computer Science 2020-08-27 Emanuele Balloni , Giuseppe Di Battista , Maurizio Patrignani

Limits of densities belonging to an exponential family appear in many applications, {e.g.} Gibbs models in Statistical Physics, relaxed combinatorial optimization, coding theory, critical likelihood computations, Bayes priors with singular…

Statistics Theory · Mathematics 2010-12-06 Luigi Malagò , Giovanni Pistone

Even though power-law or close-to-power-law degree distributions are ubiquitously observed in a great variety of large real networks, the mathematically satisfactory treatment of random power-law graphs satisfying basic statistical…

Probability · Mathematics 2023-11-09 Pim van der Hoorn , Gabor Lippner , Dmitri Krioukov

We demonstrate a mechanism for the production of massive excitations in graphs. We treat the number of neighbors at each vertex in the graph (degree) as a scalar field. Then we introduce a mechanism inspired by the Higgs mechanism in…

Disordered Systems and Neural Networks · Physics 2026-04-08 Ioannis Kleftogiannis , Ilias Amanatidis

This paper studies how close random graphs are typically to their expectations. We interpret this question through the concentration of the adjacency and Laplacian matrices in the spectral norm. We study inhomogeneous Erd\"os-R\'enyi random…

Probability · Mathematics 2016-08-10 Can M. Le , Elizaveta Levina , Roman Vershynin

The edge-degeneracy model is an exponential random graph model that uses the graph degeneracy, a measure of the graph's connection density, and number of edges in a graph as its sufficient statistics. We show this model is relatively…

Statistics Theory · Mathematics 2016-09-19 Nicolas Kim , Dane Wilburne , Sonja Petrović , Alessandro Rinaldo

We study the scaling properties of the non-equilibrium stationary states (NESS) of a reaction-diffusion model. Under a suitable smallness condition, we show that the density of particles satisfies a law of large numbers with respect to the…

Probability · Mathematics 2022-11-10 P. Gonçalves , M. Jara , R. Marinho , O. Menezes

We study the problem of detecting the presence of an underlying high-dimensional geometric structure in a random graph. Under the null hypothesis, the observed graph is a realization of an Erd\H{o}s-R\'enyi random graph $G(n,p)$. Under the…

Statistics Theory · Mathematics 2015-11-24 Sébastien Bubeck , Jian Ding , Ronen Eldan , Miklós Rácz

We introduce a method for the theoretical analysis of exponential random graph models. The method is based on a large-deviations approximation to the normalizing constant shown to be consistent using theory developed by Chatterjee and…

Probability · Mathematics 2013-11-21 Sourav Chatterjee , Persi Diaconis

We consider the canonical ensemble of $N$-vertex Erd\H{o}s-R\'enyi (ER) random topological graphs with quenched vertex degree, and with fugacity $\mu$ for each closed triple of bonds. We claim complete defragmentation of large-$N$ graphs…

Statistical Mechanics · Physics 2016-12-28 V. Avetisov , M. Hovhannisyan , A. Gorsky , S. Nechaev , M. Tamm , O. Valba

We study a new kind of proximity graphs called proportional-edge proximity catch digraphs (PCDs)in a randomized setting. PCDs are a special kind of random catch digraphs that have been developed recently and have applications in statistical…

Combinatorics · Mathematics 2010-03-30 Elvan Ceyhan

The fault tolerance of random graphs with unbounded degrees with respect to connectivity is investigated, which relates to the reliability of wireless sensor networks with unreliable relay nodes. The model evaluates the network breakdown…

Disordered Systems and Neural Networks · Physics 2019-06-05 Satoshi Takabe , Takafumi Nakano , Tadashi Wadayama

The Blume-Emery-Griffiths model with a random crystal field is studied in a random graph architecture, in which the average connectivity is a controllable parameter. The disordered average over the graph realizations is treated by replica…

Disordered Systems and Neural Networks · Physics 2023-02-22 R. Erichsen , Alexandre Silveira , S. G. Magalhaes

There has been an explosion of interest in statistical models for analyzing network data, and considerable interest in the class of exponential random graph (ERG) models, especially in connection with difficulties in computing maximum…

Machine Learning · Statistics 2009-01-05 Stephen E. Fienberg , Alessandro Rinaldo , Yi Zhou

We consider a random geometric graph with vertices sampled from a probability measure supported on $\mathbb R^d$, and study its connectivity. We show the graph is typically disconnected, unless the sampling density has superexponential…

Probability · Mathematics 2021-04-07 Henry-Louis de Kergorlay
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