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In this paper, we explore the two-star Exponential Random Graph Model, which is a two parameter exponential family on the space of simple labeled graphs. We introduce auxiliary variables to express the two-star model as a mixture of the…

Statistics Theory · Mathematics 2021-03-04 Sumit Mukherjee , Yuanzhe Xu

We derive the full phase diagram for a large family of two-parameter exponential random graph models, each containing a first order transition curve ending in a critical point.

Probability · Mathematics 2013-12-06 Charles Radin , Mei Yin

The $2$-star model is the simplest exponential random graph model that displays complex behavior, such as degeneracy and phase transition. Despite its importance, this model has been solved only in the regime of dense connectivity. In this…

Disordered Systems and Neural Networks · Physics 2015-09-02 Alessia Annibale , Owen T Courtney

We consider a family of directed exponential random graph models parametrized by edges and outward stars. Much of the important statistical content of such models is given by the normalization constant of the models, and in particular, an…

Probability · Mathematics 2018-03-28 David Aristoff , Lingjiong Zhu

The exponential family of random graphs is one of the most promising class of network models. Dependence between the random edges is defined through certain finite subgraphs, analogous to the use of potential energy to provide dependence…

Mathematical Physics · Physics 2015-06-11 Mei Yin

In this paper, we study exponential random graph models subject to certain constraints. We obtain some general results about the asymptotic structure of the model. We show that there exists non-trivial regions in the phase plane where the…

Probability · Mathematics 2017-02-27 Lingjiong Zhu

The exponential family of random graphs represents an important and challenging class of network models. Despite their flexibility, conventionally used exponential random graphs have one shortcoming. They cannot directly model weighted…

Probability · Mathematics 2016-07-15 Mei Yin

We study random graphs with latent geometric structure, where the probability of each edge depends on the underlying random positions corresponding to the two endpoints. We focus on the setting where this conditional probability is a…

Probability · Mathematics 2021-11-01 Suqi Liu , Miklos Z. Racz

The p-star model or exponential random graph is among the oldest and best-known of network models. Here we give an analytic solution for the particular case of the 2-star model, which is one of the most fundamental of exponential random…

Statistical Mechanics · Physics 2009-11-10 Juyong Park , M. E. J. Newman

The Axelrod model has been widely studied since its proposal for social influence and cultural dissemination. In particular, the community of statistical physics focused on the presence of a phase transition as a function of its two main…

Physics and Society · Physics 2020-06-24 Sebastián Pinto , Pablo Balenzuela

This paper studies a generalization of the Curie-Weiss model (the Ising model on a complete graph) to quantum mechanics. Using a natural probabilistic representation of this model, we give a complete picture of the phase diagram of the…

Probability · Mathematics 2009-11-13 Lincoln Chayes , Nicholas Crawford , Dmitry Ioffe , Anna Levit

We study a one parameter family of random graph models that spans a continuum between traditional random graphs of the Erd\H{o}s-R\'enyi type, where there is no underlying structure, and percolation models, where the possible edges are…

Probability · Mathematics 2008-04-02 Oskar Sandberg

We survey known results about phase transitions in various models of statistical physics when the underlying space is a nonamenable graph. Most attention is devoted to transitive graphs and trees.

Probability · Mathematics 2009-10-31 Russell Lyons

Many problems of interest in computer science and information theory can be phrased in terms of a probability distribution over discrete variables associated to the vertices of a large (but finite) sparse graph. In recent years,…

Probability · Mathematics 2009-11-11 Amir Dembo , Andrea Montanari

The study of probabilistic models for the analysis of complex networks represents a flourishing research field. Among the former, Exponential Random Graphs (ERGs) have gained increasing attention over the years. So far, only linear ERGs…

Physics and Society · Physics 2026-02-10 Mattia Marzi , Francesca Giuffrida , Diego Garlaschelli , Tiziano Squartini

Binomial random intersection graphs can be used as parsimonious statistical models of large and sparse networks, with one parameter for the average degree and another for transitivity, the tendency of neighbours of a node to be connected.…

Social and Information Networks · Computer Science 2018-06-26 Joona Karjalainen , Lasse Leskelä

We study a random matrix model for the statistical properties of the purity of a bipartite quantum system at a finite (fictitious) temperature. This enables us to write the generating function for the cumulants, for both balanced and…

Quantum Physics · Physics 2010-01-30 P. Facchi , U. Marzolino , G. Parisi , S. Pascazio , A. Scardicchio

We consider two independent Erd\H{o}s-R\'enyi random graphs, with possibly different parameters, and study two isomorphism problems, a graph embedding problem and a common subgraph problem. Under certain conditions on the graph parameters…

Combinatorics · Mathematics 2025-06-25 Dimitris Diamantidis , Takis Konstantopoulos , Linglong Yuan

Exponential random graphs are important to model the structure of real-world complex networks. Here we solve the two-star model with degree-degree correlations in the sparse regime. The model constraints the average correlation between the…

Statistical Mechanics · Physics 2021-08-04 Maíra Bolfe , Fernando L. Metz , Edgar Guzmán-González , Isaac Pérez Castillo

Phase transitions generically occur in random matrix models as the parameters in the joint probability distribution of the random variables are varied. They affect all main features of the theory and the interpretation of statistical models…

Statistical Mechanics · Physics 2007-05-23 G. M. Cicuta
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