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Motivated by the empirical analysis of the air transportation system, we define a network model that includes geographical attributes along with topological and weight (traffic) properties. The introduction of geographical attributes is…

Physics and Society · Physics 2007-05-23 Alain Barrat , Marc Barthelemy , Alessandro Vespignani

Core-periphery structure is a common property of complex networks, which is a composition of tightly connected groups of core vertices and sparsely connected periphery vertices. This structure frequently emerges in traffic systems, biology,…

Social and Information Networks · Computer Science 2019-05-28 Junteng Jia , Austin R. Benson

We introduce a very general model of an inhomogenous random graph with independence between the edges, which scales so that the number of edges is linear in the number of vertices. This scaling corresponds to the p=c/n scaling for G(n,p)…

Probability · Mathematics 2011-11-10 Bela Bollobas , Svante Janson , Oliver Riordan

A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel intermediate-level topological analysis that considers non-overlapping subgraphs…

Computational Physics · Physics 2009-11-13 Lucas Antiqueira , Luciano da Fontoura Costa

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

Small-world networks provide an interesting framework for studying the interplay between regular and random graphs, where links are located in a regular and random way, respectively. On one hand, the random links make the model to obey some…

Statistical Mechanics · Physics 2024-04-12 M. Ostilli

In this paper, we study the entropy of a hard random geometric graph (RGG), a commonly used model for spatial networks, where the connectivity is governed by the distances between the nodes. Formally, given a connection range $r$, a hard…

Information Theory · Computer Science 2026-01-19 Praneeth Kumar Vippathalla , Justin P. Coon , Mihai-Alin Badiu

Random graphs have proven to be one of the most important and fruitful concepts in modern Combinatorics and Theoretical Computer Science. Besides being a fascinating study subject for their own sake, they serve as essential instruments in…

Combinatorics · Mathematics 2007-05-23 Michael Krivelevich , Benny Sudakov

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

Quite often real-world networks can be thought of as being symmetric, in the abstract sense that vertices can be found to have similar or equivalent structural roles. However, traditional measures of symmetry in graphs are based on their…

Probability · Mathematics 2020-09-04 Jefferson Elbert Simões , Daniel R. Figueiredo , Valmir C. Barbosa

We consider the problem of determining the proportion of edges that are discovered in an Erdos-Renyi graph when one constructs all shortest paths from a given source node to all other nodes. This problem is equivalent to the one of…

Statistical Mechanics · Physics 2009-11-13 Vincent D. Blondel , Jean-Loup Guillaume , Julien M. Hendrickx , Raphael M. Jungers

In the original (1961) Gilbert model of random geometric graphs, nodes are placed according to a Poisson point process, and links formed between those within a fixed range. Motivated by wireless ad-hoc networks "soft" or "probabilistic"…

Statistical Mechanics · Physics 2017-06-15 Carl P. Dettmann , Orestis Georgiou

We study an evolving spatial network in which sequentially arriving vertices are joined to existing vertices at random according to a rule that combines preference according to degree with preference according to spatial proximity. We…

Probability · Mathematics 2015-06-30 Jonathan Jordan , Andrew R. Wade

Detecting the dimensionality of graphs is a central topic in machine learning. While the problem has been tackled empirically as well as theoretically, existing methods have several drawbacks. On the one hand, empirical tools are…

Social and Information Networks · Computer Science 2024-08-16 Tobias Friedrich , Andreas Göbel , Maximilian Katzmann , Leon Schiller

This paper proposes a novel graphical model, termed the spatial dependence graph model, which captures the global dependence structure of different events that occur randomly in space. In the spatial dependence graph model, the edge set is…

Methodology · Statistics 2016-07-26 Matthias Eckardt

Spatially embedded networks are shaped by a combination of purely topological (space-independent) and space-dependent formation rules. While it is quite easy to artificially generate networks where the relative importance of these two…

Physics and Society · Physics 2013-09-10 Franco Ruzzenenti , Francesco Picciolo , Riccardo Basosi , Diego Garlaschelli

Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina

A random intersection graph is constructed by independently assigning a subset of a given set of objects $W,$ to each vertex of the vertex set $V$ of a simple graph $G.$ There is an edge between two vertices of $V,$ iff their respective…

Probability · Mathematics 2008-09-09 Bhupendra Gupta

Network models with latent geometry have been used successfully in many applications in network science and other disciplines, yet it is usually impossible to tell if a given real network is geometric, meaning if it is a typical element in…

Statistical Mechanics · Physics 2016-05-23 Dmitri Krioukov

The intricate relations between elements in natural and human-made systems sustain the complex processes that shape our world, forming multiscale networks of interactions. These networks can be represented as graphs composed of nodes…

Disordered Systems and Neural Networks · Physics 2026-03-20 M. Ángeles Serrano