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Random network models, constrained to reproduce specific statistical features, are often used to represent and analyze network data and their mathematical descriptions. Chief among them, the configuration model constrains random networks by…

Social and Information Networks · Computer Science 2025-01-28 Laurent Hébert-Dufresne , Jean-Gabriel Young , Alexander Daniels , Alec Kirkley , Antoine Allard

We provide a novel family of generative block-models for random graphs that naturally incorporates degree distributions: the block-constrained configuration model. Block-constrained configuration models build on the generalised…

Physics and Society · Physics 2021-02-24 Giona Casiraghi

In this paper, we give an analytic solution for graphs with n nodes and E edges for which the probability of obtaining a given graph G is specified in terms of the degree sequence of G. We describe how this model naturally appears in the…

Probability · Mathematics 2008-10-20 M. Draief , A. Ganesh , L. Massoulie

Network (or graph) sparsification compresses a graph by removing inessential edges. By reducing the data volume, it accelerates or even facilitates many downstream analyses. Still, the accuracy of many sparsification methods, with…

Social and Information Networks · Computer Science 2023-09-28 Zhen Su , Jürgen Kurths , Henning Meyerhenke

We study the statistical properties of the generation of random graphs according the configuration model, where one assigns randomly degrees to nodes. This model is often used, e.g., for the scale-free degree distribution ~d^gamma. For the…

Disordered Systems and Neural Networks · Physics 2015-05-28 Hendrike Klein-Hennig , Alexander K. Hartmann

Complex network theory crucially depends on the assumptions made about the degree distribution, while fitting degree distributions to network data is challenging, in particular for scale-free networks with power-law degrees. We present a…

Physics and Society · Physics 2022-12-28 Judith Brugman , Johan S. H. van Leeuwaarden , Clara Stegehuis

Clustering is well-known to play a prominent role in the description and understanding of complex networks, and a large spectrum of tools and ideas have been introduced to this end. In particular, it has been recognized that the abundance…

Disordered Systems and Neural Networks · Physics 2009-11-10 Danilo Sergi

We examine the heterogeneous responses of individual nodes in sparse networks to the random removal of a fraction of edges. Using the message-passing formulation of percolation, we discover considerable variation across the network in the…

Statistical Mechanics · Physics 2017-09-13 Reimer Kuehn , Tim Rogers

Theta graphs are important geometric graphs that have many applications, including wireless networking, motion planning, real-time animation, and minimum-spanning tree construction. We give closed form expressions for the average degree of…

Computational Geometry · Computer Science 2013-04-12 Pat Morin , Sander Verdonschot

In 2007 we introduced a general model of sparse random graphs with independence between the edges. The aim of this paper is to present an extension of this model in which the edges are far from independent, and to prove several results…

Probability · Mathematics 2011-05-05 Bela Bollobas , Svante Janson , Oliver Riordan

We explore various techniques for counting the number of straight-edge crossing-free graphs that can be embedded on a planar point set. In particular, we derive a lower bound on the ratio of the number of such graphs with $m+1$ edges to the…

Combinatorics · Mathematics 2019-05-24 Siddharth Prasad

Complex systems, ranging from soft materials to wireless communication, are often organised as random geometric networks in which nodes and edges evenly fill up the volume of some space. Studying such networks is difficult because they…

Probability · Mathematics 2022-07-19 Ivan Kryven , Rik Versendaal

Understanding the subgraph distribution in random networks is important for modelling complex systems. In classic Erdos networks, which exhibit a Poissonian degree distribution, the number of appearances of a subgraph G with n nodes and g…

Statistical Mechanics · Physics 2009-11-10 S. Itzkovitz , R. Milo , N. Kashtan , G. Ziv , U. Alon

The average size of connected vertex subsets of a connected graph generalises a much-studied parameter for subtrees of trees. For trees, the possible values of this parameter are critically affected by the presence or absence of vertices of…

Combinatorics · Mathematics 2022-06-13 John Haslegrave

We identify the upper large deviation probability for the number of edges in scale-free geometric random graph models as the space volume goes to infinity. Our result covers the models of scale-free percolation, the Boolean model with…

Random graphs with a given degree sequence are often constructed using the configuration model, which yields a random multigraph. We may adjust this multigraph by a sequence of switchings, eventually yielding a simple graph. We show that,…

Probability · Mathematics 2019-02-01 Svante Janson

In this thesis we consider ordered graphs (that is, graphs with a fixed linear ordering on their vertices). We summarize and further investigations on the number of edges an ordered graph may have while avoiding a fixed forbidden ordered…

Discrete Mathematics · Computer Science 2009-07-16 Craig Weidert

We obtain several sharp spectral bounds, approximations, and exact values for the isoperimetric number and related edge-expansion parameters of graphs. Our results focus on graph powers and on families of graphs with rich algebraic or…

This article provides sharp bounds for the maximum number of edges possible in a simple graph with restricted values of two of the three parameters, namely, maxi- mum matching size, independence number and maximum degree. We also construct…

Combinatorics · Mathematics 2012-03-08 Niraj Khare , Nishali Mehta , Naushad Puliyambalath

In this paper we study first-passage percolation in the configuration model with empirical degree distribution that follows a power-law with exponent $\tau \in (2,3)$. We assign independent and identically distributed (i.i.d.)\ weights to…

Probability · Mathematics 2018-02-14 Erwin Adriaans , Julia Komjathy