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We study random graphs with arbitrary distributions of expected degree and derive expressions for the spectra of their adjacency and modularity matrices. We give a complete prescription for calculating the spectra that is exact in the limit…

Social and Information Networks · Computer Science 2013-02-04 Raj Rao Nadakuditi , M. E. J. Newman

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

In the field of complex networks, hypergraph models have so far received significantly less attention than graphs. However, many real-life networks feature multiary relations (co-authorship, protein reactions) may therefore be modeled way…

Discrete Mathematics · Computer Science 2023-06-07 Frédéric Giroire , Nicolas Nisse , Kostiantyn Ohulchanskyi , Małgorzata Sulkowska , Thibaud Trolliet

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

Given a locally finite simple graph so that its degree is not bounded, every self-adjoint realization of the adjacency matrix is unbounded from above. In this note we give an optimal condition to ensure it is also unbounded from below. We…

Functional Analysis · Mathematics 2015-05-14 Sylvain Golenia

In this paper we relate a fundamental parameter of a random graph, its degree sequence, to a simple model of nearly independent binomial random variables. This confirms a conjecture made in 1997. As a result, many interesting functions of…

Combinatorics · Mathematics 2019-08-27 Anita Liebenau , Nick Wormald

Subgraph counts - in particular the number of occurrences of small shapes such as triangles - characterize properties of random networks, and as a result have seen wide use as network summary statistics. However, subgraphs are typically…

Statistics Theory · Mathematics 2020-06-30 P-A. Maugis

Computing the embedding distribution of a given graph is a fundamental question in topological graph theory. In this article, we extend our viewpoint to a sequence of graphs and consider their asymptotic embedding distributions, which are…

Combinatorics · Mathematics 2025-07-22 Yichao Chen , Wenjie Fang , Zhicheng Gao , Jinlian Zhang

Recent work on the structure of social networks and the internet has focussed attention on graphs with distributions of vertex degree that are significantly different from the Poisson degree distributions that have been widely studied in…

Statistical Mechanics · Physics 2009-10-31 M. E. J. Newman , S. H. Strogatz , D. J. Watts

In this paper we derive results concerning the connected components and the diameter of random graphs with an arbitrary i.i.d. degree sequence. We study these properties primarily, but not exclusively, when the tail of the degree…

Probability · Mathematics 2007-05-23 Remco van der Hofstad , Gerard Hooghiemstra , Dmitri Znamenski

We obtain local weak limits in probability for Collapsed Branching Processes (CBP), which are directed random networks obtained by collapsing random-sized families of individuals in a general continuous-time branching process. The local…

Probability · Mathematics 2025-01-22 Sayan Banerjee , Prabhanka Deka , Mariana Olvera-Cravioto

We consider random rooted maps without regard to their genus, with fixed large number of edges, and address the problem of limiting distributions for six different parameters: vertices, leaves, loops, root edges, root isthmus, and root…

Combinatorics · Mathematics 2018-02-21 Olivier Bodini , Julien Courtiel , Sergey Dovgal , Hsien-Kuei Hwang

We study the growth of bipartite networks in which the number of nodes in one of the partitions is kept fixed while the other partition is allowed to grow. We study random and preferential attachment as well as combination of both. We…

Disordered Systems and Neural Networks · Physics 2009-11-13 Fernando Peruani , Monojit Choudhury , Animesh Mukherjee , Niloy Ganguly

This article presents the precise asymptotical distribution of two types of critical transmission radii, defined in terms of k-connectivity and the minimum vertex degree, for random geometry graphs distributed over three-dimensional…

Probability · Mathematics 2025-11-24 Jie Ding , Shuai Ma , Xiang Wei , Xiaohua Xu , Xinshan Zhu

Given a set D of nonnegative integers, we derive the asymptotic number of graphs with a givenvnumber of vertices, edges, and such that the degree of every vertex is in D. This generalizes existing results, such as the enumeration of graphs…

Combinatorics · Mathematics 2015-07-22 Élie de Panafieu , Lander Ramos

In this paper we investigate geometric properties of graphs generated by a preferential attachment random graph model with edge-steps. More precisely, at each time $t\in\mathbb{N}$, with probability $p$ a new vertex is added to the graph (a…

Probability · Mathematics 2019-01-10 Caio Alves , Rodrigo Ribeiro , Remy Sanchis

Preferential attachment is widely used to model power-law behavior of degree distributions in both directed and undirected networks. In a directed preferential attachment model, despite the well-known marginal power-law degree…

Probability · Mathematics 2018-08-07 Tiandong Wang , Sidney I. Resnick

The directed preferential attachment model is revisited. A new exact characterization of the limiting in- and out-degree distribution is given by two \emph{independent} pure birth processes that are observed at a common exponentially…

Probability · Mathematics 2018-10-08 Tom Britton

We study the use of local heuristics to determine spanning subgraphs for use in the dissemination of information in complex networks. We introduce two different heuristics and analyze their behavior in giving rise to spanning subgraphs that…

Networking and Internet Architecture · Computer Science 2007-05-23 A. O. Stauffer , V. C. Barbosa

A probabilistic generative network model with $n$ nodes and $m$ overlapping layers is obtained as a superposition of $m$ mutually independent Bernoulli random graphs of varying size and strength. When $n$ and $m$ are large and of the same…

Probability · Mathematics 2021-06-01 Mindaugas Bloznelis , Joona Karjalainen , Lasse Leskelä