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Geometric scale-free random graphs are popular models for networks that exhibit as heavy-tailed degree distributions, small-worldness and high clustering. In these models, vertices have weights that cause the heavy-tailed degrees and are…

Probability · Mathematics 2024-04-24 Riccardo Michielan , Clara Stegehuis , Matthias Walter

In this paper we study the behavior of maximum out/in-degree of binomial/Poisson random scaled sector graphs in the presence of random vertex and edge faults. We prove that the probability distribution of maximum degrees for random faulty…

Combinatorics · Mathematics 2019-09-18 Yilun Shang

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

We consider large random graphs with prescribed degrees, such as those generated by the configuration model. In the regime where the empirical degree distribution approaches a limit $\mu$ with finite mean, we establish the systematic…

Probability · Mathematics 2019-02-20 Justin Salez

A version of ``preferential attachment'' random graphs, corresponding to linear ``weights'' with random ``edge additions,'' which generalizes some previously considered models, is studied. This graph model is embedded in a continuous-time…

Probability · Mathematics 2007-05-23 K. B. Athreya , A. P. Ghosh , S. Sethuraman

We provide a simple proof that graphs in a general class of self-similar networks have zero percolation threshold. The considered self-similar networks include random scale-free graphs with given expected node degrees and zero clustering,…

Disordered Systems and Neural Networks · Physics 2011-01-28 M. Angeles Serrano , Dmitri Krioukov , Marian Boguna

Consider a set of $n$ vertices, where each vertex has a location in $\mathbb{R}^d$ that is sampled uniformly from the unit cube in $\mathbb{R}^d$, and a weight associated to it. Construct a random graph by placing edges independently for…

Probability · Mathematics 2022-09-07 Remco van der Hofstad , Pim van der Hoorn , Neeladri Maitra

We define a statistical ensemble of non-degenerate graphs, i.e. graphs without multiple- and self-connections between nodes. The node degree distribution is arbitrary, but the nodes are assumed to be uncorrelated. This completes our earlier…

Statistical Mechanics · Physics 2009-11-07 Z. Burda , A. Krzywicki

In this paper we describe the emergence of scale-free degree distributions from statistical mechanics principles. We define an energy associated to a degree sequence as the logarithm of the number of indistinguishable simple networks it is…

Statistical Mechanics · Physics 2007-05-23 Ginestra Bianconi

We describe the asymptotic behaviour of large degrees in random hyperbolic graphs, for all values of the curvature parameter $ \alpha$. We prove that, with high probability, the node degrees satisfy the following ordering property: the…

Probability · Mathematics 2025-03-27 Loïc Gassmann

We investigate the joint distribution of the vertex degrees in three models of random bipartite graphs. Namely, we can choose each edge with a specified probability, choose a specified number of edges, or specify the vertex degrees in one…

Combinatorics · Mathematics 2022-12-22 Brendan D. McKay , Fiona Skerman

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

A majority of studied models for scale-free networks have degree distributions with exponents greater than $2$. Real networks, however, can demonstrate essentially more heavy-tailed degree distributions. We explore two models of scale-free…

Physics and Society · Physics 2016-12-14 Gábor Timár , Sergey N. Dorogovtsev , José Fernando F. Mendes

A random geometric graph $G(\mathcal{X}_n, r_n)$ is formed by taking a binomial process $\mathcal{X}_n$ as the set of vertices and joining any two distinct points with an edge if they lie within distance $r_n$ of each other. We investigate…

Probability · Mathematics 2026-04-28 Junpei Otsuka

Degree distribution, or equivalently called degree sequence, has been commonly used to be one of most significant measures for studying a large number of complex networks with which some well-known results have been obtained. By contrast,…

Physics and Society · Physics 2020-02-19 Fei Ma , Xiaoming Wang , Ping Wang

Leaves, i.e., vertices of degree one, can play a significant role in graph structure, especially in sparsely connected settings in which leaves often constitute the largest fraction of vertices. We consider a leaf-based counterpart of the…

Statistical Mechanics · Physics 2025-11-07 Harrison Hartle , P. L. Krapivsky

In this paper, we present a detailed analysis of the global clustering coefficient in scale-free graphs. Many observed real-world networks of diverse nature have a power-law degree distribution. Moreover, the observed degree distribution…

Social and Information Networks · Computer Science 2015-07-06 Liudmila Ostroumova Prokhorenkova

We study a generalisation of the random recursive tree (RRT) model and its multigraph counterpart, the uniform directed acyclic graph (DAG). Here, vertices are equipped with a random vertex-weight representing initial inhomogeneities in the…

Probability · Mathematics 2023-12-29 Bas Lodewijks , Marcel Ortgiese

We give sufficient conditions under which a random graph with a specified degree sequence is symmetric or asymmetric. In the case of bounded degree sequences, our characterisation captures the phase transition of the symmetry of the random…

Combinatorics · Mathematics 2020-04-07 Lochlan Brick , Pu Gao , Angus Southwell

We consider an inhomogeneous Erd\H{o}s-R\'enyi random graph ensemble with exponentially decaying random disconnection probabilities determined by an i.i.d. field of variables with heavy tails and infinite mean associated to the vertices of…

Probability · Mathematics 2026-04-01 Luca Avena , Diego Garlaschelli , Rajat Subhra Hazra , Margherita Lalli