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A random geometric digraph $G_n$ is constructed by taking $\{X_1,X_2,... X_n\}$ in $\mathbb{R}^2$ independently at random with a common bounded density function. Each vertex $X_i$ is assigned at random a sector $S_i$ of central angle…

Combinatorics · Mathematics 2019-09-18 Yilun Shang

We study symmetric motifs in random geometric graphs. Symmetric motifs are subsets of nodes which have the same adjacencies. These subgraphs are particularly prevalent in random geometric graphs and appear in the Laplacian and adjacency…

Disordered Systems and Neural Networks · Physics 2017-07-28 Carl P. Dettmann , Georgie Knight

Networks of disparate phenomena-- be it the global ecology, human social institutions, within the human brain, or in micro-scale protein interactions-- exhibit broadly consistent architectural features. To explain this, we propose a new…

Physics and Society · Physics 2021-01-26 Keith M. Smith

Degree heterogeneity and latent geometry, also referred to as popularity and similarity, are key explanatory components underlying the structure of real-world networks. The relationship between these components and the statistical…

Social and Information Networks · Computer Science 2024-09-18 Keith Malcolm Smith , Jason P. Smith

We give exact relations for certain types of the hierarchic fractal structures. In the blatant distinction from regular networks of the "small world" (SW) topology [1], regular fractal networks manifests the logarithmic dependence of the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Gregory Surdutovich , Vladimir Gol'dshtein , Gennady Koganov

Various real systems simultaneously exhibit scale-free and hierarchical structure. In this paper, we study analytically average distance in a deterministic scale-free network with hierarchical organization. Using a recursive method based on…

Statistical Mechanics · Physics 2009-10-29 Zhongzhi Zhang , Yuan Lin , Shuyang Gao , Shuigeng Zhou , Jihong Guan

Much recent research activity has been devoted to empirical study and theoretical models of complex networks (random graphs) with three qualitative features: power-law degree distribution, local clustering of edges, and small diameter. We…

Disordered Systems and Neural Networks · Physics 2017-08-23 David J. Aldous

Network complexity has been studied for over half a century and has found a wide range of applications. Many methods have been developed to characterize and estimate the complexity of networks. However, there has been little research with…

Machine Learning · Statistics 2021-01-13 Yann Issartel

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

Complex networks have become increasingly popular for modeling various real-world phenomena. Realistic generative network models are important in this context as they avoid privacy concerns of real data and simplify complex network research…

Data Structures and Algorithms · Computer Science 2015-04-24 Moritz von Looz , Christian L. Staudt , Henning Meyerhenke , Roman Prutkin

We analyse the performance of simple distributed colouring algorithms under the assumption that the input graph is a hyperbolic random graph (HRG), a generative model capturing key properties of real-world networks such as power-law degree…

Data Structures and Algorithms · Computer Science 2025-07-23 Yannic Maus , Janosch Ruff

In this paper, we study graph distances in the geometric random graph models scale-free percolation SFP, geometric inhomogeneous random graphs GIRG, and hyperbolic random graphs HRG. Despite the wide success of the models, the parameter…

Probability · Mathematics 2024-05-15 Kostas Lakis , Johannes Lengler , Kalina Petrova , Leon Schiller

To quantify the fundamental evolution of time-varying networks, and detect abnormal behavior, one needs a notion of temporal difference that captures significant organizational changes between two successive instants. In this work, we…

Social and Information Networks · Computer Science 2017-08-17 Nathan D Monnig , Francois G Meyer

We study random graphs with an i.i.d. degree sequence of which the tail of the distribution function $F$ is regularly varying with exponent $\tau\in (1,2)$. Thus, the degrees have infinite mean. Such random graphs can serve as models for…

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

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

We count the asymptotic number of triangles in uniform random graphs where the degree distribution follows a power law with degree exponent $\tau\in(2,3)$. We also analyze the local clustering coefficient $c(k)$, the probability that two…

Probability · Mathematics 2018-12-12 Pu Gao , Remco van der Hofstad , Angus Southwell , Clara Stegehuis

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

Among all characteristics exhibited by natural and man-made networks the small-world phenomenon is surely the most relevant and popular. But despite its significance, a reliable and comparable quantification of the question `how small is a…

Physics and Society · Physics 2019-11-27 Gorka Zamora-López , Romain Brasselet

We consider the number of crossings in a graph which is embedded randomly on a convex set of points. We give an estimate to the normal distribution in Kolmogorov distance which implies a convergence rate of order $n^{-1/2}$ for various…

Combinatorics · Mathematics 2022-08-26 Santiago Arenas-Velilla , Octavio Arizmendi

Proximity networks are time-varying graphs representing the closeness among humans moving in a physical space. Their properties have been extensively studied in the past decade as they critically affect the behavior of spreading phenomena…

Physics and Society · Physics 2019-11-28 Fragkiskos Papadopoulos , Marco Antonio Rodríguez Flores
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