Percolation in random graphs with higher-order clustering

Peter Mann, V. Anne Smith, John B. O. Mitchell, and Simon Dobson
Phys. Rev. E 103, 012313 – Published 25 January 2021

Abstract

Percolation theory can be used to describe the structural properties of complex networks using the generating function formulation. This mapping assumes that the network is locally treelike and does not contain short-range loops between neighbors. In this paper we use the generating function formulation to examine clustered networks that contain simple cycles and cliques of any order. We use the natural generalization to the Molloy-Reed criterion for these networks to describe their critical properties and derive an approximate analytical description of the size of the giant component, providing solutions for Poisson and power-law networks. We find that networks comprising larger simple cycles behave increasingly more treelike. Conversely, clustering composed of larger cliques increasingly deviate from the treelike solution, although the behavior is strongly dependent on the degree-assortativity.

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  • Received 12 February 2020
  • Revised 1 June 2020
  • Accepted 6 January 2021

DOI:https://doi.org/10.1103/PhysRevE.103.012313

©2021 American Physical Society

Physics Subject Headings (PhySH)

Networks

Authors & Affiliations

Peter Mann1,2,3,*, V. Anne Smith2, John B. O. Mitchell1, and Simon Dobson3

  • 1School of Chemistry, University of St Andrews, St Andrews, Fife KY16 9ST, United Kingdom
  • 2School of Biology, University of St Andrews, St Andrews, Fife KY16 9TH, United Kingdom
  • 3School of Computer Science, University of St Andrews, St Andrews, Fife KY16 9SX, United Kingdom

  • *pm78@st-andrews.ac.uk

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Vol. 103, Iss. 1 — January 2021

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