학술논문

Belief propagation on networks with cliques and chordless cycles.
Document Type
Academic Journal
Author
Mann P; School of Computer Science, University of St Andrews, St Andrews, Fife KY16 9SX, United Kingdom.; Dobson S; School of Computer Science, University of St Andrews, St Andrews, Fife KY16 9SX, United Kingdom.
Source
Publisher: American Physical Society Country of Publication: United States NLM ID: 101676019 Publication Model: Print Cited Medium: Internet ISSN: 2470-0053 (Electronic) Linking ISSN: 24700045 NLM ISO Abbreviation: Phys Rev E Subsets: PubMed not MEDLINE; MEDLINE
Subject
Language
English
Abstract
It is well known that tree-based theories can describe the properties of undirected clustered networks with extremely accurate results [S. Melnik et al., Phys. Rev. E 83, 036112 (2011)10.1103/PhysRevE.83.036112]. It is reasonable to suggest that a motif-based theory would be superior to a tree one, since additional neighbor correlations are encapsulated in the motif structure. In this paper, we examine bond percolation on random and real world networks using belief propagation in conjunction with edge-disjoint motif covers. We derive exact message passing expressions for cliques and chordless cycles of finite size. Our theoretical model gives good agreement with Monte Carlo simulation and offers a simple, yet substantial improvement on traditional message passing, showing that this approach is suitable to study the properties of random and empirical networks.