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High-Accuracy Approximation of Binary-State Dynamics on Networks

Open access
Gleeson, James P.·2011·Physical Review Letters

Abstract

Binary-state dynamics (such as the susceptible-infected-susceptible (SIS) model of disease spread, or Glauber spin dynamics) on random networks are accurately approximated using master equations. Standard mean-field and pairwise theories are shown to result from seeking approximate solutions of the master equations. Applications to the calculation of SIS epidemic thresholds and critical points of nonequilibrium spin models are also demonstrated.

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Metadata

Authors
Gleeson, J. P.
Venue
Physical Review Letters
Published
2011-08-04
Volume
107
Issue
6
Pages
068701-068701
ISSN
  • 0031-9007 (ISSN-L)
  • 1079-7114
OpenAlex
W1977136137
Cited by
240
References
4
FWCI
12.20
Type
journal article
Language
en
Open access
green

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Gleeson, J. P. (2011). High-Accuracy Approximation of Binary-State Dynamics on Networks. Physical Review Letters. https://doi.org/10.1103/physrevlett.107.068701

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.