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High-accuracy approximation of binary-state dynamics on networks

Date
2011
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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Description
peer-reviewed
Publisher
American Physical Society
Citation
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Mathematics & Statistics
MACSI - Mathematics Application Consortium for Science & Industry
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Gleeson_2011_highaccuracy.pdf
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Keywords
contact process, model, epidemics, lattice, spread
ULRR Identifiers
https://hdl.handle.net/10344/4463
 https://doi.org/10.34961/4469
Funding code
Funding Information
Science Foundation Ireland (SFI)
Sustainable Development Goals
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