Hypergraph assortativity: A dynamical systems perspective.
Chaos
; 32(5): 053113, 2022 May.
Article
em En
| MEDLINE
| ID: mdl-35649990
ABSTRACT
The largest eigenvalue of the matrix describing a network's contact structure is often important in predicting the behavior of dynamical processes. We extend this notion to hypergraphs and motivate the importance of an analogous eigenvalue, the expansion eigenvalue, for hypergraph dynamical processes. Using a mean-field approach, we derive an approximation to the expansion eigenvalue in terms of the degree sequence for uncorrelated hypergraphs. We introduce a generative model for hypergraphs that includes degree assortativity, and use a perturbation approach to derive an approximation to the expansion eigenvalue for assortative hypergraphs. We define the dynamical assortativity, a dynamically sensible definition of assortativity for uniform hypergraphs, and describe how reducing the dynamical assortativity of hypergraphs through preferential rewiring can extinguish epidemics. We validate our results with both synthetic and empirical datasets.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Epidemias
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Chaos
Assunto da revista:
CIENCIA
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos