Higher-order percolation processes on multiplex hypergraphs.
- Resource Type
- Academic Journal
- Authors
- Sun H; School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom.; Bianconi G; School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom.; The Alan Turing Institute, The British Library, 96 Euston Road, London NW1 2DB, 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
Higher-order interactions are increasingly recognized as a fundamental aspect of complex systems ranging from the brain to social contact networks. Hypergraphs as well as simplicial complexes capture the higher-order interactions of complex systems and allow us to investigate the relation between their higher-order structure and their function. Here we establish a general framework for assessing hypergraph robustness and we characterize the critical properties of simple and higher-order percolation processes. This general framework builds on the formulation of the random multiplex hypergraph ensemble where each layer is characterized by hyperedges of given cardinality. We observe that in presence of the structural cutoff the ensemble of multiplex hypergraphs can be mapped to an ensemble of multiplex bipartite networks. We reveal the relation between higher-order percolation processes in random multiplex hypergraphs, interdependent percolation of multiplex networks, and K-core percolation. The structural correlations of the random multiplex hypergraphs are shown to have a significant effect on their percolation properties. The wide range of critical behaviors observed for higher-order percolation processes on multiplex hypergraphs elucidates the mechanisms responsible for the emergence of discontinuous transition and uncovers interesting critical properties which can be applied to the study of epidemic spreading and contagion processes on higher-order networks.