Connected components in networks with higher-order interactions
Abstract We address the problem of defining connected components in hypergraphs, which are models for systems with higher-order interactions. For graphs with dyadic interactions, connected components are defined in terms of paths connecting nodes along the graph. However, defining connected components in hypergraphs is a more involved problem, as one needs to consider the higher-order nature of the interactions associated with the hyperedge. Higher-order interactions can be taken into consideration through a logic associated with the hyperedges, two examples being OR-logic and AND-logic; these logical operations can be considered two limiting cases corresponding to non-cooperative and fully cooperative interactions, respectively. In this paper we show how connected components can be defined in hypergraphs with OR- or AND-logic. While OR-logic and AND-logic provide the same connected components for nondirected hypergraphs, for directed hypergraphs the strongly connected component of AND-logic is a subset of the OR-logic strongly connected component. Interestingly, higher-order interactions change the general topological properties of connected components in directed hypergraphs. Notably, while for directed graphs the strongly connected component is the intersection of its in- and out-component, in hypergraphs with AND-logic the intersection of in- and out-component does not equal the strongly connected component. We develop a theory for the fraction of nodes that are part of the largest connected component and through comparison with real-world data we show that degree-cardinality correlations play a significant role.
Authors
- Gyeong Gyun Ha (ORCID: https://orcid.org/0009-0009-9298-1806)
- Izaak Neri (ORCID: https://orcid.org/0000-0001-9529-5742)
- Alessia Annibale (ORCID: https://orcid.org/0000-0003-4010-6742)
Institutions
- King's College London (GB)
Publication Details
- Journal
- Journal of Physics Complexity
- Published
- 2025-10-16
- DOI
- https://doi.org/10.1088/2632-072x/ae1431
- Primary Topic
- Complex Network Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00