
Providing an abstract representation of natural and human complex structures is a challenging problem. Accounting for the system heterogenous components while allowing for analytical tractability is a difficult balance. Here I introduce complex hypergraphs (chygraphs), bringing together concepts from hypergraphs, multi-layer networks, simplicial complexes and hyperstructures. To illustrate the applicability of this combinatorial structure I calculate the component sizes statistics and identify the transition to a giant component. To this end I introduce a vectorization technique that tackles the multi-level nature of chygraphs. I conclude that chygraphs are a unifying representation of complex systems allowing for analytical insight.
8 pages, 3 figures, Phys Rev E (In press)
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Discrete Mathematics (cs.DM), FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Computer Science - Discrete Mathematics
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Discrete Mathematics (cs.DM), FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Computer Science - Discrete Mathematics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
