Hypergraph Animals

3 Apr 2023  ·  Michael P. H. Stumpf ·

Here we introduce simple structures for the analysis of complex hypergraphs, hypergraph animals. These structures are designed to describe the local node neighbourhoods of nodes in hypergraphs. We establish their relationships to lattice animals and network motifs and develop their combinatorial properties, for sparse and uncorrelated hypergraphs. Here we can make use of the tight link of hypergraph animals to partition numbers, which opens up a vast mathematical framework for the analysis of hypergraph animals. We then study their abundances in random hypergraphs. Two transferable insights result from this analysis: (i) it establishes the importance of high-cardinality edges in ensembles of random hypergraphs that are inspired by the classical Erdos-Reny\'i random graphs; and (ii) there is a close connection between degree and hyperedge cardinality in random hypergraphs that shapes the animal abundances and spectra profoundly. Together these two findings imply that we need to spend more effort on investigating and developing suitable conditional ensembles of random hypergraph that can capture real-world structures and their complex dependency structures.

PDF Abstract
No code implementations yet. Submit your code now

Tasks


Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here