The nature of hypergraph $k$-core percolation problems
Ginestra Bianconi, Sergey N. Dorogovtsev

TL;DR
This paper develops a theory for hypergraph $k$-core percolation, revealing significant differences from factor graph models and identifying conditions under which their phase diagrams coincide.
Contribution
It introduces a message-passing framework for hypergraph $k$-core percolation and explores the effects of different pruning processes on phase diagrams.
Findings
Hypergraph $k$-core percolation differs markedly from factor graph models.
Pruning processes on hyperedges can replicate factor graph phase diagrams.
Second-neighbor $k$-core percolation processes are fundamentally distinct.
Abstract
Hypergraphs are higher-order networks that capture the interactions between two or more nodes. Hypergraphs can always be represented by factor graphs, i.e. bipartite networks between nodes and factor nodes (representing groups of nodes). Despite this universal representation, here we reveal that -core percolation on hypergraphs can be significantly distinct from -core percolation on factor graphs. We formulate the theory of hypergraph -core percolation based on the assumption that a hyperedge can only be intact if all its nodes are intact. This scenario applies for instance to supply chains where the production of a product requires all raw materials and all processing steps; in biology it applies to protein-interaction networks where protein complexes can only function if all the proteins are present, and it applies as well to chemical reaction networks where a chemical…
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Taxonomy
TopicsComplex Network Analysis Techniques · Bioinformatics and Genomic Networks · Gene Regulatory Network Analysis
