# gst: directionality and node heterogeneity reshape criticality in hypergraph percolation.

<< Directed and heterogeneous hypergraphs capture directional higher-order interactions with intrinsically asymmetric functional dependencies among nodes. As a result, damage to certain nodes can suppress entire hyperedges, whereas failure of others only weakens interactions. Metabolic reaction networks offer an intuitive example of such asymmetric dependencies. >>

<< Here (AA) develop a message-passing and statistical mechanics framework for percolation in directed hypergraphs that explicitly incorporates directionality and node heterogeneity. Remarkably, (They)  show that these hypergraph features have a fundamental effect on the critical properties of hypergraph percolation, reshaping criticality in a way that depends on network structure. >>

<< Specifically, (AA) derive anomalous critical exponents that depend on whether node or hyperedge percolation is considered in maximally correlated, heavy-tailed regimes. These theoretical predictions are validated on synthetic hypergraph models and on a real directed metabolic network, opening new perspectives for the characterization of the robustness and resilience of real-world directed, heterogeneous higher-order networks. >>

Yunxue Sun, Xueming Liu, Ginestra Bianconi. Directionality and node heterogeneity reshape criticality in hypergraph percolation. arXiv: 2601.20726v1 [cond-mat.dis-nn]. Jan 28, 2026.

https://arxiv.org/abs/2601.20726

Also: network, transition, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, networks, transitions, criticality, hypergraph, percolation, anchor nodes.