Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes

Yuanzhao Zhang (), Maxime Lucas () and Federico Battiston ()
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Yuanzhao Zhang: Santa Fe Institute
Maxime Lucas: ISI Foundation
Federico Battiston: Central European University

Nature Communications, 2023, vol. 14, issue 1, 1-8

Abstract: Abstract Higher-order networks have emerged as a powerful framework to model complex systems and their collective behavior. Going beyond pairwise interactions, they encode structured relations among arbitrary numbers of units through representations such as simplicial complexes and hypergraphs. So far, the choice between simplicial complexes and hypergraphs has often been motivated by technical convenience. Here, using synchronization as an example, we demonstrate that the effects of higher-order interactions are highly representation-dependent. In particular, higher-order interactions typically enhance synchronization in hypergraphs but have the opposite effect in simplicial complexes. We provide theoretical insight by linking the synchronizability of different hypergraph structures to (generalized) degree heterogeneity and cross-order degree correlation, which in turn influence a wide range of dynamical processes from contagion to diffusion. Our findings reveal the hidden impact of higher-order representations on collective dynamics, highlighting the importance of choosing appropriate representations when studying systems with nonpairwise interactions.

Date: 2023
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DOI: 10.1038/s41467-023-37190-9

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