Higher-order interactions lead to ‘reluctant’ synchrony breaking

To model dynamical systems on networks with higher-order (non-pairwise) interactions, we recently introduced a new class of ordinary differential equations (ODEs) on hypernetworks. Here, we consider one-parameter synchrony breaking bifurcations in such ODEs. We call a synchrony breaking steady-state branch ‘reluctant’ if it is tangent to a synchrony space, but does not lie inside it. We prove that reluctant synchrony breaking is ubiquitous in hypernetwork systems, by constructing a large class of examples that support it. We also give an explicit formula for the order of tangency to the synchrony space of a reluctant steady-state branch.

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Publication Details

Journal
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
Published
2024-11-01
DOI
https://doi.org/10.1098/rspa.2023.0945
Citations
2
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
0.69

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article

Higher-order interactions lead to ‘reluctant’ synchrony breaking

Bob Rink, Eddie Nijholt, Sören von der Gracht
2 citations
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
Neural dynamics and brain function
0.69
article

Higher-order interactions lead to ‘reluctant’ synchrony breaking

Bob Rink, Eddie Nijholt, Sören von der Gracht
article en
2 citations

Abstract

To model dynamical systems on networks with higher-order (non-pairwise) interactions, we recently introduced a new class of ordinary differential equations (ODEs) on hypernetworks. Here, we consider one-parameter synchrony breaking bifurcations in such ODEs. We call a synchrony breaking steady-state branch ‘reluctant’ if it is tangent to a synchrony space, but does not lie inside it. We prove that reluctant synchrony breaking is ubiquitous in hypernetwork systems, by constructing a large class of examples that support it. We also give an explicit formula for the order of tangency to the synchrony space of a reluctant steady-state branch.

Proceedings of the Royal Society A Mathematical Physical and Engineering SciencesVol. 480(2301)
Paderborn University (DE), Imperial College London (GB), Vrije Universiteit Amsterdam (NL)
Deutsche Forschungsgemeinschaft, Instituto Serrapilheira
Openalex Percentile: Top 30%
Neural dynamics and brain function
0.69
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Higher-order interactions lead to ‘reluctant’ synchrony breaking — Bob Rink, Eddie Nijholt, et al. · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (2024) | TGRS Research Map | TGRS