How to enhance adaptive synchronization capability via higher-order network structures?

How to reduce the control costs and then enhance synchronization capability is one of the current highly anticipated issues. Based on Lyapunov stability theory, this paper derives a sufficient condition for ensuring adaptive synchronization in higher-order dynamic networks, where the first-order interactions and the second-order interactions are represented by edges and 2-simplices, respectively. Three different kinds of higher-order networks are constructed, named Erdős-Rényi simplicial complex (ERSC), Watts-Strogatz simplicial complex (WSSC), and Barabási-Albert simplicial complex (BASC). Subsequently, the first- and the second-order degree distributions of these networks are then discussed. Finally, numerical simulations validate the theoretical analyses and yield the following key findings: Smaller scale or smaller coupling strengths can save control costs and reduce energy consumption across all three networks. Increasing the number of 2-simplices, ERSC demonstrates the best adaptive synchronization capability. When varying the coupling strengths or the number of 2-simplices, WSSC has stronger robustness than ERSC and BASC.

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Publication Details

Journal
Chaos An Interdisciplinary Journal of Nonlinear Science
Published
2026-02-01
DOI
https://doi.org/10.1063/5.0308966
Primary Topic
Neural Networks Stability and Synchronization
Type
article
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article

How to enhance adaptive synchronization capability via higher-order network structures?

Jia Hu, Qiuyue Zhao, Lilan Tu
Chaos An Interdisciplinary Journal of Nonlinear Science
Neural Networks Stability and Synchronization
article

How to enhance adaptive synchronization capability via higher-order network structures?

Jia Hu, Qiuyue Zhao, Lilan Tu
article en

Abstract

How to reduce the control costs and then enhance synchronization capability is one of the current highly anticipated issues. Based on Lyapunov stability theory, this paper derives a sufficient condition for ensuring adaptive synchronization in higher-order dynamic networks, where the first-order interactions and the second-order interactions are represented by edges and 2-simplices, respectively. Three different kinds of higher-order networks are constructed, named Erdős-Rényi simplicial complex (ERSC), Watts-Strogatz simplicial complex (WSSC), and Barabási-Albert simplicial complex (BASC). Subsequently, the first- and the second-order degree distributions of these networks are then discussed. Finally, numerical simulations validate the theoretical analyses and yield the following key findings: Smaller scale or smaller coupling strengths can save control costs and reduce energy consumption across all three networks. Increasing the number of 2-simplices, ERSC demonstrates the best adaptive synchronization capability. When varying the coupling strengths or the number of 2-simplices, WSSC has stronger robustness than ERSC and BASC.

Chaos An Interdisciplinary Journal of Nonlinear ScienceVol. 36(2)
Wuhan University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 58%
Neural Networks Stability and Synchronization
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How to enhance adaptive synchronization capability via higher-order network structures? — Jia Hu, Qiuyue Zhao, et al. · Chaos An Interdisciplinary Journal of Nonlinear Science (2026) | TGRS Research Map | TGRS