Year: 2026
Type: article
Abstract: Synchronization is a fundamental phenomenon in complex systems, observed across a wide range of natural and engineered contexts. The Kuramoto model provides a foundational framework for understanding synchronization among coupled oscillators, traditionally assuming pairwise interactions. However, many real-world systems exhibit group and many-body interactions, which can be effectively modeled through hypergraphs. Here, we show that the effect of such higher-order interactions on synchronization is non-monotonic. Through a numerical study of higher-order Kuramoto models on random hypergraphs and on globally coupled systems, we find that the degree of synchronization reached from incoherent initial conditions is maximized at small but nonzero higher-order coupling strength: Weak higher-order interactions enhance synchronization when added to pairwise ones, whereas strong ones work against it, in line with earlier reports of reduced basins and of cluster states. We further show, through a cost-constrained allocation analysis, that under a constrained budget for interactions, a mixed allocation of pairwise and higher-order couplings consistently achieves higher synchronization than relying on either type alone. These findings clarify the role of higher-order interactions in shaping collective dynamics and point to design principles for optimizing synchronization in complex systems.
DOI: 10.1063/5.0354134
Authors: Riccardo Muolo, Hiroya Nakao, Marco Coraggio
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Awards: Synchronization dynamics and dimensionality reduction in coupled dynamical systems on hypergraphs, Machine Learning for Prediction and Control of Complex Dynamics Based on Integration of Mathematical and Data-Driven Methods, G8080901651, G8208761268, Systematic extraction of key dynamical structures, prediction, and control of nonlinear systems
OpenAlex ID: W7127437775