학술논문

Emergence of chaotic cluster synchronization in heterogeneous networks
Document Type
Working Paper
Source
Chaos 33, 091103 (2023)
Subject
Nonlinear Sciences - Adaptation and Self-Organizing Systems
Condensed Matter - Disordered Systems and Neural Networks
Mathematics - Dynamical Systems
Nonlinear Sciences - Chaotic Dynamics
Nonlinear Sciences - Pattern Formation and Solitons
37D99, 37E10, 37M05, 37N20, 37C05, 37C75, 82B44
J.2
G.1.2
Language
Abstract
Many real-world complex systems rely on cluster synchronization to function properly. A cluster of nodes exhibits synchronous behavior while others behave erratically. Predicting the emergence of these clusters and understanding the mechanism behind their structure and variation in response to parameter change is a daunting task in networks that lack symmetry. We unravel the mechanism for the emergence of cluster synchronization in heterogeneous random networks. We develop a heterogeneous mean field approximation together with a self-consistent theory to determine the onset and stability of the cluster. Our analysis shows that cluster synchronization occurs in a wide variety of heterogeneous networks, node dynamics, and coupling functions. The results could lead to a new understanding of the dynamical behavior of networks ranging from neural to social.
Comment: 7 pages, 3 figures