2016/03/01 by Stefan Ulonska, Iryna Omelchenko, Ulonska, Stefan +5
Computer Science · Neuroscience · #Adaptation and Self-Organizing Systems (nlin.AO) #FOS: Physical sciences #Neural Networks and Reservoir Computing #Neural dynamics and brain function #Nonlinear Dynamics and Pattern Formation
paper · pdf · doi:10.48550/arxiv.1603.00171
openalex publication_date 2016/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Chimera states are complex spatio-temporal patterns that consist of coexisting domains of coherent and incoherent dynamics. We analyse chimera states in networks of Van der Pol oscillators with hierarchical coupling topology. We investigate the stepwise transition from a nonlocal to a hierarchical topology, and propose the network clustering coefficient as a measure to establish a link between the existence of chimera states and the compactness of the initial base pattern of a hierarchical topology; we show that a large clustering coefficient promotes the occurrence of chimeras. Depending on the level of hierarchy and base pattern, we obtain chimera states with different numbers of incoherent domains. We investigate the chimera regimes as a function of coupling strength and nonlinearity parameter of the individual oscillators. The analysis of a network with larger base pattern resulting in larger clustering coefficient reveals two different types of chimera states and highlights the increasing role of amplitude dynamics.