Detection of Functional Communities in Networks of Randomly Coupled Oscillators Using the Dynamic-Mode Decomposition
arXiv:2103.14763 · doi:10.1103/PhysRevE.104.044305
Abstract
Dynamic-mode decomposition (DMD) is a versatile framework for model-free analysis of time series that are generated by dynamical systems. We develop a DMD-based algorithm to investigate the formation of "functional communities" in networks of coupled, heterogeneous Kuramoto oscillators. In these functional communities, the oscillators in the network have similar dynamics. We consider two common random-graph models (Watts--Strogatz networks and Barabási--Albert networks) with different amounts of heterogeneities among the oscillators. In our computations, we find that membership in a community reflects the extent to which there is establishment and sustainment of locking between oscillators. We construct forest graphs that illustrate the complex ways in which the heterogeneous oscillators associate and disassociate with each other.
References in corpus (7)
- Synchronization in complex networks
- Community detection in networks: A user guide
- Quantifying social group evolution
- Robust Detection of Dynamic Community Structure in Networks
- Paths to Synchronization on Complex Networks
- Dynamical Systems on Networks: A Tutorial
- Modern Koopman Theory for Dynamical Systems