title: Synchronization in interacting populations of heterogeneous oscillators with time-varying coupling.
abstract: In many networks of interest (including technological, biological, and social networks), the connectivity between the interacting elements is not static, but changes in time. Furthermore, the elements themselves are often not identical, but rather display a variety of behaviors, and may come in different classes. Here, we investigate the dynamics of such systems. Specifically, we study a network of two large interacting heterogeneous populations of limit-cycle oscillators whose connectivity switches between two fixed arrangements at a particular frequency. We show that for sufficiently high switching frequency, this system behaves as if the connectivity were static and equal to the time average of the switching connectivity. We also examine the mechanisms by which this fast-switching limit is approached in several nonintuitive cases. The results illuminate novel mechanisms by which synchronization can arise or be thwarted in large populations of coupled oscillators with nonstatic coupling.
authors.affiliation: Department of Physics & Astronomy, The Center for Neural Dynamics, and The Krasnow Institute for Advanced Study, George Mason University, Fairfax, Virginia 22030, USA. paso@gmu.edu
authors.forename: Paul
authors.initials: P
authors.lastname: So
authors.forename: Bernard C
authors.initials: BC
authors.lastname: Cotton
authors.forename: Ernest
authors.initials: E
authors.lastname: Barreto
mesh_terms: D000465:Algorithms; D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D005246:Feedback; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008962:Models, Theoretical; D009415:Nerve Net / Q000502:physiology*; D017711:Nonlinear Dynamics; D009991:Oscillometry / Q000379:methods*