Abstract

The master stability function is a powerful tool for determining synchrony in high-dimensional networks of coupled limit cycle oscillators. In part, this approach relies on the analysis of a low-dimensional variational equation around a periodic orbit. For smooth dynamical systems, this orbit is not generically available in closed form. However, many models in physics, engineering and biology admit to non-smooth piece-wise linear caricatures, for which it is possible to construct periodic orbits without recourse to numerical evolution of trajectories. A classic example is the McKean model of an excitable system that has been extensively studied in the mathematical neuroscience community. Understandably, the master stability function cannot be immediately applied to networks of such non-smooth elements. Here, we show how to extend the master stability function to non-smooth planar piece-wise linear systems, and in the process demonstrate that considerable insight into network dynamics can be obtained. In illustration, we highlight an inverse period-doubling route to synchrony, under variation in coupling strength, in globally linearly coupled networks for which the node dynamics is poised near a homoclinic bifurcation. Moreover, for a star graph, we establish a mechanism for achieving so-called remote synchronisation (where the hub oscillator does not synchronise with the rest of the network), even when all the oscillators are identical. We contrast this with node dynamics close to a non-smooth Andronov–Hopf bifurcation and also a saddle node bifurcation of limit cycles, for which no such bifurcation of synchrony occurs.

Highlights

  • Real world networks such as those found in the brain, heart, World Wide Web, geoeconomic structures and ecologies show wonderfully rich emergent behaviour

  • There has been an appreciation for some time in the applied sciences, in engineering and biology, of the benefits of studying caricature systems built from piece-wise linear and possibly discontinuous dynamical systems

  • To illustrate the application of the theory, we have considered global linearly coupled networks and used this to highlight the importance that local node dynamics can have on network states

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Summary

Introduction

Real world networks such as those found in the brain, heart, World Wide Web, geoeconomic structures and ecologies show wonderfully rich emergent behaviour. We augment the master stability function (MSF) approach to treat networks of non-smooth dynamical elements. This is sufficiently broad that we can discuss three distinct oscillator models that exemplify (i) a saddle node bifurcation of limit cycles, (ii) a non-smooth Andronov–Hopf bifurcation and (iii) a homoclinic bifurcation. As an application of this new form of MSF, we consider global and star linearly coupled networks in Section 5 and contrast the stability properties of the synchronous state for each of the oscillator models (i)–(iii).

Piece-wise linear models
The McKean model
The absolute model
A model with a homoclinic loop
Floquet theory
Extending the master stability function
Global and star graph connectivities
Discussion
Full Text
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