Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function

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...

Full description

Bibliographic Details
Main Authors: Coombes, Stephen, Thul, Ruediger
Format: Article
Published: Cambridge University Press 2016
Subjects:
Online Access:https://eprints.nottingham.ac.uk/34103/
_version_ 1848794775244767232
author Coombes, Stephen
Thul, Ruediger
author_facet Coombes, Stephen
Thul, Ruediger
author_sort Coombes, Stephen
building Nottingham Research Data Repository
collection Online Access
description 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.
first_indexed 2025-11-14T19:21:33Z
format Article
id nottingham-34103
institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T19:21:33Z
publishDate 2016
publisher Cambridge University Press
recordtype eprints
repository_type Digital Repository
spelling nottingham-341032020-05-04T17:48:18Z https://eprints.nottingham.ac.uk/34103/ Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function Coombes, Stephen Thul, Ruediger 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. Cambridge University Press 2016-12-01 Article PeerReviewed Coombes, Stephen and Thul, Ruediger (2016) Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function. European Journal of Applied Mathematics, 27 (6). pp. 904-922. ISSN 1469-4425 General Applied Mathematics Synchronisation Non-Smooth Equations Complex Networks Neural Networks http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=10256500&fileId=S0956792516000115 doi:10.1017/S0956792516000115 doi:10.1017/S0956792516000115
spellingShingle General Applied Mathematics
Synchronisation
Non-Smooth Equations
Complex Networks
Neural Networks
Coombes, Stephen
Thul, Ruediger
Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function
title Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function
title_full Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function
title_fullStr Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function
title_full_unstemmed Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function
title_short Synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function
title_sort synchrony in networks of coupled non-smooth dynamical systems: extending the master stability function
topic General Applied Mathematics
Synchronisation
Non-Smooth Equations
Complex Networks
Neural Networks
url https://eprints.nottingham.ac.uk/34103/
https://eprints.nottingham.ac.uk/34103/
https://eprints.nottingham.ac.uk/34103/