English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Deciphering the imprint of topology on nonlinear dynamical network stability

Authors
/persons/resource/jan.nitzbon

Nitzbon,  Jan
Potsdam Institute for Climate Impact Research;

/persons/resource/Paul.Schultz

Schultz,  Paul
Potsdam Institute for Climate Impact Research;

/persons/resource/heitzig

Heitzig,  Jobst
Potsdam Institute for Climate Impact Research;

/persons/resource/Juergen.Kurths

Kurths,  Jürgen
Potsdam Institute for Climate Impact Research;

/persons/resource/frank.hellmann

Hellmann,  Frank
Potsdam Institute for Climate Impact Research;

External Ressource
No external resources are shared
Fulltext (public)

7642oa.pdf
(Publisher version), 14MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Nitzbon, J., Schultz, P., Heitzig, J., Kurths, J., Hellmann, F. (2017): Deciphering the imprint of topology on nonlinear dynamical network stability. - New Journal of Physics, 19, 33029.
https://doi.org/10.1088/1367-2630/aa6321


Cite as: https://publications.pik-potsdam.de/pubman/item/item_21706
Abstract
Coupled oscillator networks show complex interrelations between topological characteristics of the network and the nonlinear stability of single nodes with respect to large but realistic perturbations. We extend previous results on these relations by incorporating sampling-based measures of the transient behaviour of the system, its survivability, as well as its asymptotic behaviour, its basin stability. By combining basin stability and survivability we uncover novel, previously unknown asymptotic states with solitary, desynchronized oscillators which are rotating with a frequency different from their natural one. They occur almost exclusively after perturbations at nodes with specific topological properties. More generally we confirm and significantly refine the results on the distinguished role tree-shaped appendices play for nonlinear stability. We find a topological classification scheme for nodes located in such appendices, that exactly separates them according to their stability properties, thus establishing a strong link between topology and dynamics. Hence, the results can be used for the identification of vulnerable nodes in power grids or other coupled oscillator networks. From this classification we can derive general design principles for resilient power grids. We find that striving for homogeneous network topologies facilitates a better performance in terms of nonlinear dynamical network stability. While the employed second-order Kuramoto-like model is parametrised to be representative for power grids, we expect these insights to transfer to other critical infrastructure systems or complex network dynamics appearing in various other fields.