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Network susceptibilities: Theory and applications

MPS-Authors
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Manik,  Debsankha
Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Ronellenfitsch,  Henrik
Max Planck Research Group Physics of Biological Organization, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Zhang,  Xiaozhu
Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Hallerberg,  Sarah
Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Timme,  Marc
Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Citation

Manik, D., Rohden, M., Ronellenfitsch, H., Zhang, X., Hallerberg, S., Witthaut, D., et al. (2017). Network susceptibilities: Theory and applications. Physical Review E, 95(1): 012319. doi:10.1103/PhysRevE.95.012319.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002C-7B8E-4
Abstract
We introduce the concept of network susceptibilities quantifying the response of the collective dynamics of a network to small parameter changes. We distinguish two types of susceptibilities: vertex susceptibilities and edge susceptibilities, measuring the responses due to changes in the properties of units and their interactions, respectively. We derive explicit forms of network susceptibilities for oscillator networks close to steady states and offer example applications for Kuramoto-type phase-oscillator models, power grid models, and generic flow models. Focusing on the role of the network topology implies that these ideas can be easily generalized to other types of networks, in particular those characterizing flow, transport, or spreading phenomena. The concept of network susceptibilities is broadly applicable and may straightforwardly be transferred to all settings where networks responses of the collective dynamics to topological changes are essential.