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  Interaction control to synchronize non-synchronizable networks.

Schröder, M., Chakraborty, S., Witthaut, D., Nagler, J., & Timme, M. (2016). Interaction control to synchronize non-synchronizable networks. Scientific Reports, 6: 37142. doi:10.1038/srep37142.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-BE3D-A Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-405E-6
Genre: Journal Article

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https://www.nature.com/articles/srep37142 (Publisher version)
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 Creators:
Schröder, Malte1, Author              
Chakraborty, S., Author
Witthaut, D., Author
Nagler, J., Author
Timme, Marc2, Author              
Affiliations:
1Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063295              
2Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063286              

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Free keywords: Complex networks; Nonlinear phenomena
 Abstract: Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks' exact interaction topology and consequently have implications for biological and self-organizing technical systems.

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Language(s): eng - English
 Dates: 2016-11-17
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1038/srep37142
 Degree: -

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Title: Scientific Reports
Source Genre: Journal
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Pages: 7 Volume / Issue: 6 Sequence Number: 37142 Start / End Page: - Identifier: -