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dc.contributor.authorZhao, Chen
dc.contributor.authorWang, Wen-Xu
dc.contributor.authorLiu, Yang-Yu
dc.contributor.authorSlotine, Jean-Jacques E.
dc.date.accessioned2015-04-08T19:36:30Z
dc.date.available2015-04-08T19:36:30Z
dc.date.issued2015-02
dc.date.submitted2014-11
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/1721.1/96474
dc.description.abstractControlling complex networked systems to desired states is a key research goal in contemporary science. Despite recent advances in studying the impact of network topology on controllability, a comprehensive understanding of the synergistic effect of network topology and individual dynamics on controllability is still lacking. Here we offer a theoretical study with particular interest in the diversity of dynamic units characterized by different types of individual dynamics. Interestingly, we find a global symmetry accounting for the invariance of controllability with respect to exchanging the densities of any two different types of dynamic units, irrespective of the network topology. The highest controllability arises at the global symmetry point, at which different types of dynamic units are of the same density. The lowest controllability occurs when all self-loops are either completely absent or present with identical weights. These findings further improve our understanding of network controllability and have implications for devising the optimal control of complex networked systems in a wide range of fields.en_US
dc.language.isoen_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/srep08422en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNature Publishing Groupen_US
dc.titleIntrinsic dynamics induce global symmetry in network controllabilityen_US
dc.typeArticleen_US
dc.identifier.citationZhao, Chen, Wen-Xu Wang, Yang-Yu Liu, and Jean-Jacques Slotine. “Intrinsic Dynamics Induce Global Symmetry in Network Controllability.” Sci. Rep. 5 (February 12, 2015): 8422.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Nonlinear Systems Laboratoryen_US
dc.contributor.mitauthorSlotine, Jean-Jacques E.en_US
dc.relation.journalScientific Reportsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsZhao, Chen; Wang, Wen-Xu; Liu, Yang-Yu; Slotine, Jean-Jacquesen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-7161-7812
mit.licensePUBLISHER_CCen_US


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