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  Probabilistic Behavioral Distance and Tuning - Reducing and aggregating complex systems

Hellmann, F., Zolotarevskaia, E., Kurths, J., Raisch, J. (2023): Probabilistic Behavioral Distance and Tuning - Reducing and aggregating complex systems. - Journal of Physics: Complexity, 4, 2, 025007.
https://doi.org/10.1088/2632-072X/acccc9

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???ViewItemFull_lblCiteItemAs???: https://publications.pik-potsdam.de/pubman/item/item_28348 ???ViewItemFull_lblCiteItemVersionAs???: https://publications.pik-potsdam.de/pubman/item/item_28348_2
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https://publications.pik-potsdam.de/pubman/item/item_28348_2/component/file_28366/28348oa.pdf
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https://creativecommons.org/licenses/by/4.0/

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 ???ViewItemFull_lblCreators???:
Hellmann, Frank1, ???ENUM_CREATORROLE_AUTHOR???           
Zolotarevskaia, Ekaterina1, ???ENUM_CREATORROLE_AUTHOR???           
Kurths, Jürgen1, ???ENUM_CREATORROLE_AUTHOR???           
Raisch, Jörg2, ???ENUM_CREATORROLE_AUTHOR???
???ViewItemFull_lblAffiliations???:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 ???ViewItemFull_lblAbstract???: Given two dynamical systems, we quantify how similar they are with respect to their interaction with the outside world. We focus on the case where simpler systems act as a specification for a more complex one. Combining a behavioral and probabilistic perspective we define several useful notions of the distance of a system to a specification. We show that these distances can be used to tune a complex system. We demonstrate that our approach can successfully make non-linear networked systems behave like much smaller networks, allowing us to aggregate large sub-networks into one or two effective nodes. Finally, we discuss similarities and differences between our approach and H∞ model reduction.

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???ViewItemFull_lblLanguages???: eng - English
 ???ViewItemFull_lblDates???: 2023-04-132023-04-132023-04-27
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_DOI???: 10.1088/2632-072X/acccc9
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???ENUM_IDENTIFIERTYPE_PIKDOMAIN???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_WORKINGGROUP???: Dynamics, stability and resilience of complex hybrid infrastructure networks
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Complex Networks
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Energy
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Nonlinear Dynamics
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???ViewItemFull_lblSourceTitle???: Journal of Physics: Complexity
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???ENUM_IDENTIFIERTYPE_PUBLISHER???: IOP Publishing