This title appears in the Scientific Report :
2019
Please use the identifier:
http://hdl.handle.net/2128/24322 in citations.
Please use the identifier: http://dx.doi.org/10.1126/sciadv.aav1027 in citations.
Fluctuation-induced distributed resonances in oscillatory networks
Fluctuation-induced distributed resonances in oscillatory networks
Across physics, biology, and engineering, the collective dynamics of oscillatory networks often evolve into self-organized operating states. How such networks respond to external fluctuating signals fundamentally underlies their function, yet is not well understood. Here, we present a theory of dyna...
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Personal Name(s): | Zhang, Xiaozhu (Corresponding author) |
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Hallerberg, Sarah / Matthiae, Moritz / Witthaut, Dirk / Timme, Marc | |
Contributing Institute: |
Systemforschung und Technologische Entwicklung; IEK-STE |
Published in: | Science advances, 5 (2019) 7, S. eaav1027 |
Imprint: |
Washington, DC [u.a.]
Assoc.
2019
|
PubMed ID: |
31392264 |
DOI: |
10.1126/sciadv.aav1027 |
Document Type: |
Journal Article |
Research Program: |
Helmholtz Young Investigators Group "Efficiency, Emergence and Economics of future supply networks" Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.1126/sciadv.aav1027 in citations.
Across physics, biology, and engineering, the collective dynamics of oscillatory networks often evolve into self-organized operating states. How such networks respond to external fluctuating signals fundamentally underlies their function, yet is not well understood. Here, we present a theory of dynamic network response patterns and reveal how distributed resonance patterns emerge in oscillatory networks once the dynamics of the oscillatory units become more than one-dimensional. The network resonances are topology specific and emerge at an intermediate frequency content of the input signals, between global yet homogeneous responses at low frequencies and localized responses at high frequencies. Our analysis reveals why these patterns arise and where in the network they are most prominent. These results may thus provide general theoretical insights into how fluctuating signals induce response patterns in networked systems and simultaneously help to develop practical guiding principles for real-world network design and control. |