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  Impact of basic network motifs on the collective response to perturbations

Bao, X., Hu, Q., Ji, P., Lin, W., Kurths, J., & Nagler, J. (2022). Impact of basic network motifs on the collective response to perturbations. Nature Communications, 13:. doi:10.1038/s41467-022-32913-w.

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資料種別: 学術論文

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bao_2022_s41467-022-32913-w.pdf (出版社版), 2MB
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bao_2022_s41467-022-32913-w.pdf
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 作成者:
Bao, Xiaoge1, 著者
Hu, Qitong1, 著者
Ji, Peng1, 著者
Lin, Wei1, 著者
Kurths, Jürgen2, 著者              
Nagler, Jan1, 著者
所属:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 要旨: Many collective phenomena such as epidemic spreading and cascading failures in socioeconomic systems on networks are caused by perturbations of the dynamics. How perturbations propagate through networks, impact and disrupt their functions may depend on the network, the type and location of the perturbation as well as the spreading dynamics. Previous work has analyzed the retardation effects of the nodes along the propagation paths, suggesting a few transient propagation "scaling” regimes as a function of the nodes’ degree, but regardless of motifs such as triangles. Yet, empirical networks consist of motifs enabling the proper functioning of the system. Here, we show that basic motifs along the propagation path jointly determine the previously proposed scaling regimes of distance-limited propagation and degree-limited propagation, or even cease their existence. Our results suggest a radical departure from these scaling regimes and provide a deeper understanding of the interplay of self-dynamics, interaction dynamics, and topological properties.

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言語: eng - 英語
 日付: 2022-09-082022-09-08
 出版の状態: Finally published
 ページ: 8
 出版情報: -
 目次: -
 査読: 査読あり
 識別子(DOI, ISBNなど): DOI: 10.1038/s41467-022-32913-w
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Working Group: Network- and machine-learning-based prediction of extreme events
OATYPE: Gold Open Access
 学位: -

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出版物 1

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出版物名: Nature Communications
種別: 学術雑誌, SCI, Scopus, p3, oa
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出版社, 出版地: -
ページ: - 巻号: 13 通巻号: 5301 開始・終了ページ: - 識別子(ISBN, ISSN, DOIなど): CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals354
Publisher: Nature