System crash as dynamics of complex networks

Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage t...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 113; no. 42; pp. 11726 - 11731
Main Authors Yu, Yi, Xiao, Gaoxi, Zhou, Jie, Wang, Yubo, Wang, Zhen, Kurths, Jürgen, Schellnhuber, Hans Joachim
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 18.10.2016
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Summary:Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the “peculiar” dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.
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1Y.Y., G.X., and Z.W. contributed equally to this work.
Author contributions: Y.Y., G.X., J.Z., Y.W., Z.W., J.K., and H.J.S. designed research; Y.Y., G.X., J.Z., Y.W., and Z.W. performed research; and Y.Y., G.X., Z.W., J.K., and H.J.S. wrote the paper.
Reviewers: Y.-C.L., Arizona State University; and M.P., University of Maribor.
Contributed by Hans Joachim Schellnhuber, August 11, 2016 (sent for review June 8, 2016; reviewed by Ying-Cheng Lai and Matjaz Perc)
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1612094113