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  Predictability of critical transitions

Zhang, X., Kuehn, C., & Hallerberg, S. (2015). Predictability of critical transitions. Physical Review E, 92(5): 052905. doi:10.1103/PhysRevE.92.052905.

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 Creators:
Zhang, Xiaozhu1, Author              
Kuehn, Christian, Author
Hallerberg, Sahra2, Author              
Affiliations:
1Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063295              
2Max Planck Institute for the Physics of Complex Systems, Max Planck Society, ou_2117288              

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 Abstract: Critical transitions in multistable systems have been discussed as models for a variety of phenomena ranging from the extinctions of species to socioeconomic changes and climate transitions between ice ages and warm ages. From bifurcation theory we can expect certain critical transitions to be preceded by a decreased recovery from external perturbations. The consequences of this critical slowing down have been observed as an increase in variance and autocorrelation prior to the transition. However, especially in the presence of noise, it is not clear whether these changes in observation variables are statistically relevant such that they could be used as indicators for critical transitions. In this contribution we investigate the redictability of critical transitions in conceptual models. We study the quadratic integrate-and-fire model and the van der Pol model under the influence of external noise. We focus especially on the statistical analysis of the success of predictions and the overall predictability of the system. The performance of different indicator variables turns out to be dependent on the specific model under study and the conditions of accessing it. Furthermore, we study the influence of the magnitude of transitions on the predictive performance.

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Language(s): eng - English
 Dates: 2015-11-062015-11
 Publication Status: Published in print
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1103/PhysRevE.92.052905
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Title: Physical Review E
Source Genre: Journal
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Pages: 14 Volume / Issue: 92 (5) Sequence Number: 052905 Start / End Page: - Identifier: ISSN: 1539-3755