Quantifying the parameter dependent basin of the unsafe regime of asymmetric 
Lévy-noise-induced critical transitions

Ma, Jinzhong; Xu, Yong; Li, Yongge; Tian, Ruilan; Ma, Shaojuan; Kurths, Jürgen

doi:10.1007/s10483-021-2672-8

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学術論文

Quantifying the parameter dependent basin of the unsafe regime of asymmetric Lévy-noise-induced critical transitions

Authors

Ma, Jinzhong
External Organizations;

Xu, Yong
External Organizations;

Li, Yongge
External Organizations;

Tian, Ruilan
External Organizations;

Ma, Shaojuan
External Organizations;

/persons/resource/Juergen.Kurths

Kurths, Jürgen
Potsdam Institute for Climate Impact Research;

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Ma2021_Article_QuantifyingTheParameterDepende.pdf
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引用

Ma, J., Xu, Y., Li, Y., Tian, R., Ma, S., & Kurths, J. (2021). Quantifying the parameter dependent basin of the unsafe regime of asymmetric Lévy-noise-induced critical transitions. Applied Mathematics and Mechanics, 42(1), 65-84. doi:10.1007/s10483-021-2672-8.

引用: https://publications.pik-potsdam.de/pubman/item/item_25477

要旨

In real systems, the unpredictable jump changes of the random environment can induce the critical transitions (CTs) between two non-adjacent states, which are more catastrophic. Taking an asymmetric Lévy-noise-induced tri-stable model with desirable, sub-desirable, and undesirable states as a prototype class of real systems, a prediction of the noise-induced CTs from the desirable state directly to the undesirable one is carried out. We first calculate the region that the current state of the given model is absorbed into the undesirable state based on the escape probability, which is named as the absorbed region. Then, a new concept of the parameter dependent basin of the unsafe regime (PDBUR) under the asymmetric Lévy noise is introduced. It is an efficient tool for approximately quantifying the ranges of the parameters, where the noise-induced CTs from the desirable state directly to the undesirable one may occur. More importantly, it may provide theoretical guidance for us to adopt some measures to avert a noise-induced catastrophic CT.