First-passage problem for stochastic differential equations with combined 
parametric Gaussian and Lévy white noises via path integral method

Zan, Wanrong; Xu, Yong; Metzler, Ralf; Kurths, Jürgen

doi:10.1016/j.jcp.2021.110264

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First-passage problem for stochastic differential equations with combined parametric Gaussian and Lévy white noises via path integral method

Zan, W., Xu, Y., Metzler, R., Kurths, J. (2021): First-passage problem for stochastic differential equations with combined parametric Gaussian and Lévy white noises via path integral method. - Journal of Computational Physics, 435, 110264.
https://doi.org/10.1016/j.jcp.2021.110264

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_25807 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_25807_1

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Zan, Wanrong¹, Author
Xu, Yong¹, Author
Metzler, Ralf¹, Author
Kurths, Jürgen², Author

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1External Organizations, ou_persistent22
2Potsdam Institute for Climate Impact Research, ou_persistent13

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Abstract: We study the first-passage problem for a process governed by a stochastic differential equation (SDE) driven simultaneously by both parametric Gaussian and Lévy white noises. We extend the path integral (PI) method to solve the SDE with this combined noise input and the corresponding fractional Fokker-Planck-Kolmogorov equations. Then, the PI solutions are modified to analyze the first-passage problem. Finally, numerical examples based on Monte Carlo simulations verify the extension of the PI method and the modification of the PI solutions. The detailed effects of the system parameters on the first-passage problem are analyzed.

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Dates: Published Online: 2021-03-04Finally published : 2021-03-04

Publication Status: Finally published

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Rev. Type: Peer

Identifiers: DOI: 10.1016/j.jcp.2021.110264
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Tipping Elements
Organisational keyword: RD4 - Complexity Science

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Title: Journal of Computational Physics

Source Genre: Journal, SCI, Scopus

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Pages: - Volume / Issue: 435 Sequence Number: 110264 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journal-computational-physics
Publisher: Elsevier