2017-05-01
Continuation of probability density functions using a generalized Lyapunov approach
Publication
Publication
Journal of Computational Physics , Volume 336 p. 627- 643
Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining probability density functions of systems of stochastic partial differential equations near fixed points, under a small noise approximation. Key innovation is the efficient solution of a generalized Lyapunov equation using an iterative method involving low-rank approximations. We apply and illustrate the capabilities of the method using a problem in physical oceanography, i.e. the occurrence of multiple steady states of the Atlantic Ocean circulation.
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| doi.org/10.1016/j.jcp.2017.02.021 | |
| Journal of Computational Physics | |
| Organisation | Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands |
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Baars, S., Viebahn, J., Mulder, T. E., Kuehn, C., Wubs, F., & Dijkstra, H. A. (2017). Continuation of probability density functions using a generalized Lyapunov approach. Journal of Computational Physics, 336, 627–643. doi:10.1016/j.jcp.2017.02.021 |
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