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Optimal explicit stabilized integrator of weak order one for stiff and ergodic stochastic differential equations

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Published in SIAM/ASA Journal on Uncertainty Quantification. 2018, vol. 6, no. 2, p. 937-964
Abstract A new explicit stabilized scheme of weak order one for stiff and ergodic stochastic differential equations (SDEs) is introduced. In the absence of noise, the new method coincides with the classical deterministic stabilized scheme (or Chebyshev method) for diffusion dominated advection-diffusion problems and it inherits its optimal stability domain size that grows quadratically with the number of internal stages of the method. For mean-square stable stiff stochastic problems, the scheme has an optimal extended mean-square stability domain that grows at the same quadratic rate as the deterministic stability domain size in contrast to known existing methods for stiff SDEs [A. Abdulle and T. Li. Commun. Math. Sci., 6(4), 2008, A. Abdulle, G. Vilmart, and K. C. Zygalakis, SIAM J. Sci. Comput., 35(4), 2013]. Combined with postprocessing techniques, the new methods achieve a convergence rate of order two for sampling the invariant measure of a class of ergodic SDEs, achieving a stabilized version of the non-Markovian scheme introduced in [B. Leimkuhler, C. Matthews, and M. V. Tretyakov, Proc. R. Soc. A, 470, 2014].
Keywords Explicit stochastic methodsStabilized methodsPostprocessorInvariant measureErgodicityOrthogonal Runge–Kutta ChebyshevSK-ROCKPSK-ROCK
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Research group Analyse numérique
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ABDULLE, Assyr, ALMUSLIMANI, Ibrahim, VILMART, Gilles. Optimal explicit stabilized integrator of weak order one for stiff and ergodic stochastic differential equations. In: SIAM/ASA Journal on Uncertainty Quantification, 2018, vol. 6, n° 2, p. 937-964. https://archive-ouverte.unige.ch/unige:105971

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Deposited on : 2018-06-28

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