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      Efficient simulation of nonlinear parabolic SPDEs with additive noise

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          Abstract

          Recently, in a paper by Jentzen and Kloeden [Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci. 465 (2009) 649-667], a new method for simulating nearly linear stochastic partial differential equations (SPDEs) with additive noise has been introduced. The key idea was to use suitable linear functionals of the noise process in the numerical scheme which allow a higher approximation order to be obtained. Following this approach, a new simplified version of the scheme in the above named reference is proposed and analyzed in this article. The main advantage of the convergence result given here is the higher convergence order for nonlinear parabolic SPDEs with additive noise, although the used numerical scheme is very simple to simulate and implement.

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          Strong and weak divergence in finite time of Euler's method for stochastic differential equations with non-globally Lipschitz continuous coefficients

          The stochastic Euler scheme is known to converge to the exact solution of a stochastic differential equation with globally Lipschitz continuous drift and diffusion coefficient. Recent results extend this convergence to coefficients which grow at most linearly. For superlinearly growing coefficients finite-time convergence in the strong mean square sense remained an open question according to [Higham, Mao & Stuart (2002); Strong convergence of Euler-type methods for nonlinear stochastic differential equations, SIAM J. Numer. Anal. 40, no. 3, 1041-1063]. In this article we answer this question to the negative and prove for a large class of stochastic differential equations with non-globally Lipschitz continuous coefficients that Euler's approximation converges neither in the strong mean square sense nor in the numerically weak sense to the exact solution at a finite time point. Even worse, the difference of the exact solution and of the numerical approximation at a finite time point diverges to infinity in the strong mean square sense and in the numerically weak sense.
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            Overcoming the order barrier in the numerical approximation of stochastic partial differential equations with additive space-time noise

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              Finite Element Methods for Parabolic Stochastic PDE?s

              J Walsh (2005)
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                Author and article information

                Journal
                31 October 2012
                Article
                10.1214/10-AAP711
                1210.8320
                e8a3ebd9-6887-4e94-9965-a2a54b0aac51

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                IMS-AAP-AAP711
                Annals of Applied Probability 2011, Vol. 21, No. 3, 908-950
                Published in at http://dx.doi.org/10.1214/10-AAP711 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
                math.PR math.NA
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