Skip to main content
Log in

A Runge–Kutta type scheme for nonlinear stochastic partial differential equations with multiplicative trace class noise

  • Original Paper
  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

In this paper a new Runge–Kutta type scheme is introduced for nonlinear stochastic partial differential equations (SPDEs) with multiplicative trace class noise. The proposed scheme converges with respect to the computational effort with a higher order than the well-known linear implicit Euler scheme. In comparison to the infinite dimensional analog of Milstein type scheme recently proposed in Jentzen and Röckner (2012), our scheme is easier to implement and needs less computational effort due to avoiding the derivative of the diffusion function. The new scheme can be regarded as an infinite dimensional analog of Runge–Kutta method for finite dimensional stochastic ordinary differential equations (SODEs). Numerical examples are reported to support the theoretical results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Burrage, K., Burrage, P.M.: High strong order explicit Runge–Kutta methods for stochastic ordinary differential equations. Appl. Numer. Math. 22, 81–101 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  2. Chow, P.L.: Stochastic Partial Differential Equations. Chapman & Hall/CRC, New York (2007)

    MATH  Google Scholar 

  3. Da Prato, G., Zabczyk, J.: Stochastic equations in infinite dimensions. In: Encyclopedia of Mathematics and its Applications, vol. 44. Cambridge University Press, Cambridge (1992)

    Google Scholar 

  4. Grecksch, W., Kloeden, P.E.: Time-discretised Galerkin approximations of parabolic stochastic PDEs. Bull. Aust. Math. Soc. 54(1), 79–85 (1996)

    Article  MathSciNet  Google Scholar 

  5. Gyöngy, I.: Lattice approximations for stochastic quasi-linear parabolic partial differential equations driven by space-time white noise II. Potential Anal. 11(1), 1–37 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  6. Jentzen, A., Kloeden, P.E.: Overcoming the order barrier in the numerical approximation of stochastic partial differential equations with additive space-time noise. Proc. R. Soc. Lond., A Math. Phys. Eng. Sci. 465(2102), 649–667 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  7. Jentzen, A., Kloeden, P.E.: The numerical approximation of stochastic partial differential equations. Milan J. Math. 77(1), 205–244 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  8. Jentzen, A., Röckner, M.: Regularity analysis of stochastic partial differential equations with nonlinear multiplicative trace class noise. J. Differ. Equ. 252(1), 114–136 (2012)

    Article  MATH  Google Scholar 

  9. Jentzen, A., Röckner, M.: A Milstein scheme for SPDEs. Arxiv preprint, arXiv:1001.2751v4 (2012)

  10. Kloeden, P.E., Platen, E.: Numerical Solution of Stochastic Differential Equations. Springer, Berlin (1992)

    MATH  Google Scholar 

  11. Kloeden, P.E., Lord, G.J., Neuenkirch, A., Shardlow, T.: The exponential integrator scheme for stochastic partial differential equations: pathwise error bounds. J. Comput. Appl. Math. 235(5), 1245–1260 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  12. Kovács, M., Larsson, S., Lindgren, F.: Strong convergence of the finite element method with truncated noise for semilinear parabolic stochastic equations with additive noise. Numer. Algorithms 53, 309–320 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  13. Lord, G.J., Rougemont, J.: A numerical scheme for stochastic PDEs with Gevrey regularity. IMA J. Numer. Anal. 24(4), 587–604 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  14. Lord, G.J., Tambue, A.: A modified semi-implict Euler–Maruyama scheme for finite element discretization of SPDEs. arXiv:1004.1998v2 (2010)

  15. Prévôt, C., Röckner, M.: A concise course on stochastic partial differential equations. In: Lecture Notes in Mathematics, vol. 1905. Springer, Berlin (2007)

    Google Scholar 

  16. Shardlow, T.: Numerical methods for stochastic parabolic PDEs. Numer. Funct. Anal. Optim. 20(1–2), 121–145 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  17. Shardlow, T.: Weak convergence of a numerical method for a stochastic heat equation. BIT 43, 179–193 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  18. Yan, Y.: Galerkin finite element methods for stochastic parabolic partial differential equations. SIAM J. Numer. Anal. 43(4), 1363–1384 (2005)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaojie Wang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, X., Gan, S. A Runge–Kutta type scheme for nonlinear stochastic partial differential equations with multiplicative trace class noise. Numer Algor 62, 193–223 (2013). https://doi.org/10.1007/s11075-012-9568-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11075-012-9568-8

Keywords

AMS 2000 Subject Classifications

Navigation