Finite Difference Approximation for Linear Stochastic Partial Differential Equations with Method of Lines

McDonald, Stuart (2006): Finite Difference Approximation for Linear Stochastic Partial Differential Equations with Method of Lines.

Abstract

A stochastic partial differential equation, or SPDE, describes the dynamics of a stochastic process defined on a space-time continuum. This paper provides a new method for solving SPDEs based on the method of lines (MOL). MOL is a technique that has largely been used for numerically solving deterministic partial differential equations (PDEs). MOL works by transforming the PDE into a system of ordinary differential equations (ODEs) by discretizing the spatial dimension of the PDE. The resulting system of ODEs is then solved by application of either a finite difference or a finite element method. This paper provides a proof that the MOL can be used to provide a finite difference approximation of the boundary value solutions for two broad classes of linear SPDEs, the linear elliptic and parabolic SPDEs.

• Item Type: MPRA Paper
• Institution: Social and Information Systems Laboratory, California Institute of Technology
• Language: English
• Keywords: Finite difference approximation; linear stochastic partial differential equations (SPDEs); the method of lines (MOL)
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling

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