Abstract

This article proposes an implicit finite difference scheme for a two-dimensional parabolic stochastic partial differential equation of Zakai type. The scheme is based on a Milstein approximation to the stochastic integral and an alternating direction implicit discretisation of the elliptic term. Mean-square stability and L_2-convergence of first order in time and second order in space are proven by Fourier analysis, in the presence of Dirac initial data. Numerical tests confirm these findings empirically.

Highlights

  • The analysis and numerical computation of Zakai equations and other types of stochastic partial differential equation (SPDE) have been extensively studied in recent years

  • We study the mean-square stability, and the strong convergence of the second moment

  • We combine the scheme with an Alternating Direction Implicit (ADI) factorisation, which has been introduced in [34] for parabolic PDEs to approximately factorise the system matrix by matrices which correspond to derivatives in individual directions and which can more be inverted, while the consistency order is maintained

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Summary

Introduction

The analysis and numerical computation of Zakai equations and other types of stochastic partial differential equation (SPDE) have been extensively studied in recent years. Giles and Reisinger [16] use an explicit Milstein finite difference approximation to the solution of the following one-dimensional SPDE, a special case of (1.1) for d = 1 and constant coefficients, dv. Where T > 0, M is a standard Brownian motion, and μ and 0 ≤ ρ < 1 are real-valued parameters This is extended in [35] to an approximation of (1.6) with an implicit method on the basis of the σ –θ time-stepping scheme, where the finite variation parts of the double stochastic integral are taken implicit. The sharp estimates we derive give a precise description of the error given Dirac initial data This is achieved by a Fourier analysis originating from Carter and Giles in [7], where they estimated the error arising from explicit and implicit approximations of the constant-coefficient 1-d convection–diffusion equation with Dirac initial data.

Semi-implicit Milstein finite difference scheme
Main convergence results
Fourier analysis of mean-square stability
Fourier analysis of L2-convergence
Numerical tests
Conclusions
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