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An efficient numerical approach for stochastic evolution PDEs driven by random diffusion coefficients and multiplicative noise

Xiao Qi, Mejdi Azaïez, Can Huang, Chuanju Xu

2022AIMS Mathematics13 citationsDOIOpen Access PDF

Abstract

<abstract><p>In this paper, we investigate the stochastic evolution equations (SEEs) driven by a bounded $ \log $-Whittle-Mat$ \acute{{\mathrm{e}}} $rn (W-M) random diffusion coefficient field and $ Q $-Wiener multiplicative force noise. First, the well-posedness of the underlying equations is established by proving the existence, uniqueness, and stability of the mild solution. A sampling approach called approximation circulant embedding with padding is proposed to sample the random coefficient field. Then a spatio-temporal discretization method based on semi-implicit Euler-Maruyama scheme and finite element method is constructed and analyzed. An estimate for the strong convergence rate is derived. Numerical experiments are finally reported to confirm the theoretical result.</p></abstract>

Topics & Concepts

MathematicsDiscretizationBounded functionMultiplicative noiseMultiplicative functionApplied mathematicsWiener processUniquenessStability (learning theory)Mathematical analysisBackward Euler methodRandom fieldComputer scienceStatisticsDigital signal processingAnalog signalComputer hardwareMachine learningSignal transfer functionAdvanced Mathematical Modeling in EngineeringStochastic processes and financial applicationsNumerical methods in inverse problems