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- W2894923857 abstract "In this article, we propose and analyze some efficient numerical methods for the solution of a class of stiff stochastic partial differential equations (SPDEs) with additive noise. First, we apply the polynomial chaos (PC) expansion to treat the randomness, which results to a set of deterministic stiff PDEs. Then this system of PDEs is discretized in space by the Fourier pseudo‐spectral method, enabling us to use the FFT algorithm to reduce computational cost efficiently. To overcome the instability in discretizing time component of resulting system of ordinary differential equations (ODEs), we apply the exponential time differencing (ETD), integrating factor Runge‐Kutta (IFRK) and modified exponential time differencing Runge‐Kutta (ETDRKB) methods. We also analyze the strong error bound of numerical approximation in a framework of Lipschitz nonlinearities for the method based on the ETDRKB scheme. Some numerical experiments are included to demonstrate the performance and convergence of methods. Numerical results show that the method based on the ETDRKB scheme is more efficient for stiff SPDEs." @default.
- W2894923857 created "2018-10-12" @default.
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- W2894923857 date "2018-10-05" @default.
- W2894923857 modified "2023-09-29" @default.
- W2894923857 title "Convergence of a method based on the exponential integrator and Fourier spectral discretization for stiff stochastic PDEs" @default.
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- W2894923857 doi "https://doi.org/10.1002/mma.5290" @default.
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