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Asymptotic error distribution of accelerated exponential Euler method for parabolic SPDEs
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The asymptotic error distribution of numerical methods applied to stochastic ordinary differential equations has been well studied, which characterizes the evolution pattern of the error distribution in the small step-size regime. It is still open for stochastic partial differential equations whether the normalized error process of numerical methods admits a nontrivial limit distribution. We answer this question by presenting the asymptotic error distribution of the temporal accelerated exponential Euler (AEE) method when applied to parabolic stochastic partial differential equations. In order to overcome the difficulty caused by the infinite-dimensional setting, we establish a uniform approximation theorem for convergence in distribution. Based on it, we derive the limit distribution of the normalized error process of the AEE method by studying the limit distribution of its certain appropriate finite-dimensional approximation process. As applications of our main result, the asymptotic error distribution of a fully discrete AEE method for the original equation and that of the AEE method for a stochastic ordinary differential equation are also obtained.
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Asymptotic error distribution for stochastic Runge--Kutta methods of strong order one
The normalized error of strong-order-one stochastic Runge-Kutta methods converges to a linear-SDE limit process, and a coefficient-defined parameter eta1 connects weak order two to smaller long-time mean-square error.
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