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Strong convergence of the finite element method with truncated noise for semilinear parabolic stochastic equations with additive noise

机译:具有加性噪声的半线性抛物型随机方程组的截断噪声有限元方法的强收敛性

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We consider a semilinear parabolic PDE driven by additive noise.The equation is discretized in space by a standard piecewise linear finite element method. We show that the orthogonal expansion of the finitedimensional Wiener process, that appears in the discretized problem, can be truncated severely without losing the asymptotic order of the method, provided that the kernel of the covariance operator of the Wiener process is smooth enough. For example, if the covariance operator is given by the Gauss kernel, then the number of terms to be kept is the quasi-logarithm of the number of terms in the original expansion. Then one can reduce the size of the corresponding linear algebra problem enormously and hence reduce the computational complexity, which is a key issue when stochastic problems are simulated.
机译:我们考虑了由加性噪声驱动的半线性抛物线PDE。方程是通过标准分段线性有限元方法在空间上离散的。我们表明,只要维纳过程的协方差算子的核足够光滑,就可以在不丢失该方法的渐近阶的情况下严重截断离散问题中出现的有限维维纳过程的正交展开。例如,如果协方差算子是由高斯核给出的,那么要保留的项数就是原始扩展项中项数的准对数。这样就可以极大地减少相应线性代数问题的大小,从而降低计算复杂度,这是模拟随机问题时的关键问题。

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