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Backward error analysis of polynomial approximations for computing the action of the matrix exponential

机译:用于计算矩阵指数作用的多项式逼近的向后误差分析

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We describe how to perform the backward error analysis for the approximation of exp(A) v by p(s(-1) A)(s)v, for any given polynomial p(x). The result of this analysis is an optimal choice of the scaling parameter s which assures a bound on the backward error, i.e. the equivalence of the approximation with the exponential of a slightly perturbed matrix. Thanks to the SageMath package expbea we have developed, one can optimize the performance of the given polynomial approximation. On the other hand, we employ the package for the analysis of polynomials interpolating the exponential function at so called Leja-Hermite points. The resulting method for the action of the matrix exponential can be considered an extension of both Taylor series approximation and Leja point interpolation. We illustrate the behavior of the new approximation with several numerical examples.
机译:我们描述了对于任何给定的多项式p(x),如何对p(s(-1)A)(s)v近似exp(A)v进行向后误差分析。该分析的结果是缩放参数s的最佳选择,其确保了后向误差的边界,即近似近似与微扰矩阵的指数相等。多亏了我们开发的SageMath软件包expbea,可以优化给定多项式逼近的性能。另一方面,我们使用该软件包来分析在所谓的Leja-Hermite点处插值指数函数的多项式。得出的用于矩阵指数作用的方法可以视为泰勒级数逼近和Leja点插值的扩展。我们用几个数值示例来说明新近似的行为。

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