Computing the Mittag-Leffler function of a matrix argument

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
João R. Cardoso
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引用次数: 0

Abstract

It is well-known that the two-parameter Mittag-Leffler (ML) function plays a key role in Fractional Calculus. In this paper, we address the problem of computing this function, when its argument is a square matrix. Effective methods for solving this problem involve the computation of higher order derivatives or require the use of mixed precision arithmetic. In this paper, we provide an alternative method that is derivative-free and works entirely using IEEE standard double precision arithmetic. If certain conditions are satisfied, our method uses a Taylor series representation for the ML function; if not, it switches to a Schur-Parlett technique that will be combined with the Cauchy integral formula. A detailed discussion on the choice of a convenient contour is included. Theoretical and numerical issues regarding the performance of the proposed algorithm are discussed. A set of numerical experiments shows that our novel approach is competitive with the state-of-the-art method for IEEE double precision arithmetic, in terms of accuracy and CPU time. For matrices whose Schur decomposition has large blocks with clustered eigenvalues, our method far outperforms the other. Since our method does not require the efficient computation of higher order derivatives, it has the additional advantage of being easily extended to other matrix functions (e.g., special functions).

Abstract Image

计算矩阵参数的 Mittag-Leffler 函数
众所周知,双参数 Mittag-Leffler (ML) 函数在分数微积分中起着关键作用。在本文中,我们将讨论当其参数为方阵时计算该函数的问题。解决这一问题的有效方法涉及计算高阶导数或需要使用混合精度运算。在本文中,我们提供了另一种方法,它不需要导数,完全使用 IEEE 标准双精度算术。如果满足某些条件,我们的方法将使用 ML 函数的泰勒级数表示法;如果不满足这些条件,我们的方法将转而使用 Schur-Parlett 技术,该技术将与 Cauchy 积分公式相结合。我们将详细讨论如何选择方便的等值线。还讨论了有关所提算法性能的理论和数值问题。一组数值实验表明,就精度和 CPU 时间而言,我们的新方法与最先进的 IEEE 双精度算术方法相比具有竞争力。对于舒尔分解具有大块聚类特征值的矩阵,我们的方法远远优于其他方法。由于我们的方法不需要高效计算高阶导数,因此还具有易于扩展到其他矩阵函数(如特殊函数)的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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