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Computing Exponential for Iterative Splitting Methods: Algorithms and Applications

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  • Jürgen Geiser

Abstract

Iterative splitting methods have a huge amount to compute matrix exponential. Here, the acceleration and recovering of higher-order schemes can be achieved. From a theoretical point of view, iterative splitting methods are at least alternating Picards fix-point iteration schemes. For practical applications, it is important to compute very fast matrix exponentials. In this paper, we concentrate on developing fast algorithms to solve the iterative splitting scheme. First, we reformulate the iterative splitting scheme into an integral notation of matrix exponential. In this notation, we consider fast approximation schemes to the integral formulations, also known as 𠜙 -functions. Second, the error analysis is explained and applied to the integral formulations. The novelty is to compute cheaply the decoupled exp-matrices and apply only cheap matrix-vector multiplications for the higher-order terms. In general, we discuss an elegant way of embedding recently survey on methods for computing matrix exponential with respect to iterative splitting schemes. We present numerical benchmark examples, that compared standard splitting schemes with the higher-order iterative schemes. A real-life application in contaminant transport as a two phase model is discussed and the fast computations of the operator splitting method is explained.

Suggested Citation

  • Jürgen Geiser, 2011. "Computing Exponential for Iterative Splitting Methods: Algorithms and Applications," Journal of Applied Mathematics, Hindawi, vol. 2011, pages 1-27, March.
  • Handle: RePEc:hin:jnljam:193781
    DOI: 10.1155/2011/193781
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    Cited by:

    1. Jürgen Geiser & Eulalia Martínez & Jose L. Hueso, 2020. "Serial and Parallel Iterative Splitting Methods: Algorithms and Applications to Fractional Convection-Diffusion Equations," Mathematics, MDPI, vol. 8(11), pages 1-42, November.
    2. Jürgen Geiser, 2020. "Iterative and Noniterative Splitting Methods of the Stochastic Burgers’ Equation: Theory and Application," Mathematics, MDPI, vol. 8(8), pages 1-28, July.

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