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arXiv:1404.2463math.NA

Fast and highly accurate computation of Chebyshev expansion coefficients of analytic functions

Haiyong Wang, Daan Huybrechs

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

Chebyshev expansion coefficients can be computed efficiently by using the FFT, and for smooth functions the resulting approximation is close to optimal, with computations that are numerically stable. Given sufficiently accurate function samples, the Chebyshev expansion coefficients can be computed to machine precision accuracy. However, the accuracy is only with respect to absolute error, and this implies that very small expansion coefficients typically have very large relative error. Upon differentiating a Chebyshev expansion, this relative error in the small coefficients is magnified and accuracy may be lost, especially after repeated differentiation. At first sight, this seems unavoidable. Yet, in this paper, we focus on an alternative computation of Chebyshev expansion coefficients using contour integrals in the complex plane. The main result is that the coefficients can be computed with machine precision relative error, rather than absolute error. This implies that even very small coefficients can be computed with full floating point accuracy, even when they are themselves much smaller than machine precision. As a result, no accuracy is lost after differentiating the expansion, and even the 100th derivative of an analytic function can be computed with near machine precision accuracy using standard floating point arithmetic. In some cases, the contour integrals can be evaluated using the FFT, making the approach both highly accurate and fast.

arXiv comments
Journal reference
DOI
Subjects
math.NANumerical Analysis

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Linked by 1 identifiable commenter in 2 comments across 2 threads, from Oct 2015 to May 2017.

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Discussed in comments2 threads

    • (Disclaimer: I’m not a numerical analyst or hardware expert.) I’m not sure if you can use a dot product unit like the one in your link to make as much of a difference when handling recurrences like “Clenshaw’s algorithm” for evaluating Chebyshev polynomials (the method used in…

      jacobolusView on HNParent context

  1. Hack the derivative 1 comment
    • Yay for functions which are analytic in some neighborhood. Here’s the original paper from the 60s about the idea in this post: http://www.math.fsu.edu/~okhanmoh/media/Lyness,%20Moler,%20S... The latest work on this general topic is http://arxiv.org/pdf/1404.2463.pdf which…

      jacobolusView on HNParent context

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