ISSN 1088-6842(online) ISSN 0025-5718(print)

Finite difference weights, spectral differentiation, and superconvergence

Authors: Burhan Sadiq and Divakar Viswanath
Journal: Math. Comp. 83 (2014), 2403-2427
MSC (2010): Primary 65D05, 65D25
DOI: https://doi.org/10.1090/S0025-5718-2014-02798-1
Published electronically: January 6, 2014
MathSciNet review: 3223337
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Abstract: Let be a sequence of distinct grid points. A finite difference formula approximates the -th derivative as , with being the weight at . We derive an algorithm for finding the weights which uses fewer arithmetic operations and less memory than the algorithm in current use (Fornberg, Mathematics of Computation, vol. 51 (1988), pp. 699-706). The algorithm we derive uses fewer arithmetic operations by a factor of in the limit of large . The optimized C++ implementation we describe is a hundred to five hundred times faster than MATLAB. The method of Fornberg is faster by a factor of five in MATLAB, however, and thus remains the most attractive option for MATLAB users.

The algorithm generalizes easily to the calculation of spectral differentiation matrices, or equivalently, finite difference weights at several different points with a fixed grid. Unlike the algorithm in current use for the calculation of spectral differentiation matrices, the algorithm we derive suffers from no numerical instability.

The order of accuracy of the finite difference formula for with grid points , , is typically . However, the most commonly used finite difference formulas have an order of accuracy that is higher than normal. For instance, the centered difference approximation
to has an order of accuracy equal to not . Even unsymmetric finite difference formulas can exhibit such superconvergence or boosted order of accuracy, as shown by the explicit algebraic condition that we derive. If the grid points are real, we prove a basic result stating that the order of accuracy can never be boosted by more than .

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Additional Information

Burhan Sadiq
Affiliation: Department of Mathematics, University of Michigan, Ann Arbor, Michigan 48109
Email: bsadiq@umich.edu

Divakar Viswanath
Affiliation: Department of Mathematics, University of Michigan, Ann Arbor, Michigan 48109
Email: divakar@umich.edu

DOI: https://doi.org/10.1090/S0025-5718-2014-02798-1
Received by editor(s): July 20, 2012
Received by editor(s) in revised form: December 22, 2012, and January 17, 2013
Published electronically: January 6, 2014
Additional Notes: The authors were supported by NSF grants DMS-0715510, DMS-1115277, and SCREMS-1026317.
Article copyright: © Copyright 2014 American Mathematical Society