Pointwise error estimates and local superconvergence of Jacobi expansions

Abstract

As one myth of polynomial interpolation and quadrature, Trefethen [30] revealed that the Chebyshev interpolation of |x-a| (with |a|<1 ) at the Clenshaw-Curtis points exhibited a much smaller error than the best polynomial approximation (in the maximum norm) in about 95\% range of [-1,1] except for a small neighbourhood near the singular point x=a. In this paper, we rigorously show that the Jacobi expansion for a more general class of -functions also enjoys such a local convergence behaviour. Our assertion draws on the pointwise error estimate using the reproducing kernel of Jacobi polynomials and the Hilb-type formula on the asymptotic of the Bessel transforms. We also study the local superconvergence and show the gain in order and the subregions it occurs. As a by-product of this new argument, the undesired n-factor in the pointwise error estimate for the Legendre expansion recently stated in Babuska and Hakula [5] can be removed. Finally, all these estimates are extended to the functions with boundary singularities. We provide ample numerical evidences to demonstrate the optimality and sharpness of the estimates.

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