Approximation error of the Lagrange reconstructing polynomial

Abstract

The reconstruction approach [Shu C.W.: {\em SIAM Rev.} {\bf 51} (2009) 82--126] for the numerical approximation of $f^{\prime }(x)$ is based on the construction of a dual function $h(x)$ whose sliding averages over the interval $[x-\frac{1}{2}\Delta x,x+\frac{1}{2}\Delta x]$ are equal to $f(x)$ (assuming an homogeneous grid of cell-size $\Delta x$). We study the deconvolution problem [Harten A., Engquist B., Osher S., Chakravarthy S.R.: {\em J. Comp. Phys.} {\bf 71} (1987) 231--303] which relates the Taylor polynomials of $h(x)$ and $f(x)$, and obtain its explicit solution, by introducing rational numbers ${\tau }_n$ defined by a recurrence relation, or determined by their generating function, $g_{\tau }(x)$, related with the reconstruction pair of ${\mathrm{e}}^x$. We then apply these results to the specific case of Lagrange-interpolation-based polynomial reconstruction, and determine explicitly the approximation error of the Lagrange reconstructing polynomial (whose sliding averages are equal to the Lagrange interpolating polynomial) on an arbitrary stencil defined on a homogeneous grid.

31 pages, 1 table; revised version to appear in J. Approx. Theory

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