Polynomial approximation on $C^2$-domains
Feng Dai, Andriy Prymak

TL;DR
This paper develops new tools to precisely measure smoothness of functions on $C^2$-domains, enabling optimal polynomial approximation results in various $L_p$ spaces, with broad applicability beyond convex domains.
Contribution
It introduces a novel computable modulus of smoothness based on finite differences, establishing direct and inverse polynomial approximation inequalities on $C^2$-domains.
Findings
Established Jackson inequality for all $0<p extless=\infty$
Proved inverse inequality for $1 extless p extless=\infty$
Developed Whitney type estimates for directional moduli of smoothness
Abstract
We introduce appropriate computable moduli of smoothness to characterize the rate of best approximation by multivariate polynomials on a connected and compact -domain . This new modulus of smoothness is defined via finite differences along the directions of coordinate axes, and along a number of tangential directions from the boundary. With this modulus, we prove both the direct Jackson inequality and the corresponding inverse for best polynomial approximation in . The Jackson inequality is established for the full range of , while its proof relies on (i) Whitney type estimates with constants depending only on certain parameters; and (ii) highly localized polynomial partitions of unity on a -domain. Both (i) and (ii) are of independent interest. In particular, our Whitney type estimate (i) is established for directional…
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Taxonomy
TopicsAdvanced Mathematical Modeling in Engineering · Mathematical Approximation and Integration · Mathematical Analysis and Transform Methods
