Building hierarchies of semiclassical Jacobi polynomials for spectral methods in annuli

Fuente: arXiv
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Auteurs principaux: Papadopoulos, Ioannis P. A., Gutleb, Timon S., Slevinsky, Richard M., Olver, Sheehan
Format: Preprint
Publié: 2023
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author Papadopoulos, Ioannis P. A.
Gutleb, Timon S.
Slevinsky, Richard M.
Olver, Sheehan
author_facet Papadopoulos, Ioannis P. A.
Gutleb, Timon S.
Slevinsky, Richard M.
Olver, Sheehan
contents We discuss computing with hierarchies of families of (potentially weighted) semiclassical Jacobi polynomials which arise in the construction of multivariate orthogonal polynomials. In particular, we outline how to build connection and differentiation matrices with optimal complexity and compute analysis and synthesis operations in quasi-optimal complexity. We investigate a particular application of these results to constructing orthogonal polynomials in annuli, called the generalised Zernike annular polynomials, which lead to sparse discretisations of partial differential equations. We compare against a scaled-and-shifted Chebyshev--Fourier series showing that in general the annular polynomials converge faster when approximating smooth functions and have better conditioning. We also construct a sparse spectral element method by combining disk and annulus cells, which is highly effective for solving PDEs with radially discontinuous variable coefficients and data.
format Preprint
id arxiv_https___arxiv_org_abs_2310_07541
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Building hierarchies of semiclassical Jacobi polynomials for spectral methods in annuli
Papadopoulos, Ioannis P. A.
Gutleb, Timon S.
Slevinsky, Richard M.
Olver, Sheehan
Numerical Analysis
33C45, 33C50, 65D05, 65N35
We discuss computing with hierarchies of families of (potentially weighted) semiclassical Jacobi polynomials which arise in the construction of multivariate orthogonal polynomials. In particular, we outline how to build connection and differentiation matrices with optimal complexity and compute analysis and synthesis operations in quasi-optimal complexity. We investigate a particular application of these results to constructing orthogonal polynomials in annuli, called the generalised Zernike annular polynomials, which lead to sparse discretisations of partial differential equations. We compare against a scaled-and-shifted Chebyshev--Fourier series showing that in general the annular polynomials converge faster when approximating smooth functions and have better conditioning. We also construct a sparse spectral element method by combining disk and annulus cells, which is highly effective for solving PDEs with radially discontinuous variable coefficients and data.
title Building hierarchies of semiclassical Jacobi polynomials for spectral methods in annuli
topic Numerical Analysis
33C45, 33C50, 65D05, 65N35
url https://arxiv.org/abs/2310.07541