Spectral collocation methods and polar coordinate singularities
Journal of Computational Physics
Pole condition for singular problems: the pseudospectral approximation
Journal of Computational Physics
A spectral method for polar coordinates
Journal of Computational Physics
Journal of Computational Physics
SIAM Journal on Computing
Efficient Spectral-Galerkin Methods III: Polar and Cylindrical Geometries
SIAM Journal on Scientific Computing
Pseudospectral Solution of the Two-Dimensional Navier--Stokes Equations in a Disk
SIAM Journal on Scientific Computing
Numerical treatment of polar coordinate singularities
Journal of Computational Physics
A fast spherical harmonics transform algorithm
Mathematics of Computation
Spectral collocation schemes on the unit disc
Journal of Computational Physics
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Navier-Stokes spectral solver in a sphere
Journal of Computational Physics
Journal of Computational Physics
Journal of Computational Physics
Hi-index | 31.46 |
The singularity of cylindrical or spherical coordinate systems at the origin imposes certain regularity conditions on the spectral expansion of any infinitely differentiable function. There are two efficient choices of a set of radial basis functions suitable for discretising the solution of a partial differential equation posed in either such geometry. One choice is methods based on standard Chebyshev polynomials; although these may be efficiently computed using fast transforms, differentiability to all orders of the obtained solution at the origin is not guaranteed. The second is the so-called one-sided Jacobi polynomials that explicitly satisfy the required behavioural conditions. In this paper, we compare these two approaches in their accuracy, differentiability and computational speed. We find that the most accurate and concise representation is in terms of one-sided Jacobi polynomials. However, due to the lack of a competitive fast transform, Chebyshev methods may be a better choice for some computationally intensive timestepping problems and indeed will yield sufficiently (although not infinitely) differentiable solutions provided they are adequately converged.