Fast Computation of Orthogonal Systems with a Skew-symmetric Differentiation Matrix
Arieh Iserles, Marcus Webb

TL;DR
This paper introduces a family of orthogonal systems with skew-symmetric, structured differentiation matrices that enable fast computation of expansion coefficients in spectral methods, applicable to functions on the real line and half-line.
Contribution
It characterizes a new family of orthogonal systems with skew-symmetric, tridiagonal differentiation matrices allowing high-accuracy, fast coefficient computation using FFTs, extending spectral methods.
Findings
Coefficients computed as Jacobi polynomial coefficients of a modified function.
Special cases enable use of fast sine and cosine transforms.
Related to a new generalization of Carlitz polynomials.
Abstract
Orthogonal systems in , once implemented in spectral methods, enjoy a number of important advantages if their differentiation matrix is skew-symmetric and highly structured. Such systems, where the differentiation matrix is skew-symmetric, tridiagonal and irreducible, have been recently fully characterised. In this paper we go a step further, imposing the extra requirement of fast computation: specifically, that the first coefficients {of the expansion} can be computed to high accuracy in operations. We consider two settings, one approximating a function directly in and the other approximating and separately in . In each setting we prove that there is a single family, parametrised by , of orthogonal systems with a skew-symmetric, tridiagonal,…
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Taxonomy
TopicsMatrix Theory and Algorithms · Mathematical functions and polynomials · Numerical methods for differential equations
