Fast algorithms for the multi-dimensional Jacobi polynomial transform

Abstract

We use the well-known observation that the solutions of Jacobi's differential equation can be represented via the non-oscillatory phase and amplitude functions to develop a fast algorithm for computing multi-dimensional Jacobi polynomial transforms. More explicitly, it follows from this observation that the matrix corresponding to the discrete Jacobi transform is the Hadamard product of a numerically low-rank matrix and a multi-dimensional discrete Fourier transform (DFT) matrix. The application of the Hadamard product can be carried out via r d fast Fourier transforms (FFTs), where r = O( log n log log n ) and d is the dimension, resulting in a nearly optimal algorithm to compute the multidimensional Jacobi polynomial transform.