Fast Fourier-like Mapped Chebyshev Spectral-Galerkin Methods for PDEs with Integral Fractional Laplacian in Unbounded Domains

TL;DR

This paper introduces a fast spectral-Galerkin method using Fourier-like mapped Chebyshev functions for efficiently solving PDEs with integral fractional Laplacian in unbounded domains, achieving quasi-optimal complexity.

Contribution

The paper develops a novel spectral-Galerkin approach that diagonalizes the fractional Laplacian, significantly reducing computational complexity for solving fractional PDEs.

Findings

Method achieves quasi-optimal $O((N\log_2N)^d)$ complexity.

Numerical tests confirm convergence matches theoretical error estimates.

Applicable to nonlinear fractional PDEs like fractional nonlinear Schrödinger equation.

Abstract

In this paper, we propose a fast spectral-Galerkin method for solving PDEs involving integral fractional Laplacian in $\mathbb{R}^d$, which is built upon two essential components: (i) the Dunford-Taylor formulation of the fractional Laplacian; and (ii) Fourier-like bi-orthogonal mapped Chebyshev functions (MCFs) as basis functions. As a result, the fractional Laplacian can be fully diagonalised, and the complexity of solving an elliptic fractional PDE is quasi-optimal, i.e., $O((N\log_2N)^d)$ with $N$ being the number of modes in each spatial direction. Ample numerical tests for various decaying exact solutions show that the convergence of the fast solver perfectly matches the order of theoretical error estimates. With a suitable time-discretization, the fast solver can be directly applied to a large class of nonlinear fractional PDEs. As an example, we solve the fractional nonlinear Schr{\"o}dinger equation by using the fourth-order time-splitting method together with the proposed MCF-spectral-Galerkin method.