Fast procedures for Caputo fractional derivative and its applications to ordinary and partial differential equations

TL;DR

This paper introduces fast computational methods for solving equations with Caputo fractional derivatives, significantly reducing complexity and memory usage in discretized differential equations, with demonstrated accuracy through numerical experiments.

Contribution

The paper presents novel fast algorithms leveraging Toeplitz structure and FFT for efficient solution of fractional differential equations, improving computational speed and memory efficiency.

Findings

Reduced computational complexity from O(N^3) to O(N log^2 N)

Lowered memory requirements from O(N^2) to O(N)

Validated accuracy through numerical experiments

Abstract

In this paper, we develop fast procedures for solving linear systems arising from discretization of ordinary and partial differential equations with Caputo fractional derivative w.r.t time variable. First, we consider a finite difference scheme to solve a two-sided fractional ordinary equation. Furthermore, we present a fast solution technique to accelerate Toeplitz matrix-vector multiplications arising from finite difference discretization. This fast solution technique is based on a fast Fourier transform and depends on the special structure of coefficient matrices, and it helps to reduce the computational work from $O(N^{3})$ required by traditional methods to $O(Nlog^{2}N)$ and the memory requirement from $O(N^{2})$ to $O(N)$ without using any lossy compression, where $N$ is the number of unknowns. Two finite difference schemes to solve time fractional hyperbolic equations with different fractional order $\gamma$ are considered. We present a fast solution technique depending on the special structure of coefficient matrices by rearranging the order of unknowns. It helps to reduce the computational work from $O(N^2M)$ required by traditional methods to $O(N$log$^{2}N)$ and the memory requirement from $O(NM)$ to $O(N)$ without using any lossy compression, where $N=\tau^{-1}$ and $\tau$ is the size of time step, $M=h^{-1}$ and $h$ is the size of space step. Importantly, a fast method is employed to solve the classical time fractional diffusion equation with a lower coast at $O(MN$log$^2N)$, where the direct method requires an overall computational complexity of $O(N^2M)$. Moreover, the applicability and accuracy of the scheme are demonstrated by numerical experiments to support our theoretical analysis.