Well-Conditioned Galerkin Spectral Method for Two-Sided Fractional Diffusion Equation with Drift

TL;DR

This paper develops well-conditioned Galerkin spectral methods for two-sided fractional diffusion equations with drift, improving numerical stability and applicability to a broader range of fractional orders, with demonstrated effectiveness through numerical experiments.

Contribution

The paper introduces new well-conditioned Galerkin spectral schemes for fractional diffusion equations with drift, extending applicability to fractional orders in (0,2) and reducing condition numbers significantly.

Findings

Reduced condition number from O(N^{2α}) to O(N^{α})

Successfully applied to fractional Laplacian with generalized boundary conditions

Numerical experiments confirm scheme effectiveness and provide insights into abnormal diffusion

Abstract

In this paper, we focus on designing a well-conditioned Glarkin spectral methods for solving a two-sided fractional diffusion equations with drift, in which the fractional operators are defined neither in Riemann-Liouville nor Caputo sense, and its physical meaning is clear. Based on the image spaces of Riemann-Liouville fractional integral operators on $L_p([a,b])$ space discussed in our previous work, after a step by step deduction, three kinds of Galerkin spectral formulations are proposed, the final obtained corresponding scheme of which shows to be well-conditioned---the condition number of the stiff matrix can be reduced from $O(N^{2\alpha})$ to $O(N^{\alpha})$, where $N$ is the degree of the polynomials used in the approximation. Another point is that the obtained schemes can also be applied successfully to approximate fractional Laplacian with generalized homogeneous boundary conditions, whose fractional order $\alpha\in(0,2)$, not only having to be limited to $\alpha\in(1,2)$. Several numerical experiments demonstrate the effectiveness of the derived schemes. Besides, based on the numerical results, we can observe the behavior of mean first exit time, an interesting quantity that can provide us with a further understanding about the mechanism of abnormal diffusion.