A Novel and Accurate Finite Difference Method for the Fractional Laplacian and the Fractional Poisson Problem
Abstract
In this paper, we develop a novel finite difference method to discretize the fractional Laplacian (−Δ)α/2 in hypersingular integral form. By introducing a splitting parameter, we formulate the fractional Laplacian as the weighted integral of a weak singular function, which is then approximated by the weighted trapezoidal rule. Compared to other existing methods, our method is more accurate and simpler to implement, and moreover it closely resembles the central difference scheme for the classical Laplace operator. We prove that for u ∈ C3,α/2(R), our method has an accuracy of O(h2) uniformly for any α ∈ (0,2), while for u ∈ C1,α/2(R), the accuracy is O(1-α/2). The convergence behavior of our method is consistent with that of the central difference approximation of the classical Laplace operator. Additionally, we apply our method to solve the fractional Poisson equation and study the convergence of its numerical solutions. The extensive numerical examples that accompany our analysis verify our results, as well as give additional insights into the convergence behavior of our method.
Recommended Citation
S. Duo et al., "A Novel and Accurate Finite Difference Method for the Fractional Laplacian and the Fractional Poisson Problem," Journal of Computational Physics, vol. 355, pp. 233 - 252, Academic Press Inc., Feb 2018.
The definitive version is available at https://doi.org/10.1016/j.jcp.2017.11.011
Department(s)
Mathematics and Statistics
Research Center/Lab(s)
Center for High Performance Computing Research
Keywords and Phrases
Error estimates; Finite difference method; Fractional Laplacian; Fractional Poisson equation; Weighted Montgomery identity; Weighted trapezoidal rule
International Standard Serial Number (ISSN)
0021-9991
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Academic Press Inc., All rights reserved.
Publication Date
01 Feb 2018