Numer. Math. Theor. Meth. Appl., 15 (2022), pp. 565-591.
Published online: 2022-07
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In this paper, we analyze the spectra of the preconditioned matrices arising from discretized multi-dimensional Riesz spatial fractional diffusion equations. The finite difference method is employed to approximate the multi-dimensional Riesz fractional derivatives, which generates symmetric positive definite ill-conditioned multi-level Toeplitz matrices. The preconditioned conjugate gradient method with a preconditioner based on the sine transform is employed to solve the resulting linear system. Theoretically, we prove that the spectra of the preconditioned matrices are uniformly bounded in the open interval $(\frac{1}{2},\frac{3}{2})$ and thus the preconditioned conjugate gradient method converges linearly within an iteration number independent of the discretization step-size. Moreover, the proposed method can be extended to handle ill-conditioned multi-level Toeplitz matrices whose blocks are generated by functions with zeros of fractional order. Our theoretical results fill in a vacancy in the literature. Numerical examples are presented to show the convergence performance of the proposed preconditioner that is better than other preconditioners.
}, issn = {2079-7338}, doi = {https://doi.org/10.4208/nmtma.OA-2022-0032}, url = {http://global-sci.org/intro/article_detail/nmtma/20807.html} }In this paper, we analyze the spectra of the preconditioned matrices arising from discretized multi-dimensional Riesz spatial fractional diffusion equations. The finite difference method is employed to approximate the multi-dimensional Riesz fractional derivatives, which generates symmetric positive definite ill-conditioned multi-level Toeplitz matrices. The preconditioned conjugate gradient method with a preconditioner based on the sine transform is employed to solve the resulting linear system. Theoretically, we prove that the spectra of the preconditioned matrices are uniformly bounded in the open interval $(\frac{1}{2},\frac{3}{2})$ and thus the preconditioned conjugate gradient method converges linearly within an iteration number independent of the discretization step-size. Moreover, the proposed method can be extended to handle ill-conditioned multi-level Toeplitz matrices whose blocks are generated by functions with zeros of fractional order. Our theoretical results fill in a vacancy in the literature. Numerical examples are presented to show the convergence performance of the proposed preconditioner that is better than other preconditioners.