We define and analyze preconditioners for the Riesz operator −(−∆)^(α/2) , α ∈ (1, 2] commonly used in fractional models, such as anomalous diffusion. For α close to 2 there are various effective preconditioners at disposal with linear computational cost. Seminal results on treatment of the case α near 1 that still maintains linear computational complexity has been obtained approximating the Riesz operator as a fractional power of a discretized Laplacian, using Gauss-Jacobi formula. In this work, we extend this rational preconditioning approach by leveraging additional quadrature rules with exponential convergence. More precisely, we investigate both sinc and Gauss-Laguerre quadratures and show that, after an opportune choice of the involved parameters, both allow us to construct preconditioners based on a sum of a few shifted Laplacian inverses, and achieve high computational efficiency, ensuring numerical optimality. Several numerical results show that the sinc-based preconditioner is more versatile than the Gauss-Laguerre preconditioner, and that both outperform the Gauss-Jacobi one.
Exploring rational approximations of fractional power operators for preconditioning
Aceto, Lidia;
2026-01-01
Abstract
We define and analyze preconditioners for the Riesz operator −(−∆)^(α/2) , α ∈ (1, 2] commonly used in fractional models, such as anomalous diffusion. For α close to 2 there are various effective preconditioners at disposal with linear computational cost. Seminal results on treatment of the case α near 1 that still maintains linear computational complexity has been obtained approximating the Riesz operator as a fractional power of a discretized Laplacian, using Gauss-Jacobi formula. In this work, we extend this rational preconditioning approach by leveraging additional quadrature rules with exponential convergence. More precisely, we investigate both sinc and Gauss-Laguerre quadratures and show that, after an opportune choice of the involved parameters, both allow us to construct preconditioners based on a sum of a few shifted Laplacian inverses, and achieve high computational efficiency, ensuring numerical optimality. Several numerical results show that the sinc-based preconditioner is more versatile than the Gauss-Laguerre preconditioner, and that both outperform the Gauss-Jacobi one.| File | Dimensione | Formato | |
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