A Weighted Integral-Regularized Finite Difference Scheme for the Tempered Fractional Laplacian
Provides a high-order, efficient numerical scheme for solving equations involving the tempered fractional Laplacian, which is important for modeling anomalous diffusion in physics and finance.
The paper develops a weighted integral-regularized finite difference method for the tempered fractional Laplacian, achieving O(h^{4-α}) convergence for α∈[1,2) in 1D and O(h^{4-α}) truncation error in multiple dimensions, with numerical experiments confirming accuracy and efficiency.
The intrinsic singularity of the tempered fractional Laplacian (TFL) remains a major challenge in developing numerical methods that are simultaneously accurate, efficient, and easy to implement. We develop a weighted integral-regularized finite difference (WIRFD) method that regularizes the singular integrand via a multidimensional Taylor expansion incorporating a smooth window function. The resulting integral is decomposed into a regularized term, which is discretized by a punctured trapezoidal rule, and a directly evaluated correction term. For the multidimensional TFL operator, we derive an $O(h^{4-α})$ truncation error bound in the $l^{\infty}$-norm for $α\in(0,2)$ and $u\in C^s(\mathbb{R}^d)$ with $s\geq 8$ by introducing a smooth auxiliary function together with the aliasing formula. For the one-dimensional TFL equation, we establish stability in both the $l^2$- and $l^{\infty}$-norms and optimal $O(h^{4-α})$ convergence for $α\in[1,2)$ based on the strict diagonal dominance of the discrete matrix and a lower bound for its minimum eigenvalue. The Toeplitz structure of the discrete matrix enables FFT-based matrix-vector multiplication, and the resulting linear systems are solved efficiently by a preconditioned conjugate gradient (PCG) method. Numerical experiments corroborate the theoretical results, demonstrating the accuracy, efficiency, and robustness of the proposed method.