A sharp $\alpha$-robust $L1$ scheme on graded meshes for two-dimensional time tempered fractional Fokker-Planck equation
Can Wang, Weihua Deng, Xiangong Tang

TL;DR
This paper develops a robust numerical scheme for solving two-dimensional time tempered fractional Fokker-Planck equations, achieving high accuracy and stability on graded meshes, and verifies its effectiveness through numerical experiments.
Contribution
It introduces a sharp $ ext{α}$-robust $L1$ scheme on graded meshes that handles solution singularities and maintains stability as $ ext{α}$ approaches 1, with proven convergence and error estimates.
Findings
The scheme achieves the error order $ ext{O}( au^{ ext{min}\{2- ext{α}, r ext{α} ight\")
The constant multipliers do not blow up as $ ext{α}$ approaches 1.
Numerical experiments confirm the scheme's effectiveness and convergence order.
Abstract
In this paper, we are concerned with the numerical solution for the two-dimensional time fractional Fokker-Planck equation with tempered fractional derivative of order . Although some of its variants are considered in many recent numerical analysis papers, there are still some significant differences. Here we first provide the regularity estimates of the solution. And then a modified 1 scheme inspired by the middle rectangle quadrature formula on graded meshes is employed to compensate for the singularity of the solution at , while the five-point difference scheme is used in space. Stability and convergence are proved in the sence of norm, then a sharp error estimate is derived on graded meshes. Furthermore, unlike the bounds proved in the previous works, the constant multipliers in our analysis…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFractional Differential Equations Solutions · Differential Equations and Numerical Methods · Mathematical functions and polynomials
