Mittag--Leffler stability of numerical solutions to time fractional ODEs
Dongling Wang, Jun Zou

TL;DR
This paper proves that certain numerical methods for linear and semi-linear time fractional ODEs preserve the Mittag-Leffler stability, ensuring polynomial decay rates similar to the continuous solutions, supported by theoretical analysis and numerical experiments.
Contribution
It establishes the Mittag-Leffler stability preservation of specific numerical schemes for time fractional ODEs, extending stability results to semi-linear cases with perturbations.
Findings
Numerical schemes preserve the polynomial decay rate of solutions.
Strong A-stable F-LMMs are Mittag-Leffler stable for semi-linear F-ODEs.
Numerical experiments confirm theoretical decay rates.
Abstract
The asymptotic stable region and long-time decay rate of solutions to linear homogeneous Caputo time fractional ordinary differential equations (F-ODEs) are known to be completely determined by the eigenvalues of the coefficient matrix. Very different from the exponential decay of solutions to classical ODEs, solutions of F-ODEs decay only polynomially, leading to the so-called Mittag-Leffler stability, which was already extended to semi-linear F-ODEs with small perturbations. This work is mainly devoted to the qualitative analysis of the long-time behavior of numerical solutions. By applying the singularity analysis of generating functions developed by Flajolet and Odlyzko (SIAM J. Disc. Math. 3 (1990), 216-240), we are able to prove that both 1 scheme and strong -stable fractional linear multistep methods (F-LMMs) can preserve the numerical Mittag-Leffler stability for…
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 · Nonlinear Differential Equations Analysis
