Communications in Mathematical Sciences

Volume 19 (2021)

Number 5

Complete monotonicity-preserving numerical methods for time fractional ODEs

Pages: 1301 – 1336



Lei Li (School of Mathematical Sciences, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, China)

Dongling Wang (School of Mathematics and Computational Science, Xiangtan University, Xiangtan, Hunan, China; and Department of Mathematics and Center for Nonlinear Studies, Northwest University, Xi’an, Shaanxi, China)


The time fractional ODEs are equivalent to convolutional Volterra integral equations with completely monotone kernels. We introduce the concept of complete monotonicity-preserving ($\mathcal{CM}$-preserving) numerical methods for fractional ODEs, in which the discrete convolutional kernels inherit the $\mathcal{CM}$ property as the continuous equations. We prove that $\mathcal{CM}$-preserving schemes are at least $A(\pi / 2)$ stable and can preserve the monotonicity of solutions to scalar nonlinear autonomous fractional ODEs, both of which are novel. Significantly, by improving a result of Li and Liu (Quart. Appl. Math., 76(1):189-198, 2018), we show that the $\mathcal{L}1$ scheme is $\mathcal{CM}$-preserving. The good signs of the coefficients for such class of schemes ensure the discrete fractional comparison principles, and allow us to establish the convergence in a unified framework when applied to time fractional sub-diffusion equations and fractional ODEs. The main tools in the analysis are a characterization of convolution inverses for completely monotone sequences and a characterization of completely monotone sequences using Pick functions due to Liu and Pego (Trans. Amer. Math. Soc. 368(12): 8499-8518, 2016). The results for fractional ODEs are extended to $\mathcal{CM}$-preserving numerical methods for Volterra integral equations with general completely monotone kernels. Numerical examples are presented to illustrate the main theoretical results.


fractional ODEs, complete monotonicity, convolution inverse, Pick function, convergence

2010 Mathematics Subject Classification

34A08, 45E10, 65L05, 65L07

Received 16 June 2020

Accepted 4 January 2021

Published 11 November 2021