Abstract
Two fast L1 time-stepping methods, including the backward Euler and stabilized semi-implicit schemes, are suggested for the time-fractional Allen-Cahn equation with Caputo’s derivative. The time mesh is refined near the initial time to resolve the intrinsically initial singularity of solution, and unequal time steps are always incorporated into our approaches so that a adaptive time-stepping strategy can be used in long-time simulations. It is shown that the proposed schemes using the fast L1 formula preserve the discrete maximum principle. Sharp error estimates reflecting the time regularity of solution are established by applying the discrete fractional Grönwall inequality and global consistency analysis. Numerical experiments are presented to show the effectiveness of our methods and to confirm our analysis.
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Acknowledgements
The authors would like to thank Profs. Jia Zhao and Yuezheng Gong for their valuable discussions and fruitful suggestions. The authors are very grateful to anonymous referees for their invaluable comments and suggestions.
Funding
Hong-lin Liao is financially supported by a grant 1008-56SYAH18037 from NUAA Scientific Research Starting Fund of Introduced Talent. Luming Zhang is financially supported by the research grants No. 11571181 from National Natural Science Foundation of China.
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Appendix. Discrete fractional Grönwall lemma
Appendix. Discrete fractional Grönwall lemma
We recall the recently developed discrete fractional Grönwall inequality in [26], which is applicable for any nonuniform time meshes and suitable for a variety of discrete fractional derivatives having a discrete form of \({\sum }_{k=1}^{n}A_{n-k}^{(n)}\triangledown _{\tau } v^{k}\). The following fractional Grönwall lemma, involving the well-known Mittag–Leffler function \(E_{\alpha }(z):={\sum }_{k=0}^{\infty }\frac {z^{k}}{\Gamma (1+k\alpha )}\), gathers three previous (slightly simplified) results from [26, Lemma 2.2, Theorems 3.1 and 3.2].
Lemma A.1
For n = 1, 2,⋯ ,N, assume that the discrete convolution kernels \(\{A_{n-k}^{(n)}\}_{k=1}^{n}\) satisfy the following two assumptions:
Ass1. There is a constant πa > 0 such that \(A_{n-k}^{(n)}\geq \frac {1}{\pi _{a}}{\int \limits }_{t_{k-1}}^{t_{k}}\frac {\omega _{1-\alpha }(t_{n}-s)}{\tau _{k}} s\) for \(1\leqslant k\leqslant n\).
Ass2. The discrete kernels are monotone, i.e., \(A_{n-k-1}^{(n)}-A_{n-k}^{(n)}\geq 0\) for \(1\leqslant k\leqslant n-1\).
Define also a sequence of discrete complementary convolution kernels \(\{p_{n-j}^{(n)}\}_{j=1}^{n}\) by
Then the discrete complementary kernels \(p^{(n)}_{n-j}\ge 0\) are well-defined and fulfill
Suppose that the offset parameter \(0 \leqslant \nu <1\), λ is a nonnegative constant independent of the time steps and the maximum step size \(\tau \le 1/\sqrt [\alpha ]{2{\Gamma }(2-\alpha )\lambda \pi _{a}}.\) If the nonnegative sequences \((v^{k})_{k=0}^{N}\), \((\xi ^{k})_{k=1}^{N}\) and \((\eta ^{k})_{k=1}^{N}\) satisfy
then it holds that, for 1 ≤ n ≤ N,
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Ji, B., Liao, Hl. & Zhang, L. Simple maximum principle preserving time-stepping methods for time-fractional Allen-Cahn equation. Adv Comput Math 46, 37 (2020). https://doi.org/10.1007/s10444-020-09782-2
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DOI: https://doi.org/10.1007/s10444-020-09782-2
Keywords
- Time-fractional Allen-Cahn equation
- Fast L1 formula
- Discrete maximum principle
- Sharp error estimate
- Adaptive time-stepping strategy