Abstract
In 1986, Dixon and McKee (Z Angew Math Mech 66:535–544, 1986) developed a discrete fractional Gronwall inequality, which can be seen as a generalization of the classical discrete Gronwall inequality. However, this generalized discrete Gronwall inequality and its variant (Al-Maskari and Karaa in SIAM J Numer Anal 57:1524–1544, 2019) have not been widely applied in the numerical analysis of the time-stepping methods for the time-fractional evolution equations. The main purpose of this paper is to show how to apply the generalized discrete Gronwall inequality to prove the convergence of a class of time-stepping numerical methods for time-fractional nonlinear subdiffusion equations, including the popular fractional backward difference type methods of order one and two, and the fractional Crank-Nicolson type methods. We obtain the optimal \(L^2\) error estimate in space discretization for multi-dimensional problems. The convergence of the fast time-stepping numerical methods is also proved in a simple manner. The present work unifies the convergence analysis of several existing time-stepping schemes. Numerical examples are provided to verify the effectiveness of the present method.
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Acknowledgements
This work has been supported by the National Natural Science Foundation of China (12001326, 12171283, 12120101001), Natural Science Foundation of Shandong Province (ZR2021ZD03, ZR2020QA032, ZR2019ZD42), China Postdoctoral Science Foundation (BX20190191, 2020M672038), the startup fund from Shandong University (11140082063130). GEK would like to acknowledge support by the MURI/ARO on Fractional PDEs for Conservation Laws and Beyond: Theory, Numerics and Applications (W911NF-15-1-0562).
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Appendices
Appendix A. Proof of \(c_n\ge 0\) for the BN-\(\theta \) method
The BN-\(\theta \) method reduces to the FBDF-2 method for \(\theta =0\) and to the GNGF-2 for \(\theta = 1/2\). In this section, we prove \(c_n\ge 0\) for the BN-\(\theta \) method when \(0\le \theta \le 1/2\).
Firstly, we give the proof of the following lemma.
Lemma A.1
For \(a^{(-\alpha )}_n=\frac{\varGamma (n+\alpha )}{\varGamma (\alpha )\varGamma (n+1)}\) and \(0< \alpha < 1\), we have
Proof
From \(a^{(-\alpha )}_n=\frac{\varGamma (n+\alpha )}{\varGamma (\alpha )\varGamma (n+1)}\), we obtain \(a_{n}^{(-\alpha -1)}-a_{n}^{(-\alpha )} =\frac{n}{\alpha }a_{n}^{(-\alpha )}\) and
Eq. (8.3) implies \( \frac{a^{(-\alpha )}_{n}}{a^{(-\alpha )}_{n-j}} =\prod _{k=n-j}^{n-1}\frac{a^{(-\alpha )}_{k+1}}{a^{(-\alpha )}_k} \ge \left( \frac{1+\alpha }{2}\right) ^j\), which completes the proof of (8.1). Obviously, (8.2) holds for \(n=0,1\). From (8.4), we obtain \(a_{n}^{(-\alpha -1)}-a_{n}^{(-\alpha )} \le \left( \frac{2+\alpha }{2}\right) ^{n-2}(a_{2}^{(-\alpha -1)}-a_{2}^{(-\alpha )}) =(\alpha +1)\left( \frac{2+\alpha }{2}\right) ^{n-2}\). The proof complete. \(\square \)
For \( 0\le \theta \le 1/2\), we have the following properties:
where we used
Proof
From (2.19) and (4.2), we have \(c_n= 2b_0{a}^{(-\alpha )}_n -\sum _{j=0}^{n}{b}_j{a}^{(-\alpha )}_{n-j},\) where \(b_n\) is given by (4.3).
Step 1) Prove \(c_n\ge 0\) for \(n\ge 3\). Let
By (4.3), (8.10), (8.2), and \(\sum _{j=1}^{n-1} a_{j}^{(-\alpha )}=a_{n}^{(-\alpha -1)}-1-a_n^{(-\alpha )}\), we have
From (8.1), we have \(\lambda ^{1-n}a_n^{(-\alpha )}/\alpha \ge 1\) for \(n\ge 1\). Hence,
where we used \(\rho _1\le 1/3\), \(\rho _2/\lambda <1\), and \(\rho _3/\lambda <1\). Direct calculation yields
Combining (8.6), (8.7), (8.12), (8.13), and (8.14), yields
From (8.5), we have
Combining (8.15) and (8.16) yields
where we used \({a_{n-1}^{(-\alpha )}} \le \frac{n}{n-1+\alpha }{a_{n}^{(-\alpha )}} \le \frac{3}{2+\alpha }{a_{n}^{(-\alpha )}}\) for \(n\ge 3\).
Using (8.9), we obtain
which leads to
From (8.11), \(a_j^{(-\alpha )}\le a_2^{(-\alpha )}=\alpha (1+\alpha )/2\), and the following inequality,
we obtain
Combining (8.17) and (8.19) yields
which leads to
Step 2) Prove \(c_n> 0\) for \(n=0,1,2\). Obviously, \(c_0= 2b_0 - {b}_0\ge b_0 >0\) and
where we used (8.16). By (8.5) and (8.9), we obtain
From the above inequality and (8.16), we have
The proof is complete. \(\square \)
Appendix B. Proofs of Lemmas 3 and 7
Proof of Lemma 3
For \(\sigma \ge 0\), (3.4) follows from
Next, we prove (3.4) for \(\sigma <0\).
For \(n\ge 2\), there exists \(j_n=\lceil n/2 \rceil \) and \(x_0=j_n/n \in (0,1)\) such that
Using \(\sum _{j=1}^{n-1}j^{-\alpha -1}\lesssim 1\) and \(\sum _{j=1}^{n-1}j^{\sigma } \lesssim n^{\sigma +1}\log (n)\) completes the proof of (3.4).
By \(0\le a_{n}^{(-\alpha )}\lesssim n^{\alpha -1}\), one has
Repeating the proof of (3.4) finishes the proof of (3.5). The proof is completed. \(\square \)
Proof of Lemma 7
The condition (2.5) and Lemma 1 yield the following linear system
which leads to
Combining (3.8), Lemma 3, \(\omega _n^{(\alpha )}=O(n^{-\alpha -1})\), (2.20), and (8.20) leads to
Combining (3.2), (3.5), and (8.21) yields (3.15), which ends the proof. \(\square \)
Appendix C. Proof of Theorem 3
Proof
We show a sketch of the proof. Let \(\theta ^n={}_Fu_{h}^n-u_h^n\). By (5.6), (2.15), and \(\theta ^n=\varepsilon _{n}=0\) for \(0\le n \le n_0-1\), we obtain
Similar to (3.19), we can obtain the equivalent form of (8.22) as
where \({\widetilde{F}}^n=f({}_Fu^{n}_h)-f(u^{n}_h))\), and
By \(\omega _{n}^{(\alpha )}=O(n^{-\alpha -1})\) and (3.4), we can easily obtain
By the boundedness of \(\Vert u_h^n\Vert \), \(b_n=O(n^{-\alpha -1})\), and \(\omega _n^{(\alpha )}=O(n^{-\alpha -1})\), we derive
Following the proof of Theorem 2, we can easily arrive at (5.8), the details are omitted. The proof is complete. \(\square \)
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Zhang, H., Zeng, F., Jiang, X. et al. Convergence analysis of the time-stepping numerical methods for time-fractional nonlinear subdiffusion equations. Fract Calc Appl Anal 25, 453–487 (2022). https://doi.org/10.1007/s13540-022-00022-6
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DOI: https://doi.org/10.1007/s13540-022-00022-6
Keywords
- time-fractional nonlinear subdiffusion equations
- discrete fractional Gronwall inequality
- fast time-stepping methods
- convergence analysis