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A finite difference scheme for the two-dimensional Gray-Scott equation with fractional Laplacian

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Abstract

This paper studies numerical methods for the two-dimensional fractional Gray-Scott (GS) model with fractional Laplacian. A three-level linearized difference scheme for solving the fractional GS model is established. The boundedness, existence, uniqueness and convergence of the finite difference scheme are strictly proved by discrete energy analysis method. Furthermore, the convergence of the difference scheme in \(l^{\infty }\)-norm is of second order in space and time. Numerical experiments are implemented to verify the above theoretical results.

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References

  1. Vastano, J.A., Pearson, J.E., Horsthemke, W., Swinney, H.L.: Chemical pattern formation with equal diffusion coefficients. Phys. Lett. A 124(6), 320–324 (1987)

    Article  Google Scholar 

  2. Chen, W., Ward, M.J.: The stability and dynamics of localized spot patterns in the two-dimensional Gray-Scott model. SIAM Journal on Applied Dynamical Systems 10(2), 582–666 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  3. Farr, W.W., Golubitsky, M.: Rotating chemical waves in the Gray-Scott model. SIAM Journal on Applied Mathematics 52(1), 181–221 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  4. Sunil, K., Amit, K., Syed, A., Maysaa, A.Q., Dumitru, B.: A modified analytical approach with existence and uniqueness for fractional Cauchy reaction-diffusion equations. Advances in Difference Equations 1–18, 2020 (2020)

    MathSciNet  MATH  Google Scholar 

  5. Bataineh, A.S., Noorani, M.S.M., Hashim, I.: The homotopy analysis method for Cauchy reaction-diffusion problems. Physics Letters A 372(5), 613–618 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  6. Gray, P., Scott, S.K.: Autocatalytic reactions in the isothermal, continuous stirred tank reactor: Oscillations and instabilities in the system A + 2B \(\rightarrow \) 3B; B \(\rightarrow \) C. Chemical Engineering Science 39(6), 1087–1097 (1984)

    Article  Google Scholar 

  7. Ervin, V.J., Roop, J.P.: Variational formulation for the stationary fractional advection dispersion equation. Numerical Methods for Partial Differential Equations 22(3), 558–576 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  8. Liu, B., Wu, R.C., Iqbal, N., Chen, L.P.: Turing Patterns in the Lengyel-Epstein System with Superdiffusion. International Journal of Bifurcation and Chaos 27, 1730026 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  9. B. P. Epps and B. C. Roisin. Turbulence modeling via the fractional Laplacian. arXiv:1803.05286, 2018

  10. Gatto, P., Hesthaven, J.S.: Numerical Approximation of the Fractional Laplacian via -finite Elements, with an Application to Image Denoising. Journal of Scientific Computing 65(1), 249–270 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  11. Gunzburger, M., Jiang, N., Xu, F.: Analysis and approximation of a fractional Laplacian-based closure model for turbulent flows and its connection to Richardson pair dispersion. Comput. Math. Appl. 75(6), 1973–2001 (2018)

    MathSciNet  MATH  Google Scholar 

  12. Laskin, N.: Fractional quantum mechanics and Levy path integrals. Phys. Lett. A 268(4–6), 298–305 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  13. Sayed, A.E., Rida, S.Z., Arafa, A.: On the solutions of the generalized reaction-diffusion model for bacterial colony. Acta Applicandae Mathematicae 110(3), 1501–1511 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  14. S. Z. Rida, Aam Arafa, A. S. Abedl-Rady, and H. R. Abedl-Rahim. Fractional physical differential equations via natural transform. Chinese Journal of Physics, 55(4):1569–1575, 2017

  15. Liu, F., Zhuang, P., Anh, V., Turner, I., Burrage, K.: Stability and convergence of the difference methods for the space-time fractional advection-diffusion equation. Appl. Math. Comput. 191(1), 12–20 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  16. Ongun, M.Y., Arslan, D., Garrappa, R.: Nonstandard finite difference schemes for a fractional-order Brusselator system. Advances in Difference Equations 2013(102), 1–13 (2013)

    MathSciNet  MATH  Google Scholar 

  17. Landkof, N.S.: Foundations of Modern Potential Theory. Springer-Verlag, Berlin Heidelberg (1972)

    Book  MATH  Google Scholar 

  18. S. Samko, A. Kilbas, and O. Maricev. Fractional integrals and derivations and some applications. Gordon and Breach Science, 1993

  19. Liu, Y., Fan, E.Y., Yin, B.L., Li, H., Wang, J.F.: TT-M finite element algorithm for a two-dimensional space fractional Gray-Scott model. Computers & Mathematics with Applications 80(7), 1793–1809 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  20. Wang, T., Song, F., Wang, H., Karniadakis, G.E.: Fractional Gray-Scott model: Well-posedness, discretization, and simulations. Computer Methods in Applied Mechanics and Engineering 347(15), 1030–1049 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  21. Abbaszadeh, M., Dehghan, M.: A reduced order finite dierence method for solving space-fractional reaction-diusion systems: The Gray-Scott model. European Physical Journal Plus 134(12), 620 (2019)

    Article  Google Scholar 

  22. S. Duo and Y. Zhang. Numerical approximations for the tempered fractional Laplacian: Error analysis and applications. J. Sci. Comput., 81:569–593

  23. Han, C., Wang, Y.L., Li, Z.Y.: A high-precision numerical approach to solving space fractional Gray-Scott model. Appl. Math. Lett. 125, 107759 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  24. Han, C., Wang, Y.L., Li, Z.Y.: Novel patterns in a class of fractional reaction-diffusion models with the riesz fractional derivative. Mathematics and Computers in Simulation 202, 149–163 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  25. Pindza, E., Owolabi, K.M.: Fourier spectral method for higher order space fractional reaction-diffusion equations. Communications in Nonlinear Science and Numerical Simulation 40, 112–128 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  26. M. Abbaszadeh, M. Dehghan, and I. Navon. A POD reduced-order model based on spectral Galerkin method for solving the space-fractional Gray-Scott model with error estimate. Eng. Comput., 38:1–24, 06 2022

  27. S. Guo, L. Mei, C. Li, and Z. Zhang. Semi-implicit hermite-galerkin spectral method for distributed-order fractional-in-space nonlinear reaction-diffusion equations in multidimensional unbounded domains. Journal of Scientific Computing, 85(15), 2020

  28. Q. Li and F. Song. Splitting spectral element method for fractional reaction-diffusion equations. Journal of Algorithms & Computational Technology, 14, 2020

  29. Alzahrani, S.S., Khaliq, A.Q.M.: High-order time stepping Fourier spectral method for multi-dimensional space-fractional reaction-diffusion equations. Comput. Math. Appl. 77(3), 615–630 (2019)

    MathSciNet  MATH  Google Scholar 

  30. Xu, J.: Finite neuron method and convergence analysis. Communications in Computational Physics 28, 1707–1745 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  31. E. Weinan, Chao. Ma, and L. Wu. Barron spaces and the compositional function spaces for neural network models. arXiv:1906.08039, 2019

  32. Wang, Y.Y., Hao, Z.P., Du, R.: A linear finite difference scheme for the two-dimensional nonlinear Schrödinger equation with fractional Laplacian. J. Sci. Comput. 90(1), 1–27 (2022)

    Article  MATH  Google Scholar 

  33. Hao, Z.P., Zhang, Z.Q., Du, R.: Fractional centered difference scheme for high-dimensional integral fractional Laplacian. J. Comput. Phys. 424, 109851 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  34. Sun, Z.Z.: Numerical Methods of the Partial Differential Equations. Science Press, China (2012)

    Google Scholar 

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Acknowledgements

The authors thanks Dr. Zhaopeng Hao for useful discussing. This work is financially supported by the Natural Science Foundation of Jiangsu Province(Grants No BK20221450) and National Natural Science Foundation of China (Grant No. 12071073), and sponsored by Jiangsu Provincial Qinglan Project.

Funding

This work is financially supported by the Natural Science Foundation of Jiangsu Province(Grants No BK20221450) and National Natural Science Foundation of China (Grant No. 12071073), and sponsored by Jiangsu Provincial Qinglan Project.

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Authors and Affiliations

Authors

Contributions

Su Lei: Conceptualization, Methodology, Formal analysis, Writing - original draft, Software, Validation. Yanyan Wang: Conceptualization, Formal analysis, Project administration, Writing - review and editing. Rui Du: Conceptualization, Formal analysis, Project administration, Writing - review and editing, Funding acquisition.

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Correspondence to Rui Du.

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Appendix

Appendix

We estimate the four equations \((\textrm{I})\), \((\textrm{II})\), \((\textrm{III})\), \((\textrm{IV})\) at follows.

$$\begin{aligned} (\textrm{I})= & {} \frac{4 \tau }{\mu } \sum _{k=1}^{n} \left( R^{(2), k}, (-\varDelta _{h})^{\frac{\alpha }{2}}D_{\hat{t}}e^{k}\right) ,\nonumber \\= & {} \frac{2}{\mu }\left( (R^{(2), n}, (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n+1})-(R^{(2), n}, (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n-1})+(R^{(2),1}, (-\varDelta _{h})^{\frac{\alpha }{2}}e^{2})\right) \nonumber \\{} & {} -\frac{4 \tau }{\mu } \sum _{k=2}^{n-1} \left( D_{\hat{t}}R^{(2), k}, (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k})\right) \nonumber \\\le & {} \frac{2}{\mu }\left( \Vert R^{(2), n}\Vert \cdot \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n+1}\Vert +\Vert R^{(2), n}\Vert \cdot \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n-1}\Vert +\Vert R^{(2),1}\Vert \cdot \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{2}\Vert \right) \quad \nonumber \\{} & {} +\frac{4 \tau }{\mu } \sum _{k=2}^{n-1} \Vert D_{\hat{t}}R^{(2), k}\Vert \cdot \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k}\Vert \nonumber \\\le & {} \frac{1}{4}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n+1}\Vert ^{2}+ \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n}\Vert ^{2}+ \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{1}\Vert ^{2}\right) \nonumber \\{} & {} + \tau \sum _{k=2}^{n-1} \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k}\Vert ^{2}+\frac{12+4T}{\mu ^{2}}C_{2}^{2}(\tau ^{2}+h^{2})^{2}, \end{aligned}$$
(A.1)

for \((\textrm{II})\), we have

$$\begin{aligned} (\textrm{II})= & {} -\frac{4 \tau }{\mu } \sum _{k=1}^{n} \left( G^{\bar{k}}, (-\varDelta _{h})^{\frac{\alpha }{2}}D_{\hat{t}}e^{k})\right) , \nonumber \\= & {} \frac{2}{\mu }\left( (G^{\bar{n}}, (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n+1})-(G^{\bar{n}}, (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n-1})+(G^{\bar{1}}, (-\varDelta _{h})^{\frac{\alpha }{2}}e^{2})\right) \nonumber \\{} & {} +\frac{4 \tau }{\mu } \sum _{k=2}^{n-1} \left( D_{\hat{t}}G^{\bar{k}}, (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k})\right) \nonumber \\\le & {} \frac{1}{4}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n+1}\Vert ^{2}+ \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{n}\Vert ^{2}+ \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{1}\Vert ^{2}\right) \nonumber \\{} & {} +\frac{2 \tau }{\mu } \sum _{k=2}^{n-1} \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k}\Vert ^{2}+\frac{2 \tau }{\mu } \sum _{k=2}^{n-1} \Vert D_{\hat{t}}G^{\bar{k}}\Vert ^{2}+\frac{12}{\mu ^{2}}C_{8}^{2}C_{11}^{2}(\tau ^{2}+h^{2})^{2}.\qquad \quad \end{aligned}$$
(A.2)

In the same way

$$\begin{aligned} \begin{aligned} (\textrm{III})&=\frac{4 \tau }{\mu } \sum _{k=1}^{n} \left( R^{(4), k} (-\varDelta _{h})^{\frac{\alpha }{2}}D_{\hat{t}}f^{k})\right) , \\&\le \frac{1}{4}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{n+1}\Vert ^{2}+ \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{n}\Vert ^{2}+ \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{1}\Vert ^{2}\right) \\&\quad +\tau \sum _{k=2}^{n-1} \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k}\Vert ^{2}+\frac{12+4T}{\mu ^{2}}C_{4}^{2}(\tau ^{2}+h^{2})^{2} \end{aligned} \end{aligned}$$
(A.3)

We make the following estimate for \((\textrm{IV})\)

$$\begin{aligned} \begin{aligned} (\textrm{IV})&=-\frac{4 \tau }{\mu } \sum _{k=1}^{n} \left( G^{\bar{k}}, (-\varDelta _{h})^{\frac{\alpha }{2}}D_{\hat{t}}f^{k})\right) , \\&\le \frac{1}{4}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{n+1}\Vert ^{2}+ \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{n}\Vert ^{2}+ \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{1}\Vert ^{2}\right) \\&\quad +\frac{2 \tau }{\mu } \sum _{k=2}^{n-1} \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k}\Vert ^{2}+\frac{2 \tau }{\mu } \sum _{k=2}^{n-1} \Vert D_{\hat{t}}G^{\bar{k}}\Vert ^{2}+\frac{12}{\mu ^{2}}C_{8}^{2}C_{11}^{2}(\tau ^{2}+h^{2})^{2}, \end{aligned} \end{aligned}$$
(A.4)

combining with the expression of \(G^{\bar{k}}\), we obtain

$$\begin{aligned} D_{\hat{t}} G^{\bar{k}}= D_{\hat{t}}\left( e^{\bar{k}}(V^{k})^{2}\right) +2 D_{\hat{t}}\left( U^{\bar{k}}f^{k}V^{k}\right) -D_{\hat{t}}\left( U^{\bar{k}}(f^{k})^{2}\right) -2D_{\hat{t}}\left( e^{\bar{k}} f^{k}V^{k}\right) +D_{\hat{t}}\left( e^{\bar{k}}( f^{k} )^{2}\right) , \end{aligned}$$
(A.5)

it can be obtained from the equation expression

$$\begin{aligned} D_{\hat{t}} e^{k}=-\mu _{u}(-\varDelta _{h})^{\frac{\alpha }{2}}e^{\bar{k}}-\sigma e^{\bar{k}} -G^{\bar{k}}+R^{(2),k}, \end{aligned}$$
(A.6)

such that

$$\begin{aligned} \Vert D_{\hat{t}} e^{k}\Vert ^{2}\le & {} 4\mu ^{2}\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{\bar{k}}\Vert ^{2}+4\sigma ^{2}\Vert e^{\bar{k}}\Vert ^{2} +4\Vert G^{\bar{k}}\Vert ^{2}+4|R^{(2),k}|^{2},\nonumber \\\le & {} 2\mu ^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k+1}\Vert ^{2}+\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k-1}\Vert ^{2}\right) \nonumber \\{} & {} +2\sigma ^{2}\left( \Vert e^{k+1}\Vert ^{2}+\Vert e^{k-1}\Vert ^{2}\right) +C_{21}^{2}(\tau ^{2}+h^{2})^{2}, \end{aligned}$$
(A.7)

where \(C_{21}^{2}=4(C^{2}_{11}+C_{8}^{2}C_{11}^{2})\), similarly, we have

$$\begin{aligned} \Vert D_{\hat{t}} f^{k}\Vert ^{2}\le & {} 2\mu ^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k+1}\Vert ^{2}+\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k-1}\Vert ^{2}\right) \nonumber \\{} & {} +2(\sigma +\kappa )^{2}\left( \Vert f^{k+1}\Vert ^{2}+\Vert f^{k-1}\Vert ^{2}\right) +C_{22}^{2}(\tau ^{2}+h^{2})^{2}, \end{aligned}$$
(A.8)

where \(C_{22}^{2}=4(C^{2}_{13}+C_{8}^{2}C_{11}^{2})\).

To simplify the calculation, the paper assumes \(\Vert e^{k+1}\Vert ^{2}+\Vert e^{k-1}\Vert ^{2}\le 1,\Vert f^{k+1}\Vert ^{2}+\Vert f^{k-1}\Vert ^{2}\le 1\), which can be obtained

$$\begin{aligned} \begin{aligned} \Vert D_{\hat{t}} e^{\bar{k}}\Vert ^{2}&=\frac{1}{4} \Vert D_{\hat{t}} e^{k+1}+D_{\hat{t}} e^{k-1}\Vert ^{2}\le \frac{1}{2}\left( \Vert D_{\hat{t}} e^{k+1}\Vert ^{2}+\Vert D_{\hat{t}} e^{k-1}\Vert ^{2}\right) \\&\le 2\mu ^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k-2}\Vert ^{2}+2\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k}\Vert ^{2}+\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k+2}\Vert ^{2}\right) \\&\quad +2\sigma ^{2}(\Vert e^{k-2}\Vert ^{2}+\Vert e^{k}\Vert ^{2}+\Vert e^{k+2}\Vert ^{2})+2C_{21}^{2}(\tau ^{2}+h^{2})^{2}, \end{aligned} \end{aligned}$$
(A.9)

Denote \(C^{2}_{0}=\max \{\Vert U^{k}\Vert ^{2},\Vert V^{k}\Vert ^{2},\Vert D_{\hat{t}}(V^{k})\Vert ^{2},\Vert D_{\hat{t}}(U^{k})\Vert ^{2}\}\), \(C_{s}^{2}=24C^{4}_{0}\left( C^{2}_{29}+\right. \) \(\left. C^{2}_{20}+C^{2}_{11}+C^{2}_{17}C^{2}_{20}+C^{2}_{13}+C^{2}_{17}C^{2}_{20}\right) \), so, we have

$$\begin{aligned} s_{1}= & {} \Vert D_{\hat{t}}\left( e^{\bar{k}}(V^{k})^{2}\right) \Vert ^{2}\nonumber \\= & {} \Vert D_{\hat{t}}(e^{\bar{k}})(V^{k+1})^{2}+D_{\hat{t}}(V^{k})e^{\overline{k-1}}V^{k+1}+D_{\hat{t}}(V^{k})e^{\overline{k-1}}V^{k-1}\Vert ^{2}\nonumber \\\le & {} 3C_{0}^{4}\Vert D_{\hat{t}}(e^{\bar{k}})\Vert ^{2}+6C_{0}^{4}\Vert (e^{\overline{k-1}})\Vert ^{2}\nonumber \\\le & {} C_{s}^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k-2}\Vert ^{2}\!+\!\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k}\Vert ^{2}\!+\!\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k+2}\Vert ^{2} +\Vert e^{k-2}\Vert ^{2}+\Vert e^{k}\Vert ^{2}+\Vert e^{k+2}\Vert ^{2}\right) \nonumber \\{} & {} +C_{s}^{2}(\tau ^{2}+h^{2})^{2}. \end{aligned}$$
(A.10)
$$\begin{aligned} s_{2}= & {} \Vert D_{\hat{t}}\left( U^{\bar{k}}f^{k}V^{k}\right) \Vert ^{2}\nonumber \\= & {} \Vert D_{\hat{t}}(U^{\bar{k}})f^{k+1}V^{k+1}+D_{\hat{t}}(f^{k})U^{\overline{k-1}}V^{k+1}+D_{\hat{t}}(V^{k})U^{\overline{k-1}}f^{k-1}\Vert ^{2}\nonumber \\\le & {} 3C_{0}^{4}\Vert D_{\hat{t}}(f^{k})\Vert ^{2}+3C_{0}^{4}\Vert f^{k+1}\Vert ^{2}++3C_{0}^{4}\Vert f^{k-1}\Vert ^{2}\nonumber \\\le & {} \!C_{s}^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k-1}\Vert ^{2}\!\!+\!\!\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k+1}\Vert ^{2}\! \!+\!\!\Vert f^{k-1}\Vert ^{2}\!\!+\!\!\Vert f^{k+1}\Vert ^{2}\!\!+\!\!(\tau ^{2}\!+\!h^{2})^{2}\right) . \end{aligned}$$
(A.11)
$$\begin{aligned} s_{3}= & {} \Vert D_{\hat{t}}\left( U^{\bar{k}}(f^{k})^{2}\right) \Vert ^{2}\nonumber \\= & {} \Vert D_{\hat{t}}(U^{\bar{k}})(f^{k+1})^{2}+D_{\hat{t}}(f^{k})U^{\overline{k-1}}f^{k+1}+D_{\hat{t}}(f^{k})U^{\overline{k-1}}f^{k-1}\Vert ^{2}\nonumber \\\le & {} 3C_{0}^{4}\Vert f^{k+1}\Vert ^{2}+3C_{0}^{4}\Vert D_{\hat{t}}(f^{k})(f^{k+1}+f^{k-1})\Vert ^{2}\nonumber \\\le & {} 3C_{0}^{4}\Vert f^{k+1}\Vert ^{2}+3C_{0}^{4}\Vert D_{\hat{t}}f^{k}\Vert ^{2}\cdot \Vert f^{k+1}+f^{k-1}\Vert ^{2}\nonumber \\\le & {} 3C_{0}^{4}\Vert f^{k+1}\Vert ^{2}+6C_{0}^{4}\Vert D_{\hat{t}}f^{k}\Vert ^{2}\cdot \left( \Vert f^{k+1}\Vert ^{2}+\Vert f^{k-1}\Vert ^{2}\right) \nonumber \\\le & {} C_{s}^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k-1}\Vert ^{2}\!\!+\!\!\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k+1}\Vert ^{2}\!\! +\!\!\Vert f^{k-1}\Vert ^{2}\!\!+\!\!\Vert f^{k+1}\Vert ^{2}\!+\!(\tau ^{2}\!\!+\!\!h^{2})^{2}\right) . \end{aligned}$$
(A.12)
$$\begin{aligned} s_{4}= & {} \Vert D_{\hat{t}}\left( e^{\bar{k}}f^{k}V^{k}\right) \Vert ^{2}\nonumber \\= & {} \Vert D_{\hat{t}}(e^{\bar{k}})f^{k+1}V^{k+1}+D_{\hat{t}}(f^{k})e^{\overline{k-1}}V^{k+1}+D_{\hat{t}}(V^{k})e^{\overline{k-1}}f^{k-1}\Vert ^{2}\nonumber \\\le & {} 6C_{0}^{4}\left( \Vert f^{k+1}\Vert ^{2}+\Vert D_{\hat{t}}e^{\bar{k}}\Vert ^{2}\right) +6C_{0}^{4}\left( \Vert D_{\hat{t}}f^{k}\Vert ^{2}+\Vert e^{\bar{k-1}}\Vert ^{2}\right) \nonumber \\{} & {} +6C_{0}^{4}\left( \Vert e^{k-2}\Vert ^{2}+\Vert e^{k}\Vert ^{2}+\Vert f^{k-1}\Vert ^{2}\right) \nonumber \\\le & {} C_{s}^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k-1}\Vert ^{2}+\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k+1}\Vert ^{2} +\Vert f^{k-1}\Vert ^{2}+\Vert f^{k+1}\Vert ^{2}\right) \nonumber \\{} & {} +C_{s}^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k-2}\Vert ^{2}+\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k}\Vert ^{2}+\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k+2}\Vert ^{2}\right. \nonumber \\{} & {} \left. +\Vert e^{k-2}\Vert ^{2}+\Vert e^{k}\Vert ^{2}+\Vert e^{k+2}\Vert ^{2}\right) \nonumber \\{} & {} +C_{s}^{2}(\tau ^{2}+h^{2})^{2}. \end{aligned}$$
(A.13)
$$\begin{aligned} s_{5}= & {} \Vert D_{\hat{t}}\left( e^{\bar{k}}(f^{k})^{2}\right) \Vert ^{2}\nonumber \\= & {} \Vert D_{\hat{t}}(e^{\bar{k}})(f^{k+1})^{2}+D_{\hat{t}}(f^{k})e^{\overline{k-1}}f^{k+1}+D_{\hat{t}}(f^{k})e^{\overline{k-1}}f^{k-1}\Vert ^{2}\nonumber \\\le & {} 6C_{0}^{4}\left( \Vert f^{k+1}\Vert ^{2}+\Vert D_{\hat{t}}e^{\bar{k}}\Vert ^{2}\right) +3C_{0}^{4}\Vert D_{\hat{t}}(f^{k})e^{\bar{k-1}}\Vert ^{2}\cdot \Vert f^{k+1}+f^{k-1}\Vert ^{2}\nonumber \\\le & {} 6C_{0}^{4}\left( \Vert f^{k+1}\Vert ^{2}\!+\!\Vert D_{\hat{t}}e^{\bar{k}}\Vert ^{2}\right) \!+\!3C_{0}^{4}\Vert D_{\hat{t}}f^{k}\Vert ^{2}\cdot \left( \Vert e^{k+1}\Vert ^{2}\!+\!\Vert e^{k-1}\Vert ^{2}\right) \cdot \left( \Vert f^{k+1}\Vert ^{2}\!+\!\Vert f^{k-1}\Vert ^{2}\right) \nonumber \\\le & {} C_{s}^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k-1}\Vert ^{2}+\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}f^{k+1}\Vert ^{2} +\Vert f^{k-1}\Vert ^{2}+\Vert f^{k+1}\Vert ^{2}\right) \nonumber \\{} & {} +C_{s}^{2}\left( \Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k-2}\Vert ^{2}\!+\!\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k}\Vert ^{2}\!+\!\Vert (-\varDelta _{h})^{\frac{\alpha }{2}}e^{k+2}\Vert ^{2} \!\!+\!\!\Vert e^{k-2}\Vert ^{2}\!+\!\Vert e^{k}\Vert ^{2}\!+\!\Vert e^{k+2}\Vert ^{2}\right) \nonumber \\{} & {} +C_{s}^{2}(\tau ^{2}+h^{2})^{2}. \end{aligned}$$
(A.14)

Combining the above five estimators, it can be obtained

$$\begin{aligned} \frac{2\tau }{\mu } \sum _{k=2}^{n}\left\| D_{\hat{t}} G^{\bar{k}}\right\| ^{2}\le & {} \frac{6}{\mu } C_{s}^{2} \tau \sum _{k=2}^{n-1}\left( \left\| e^{k-2}\right\| ^{2}+\left\| e^{k}\right\| ^{2}+\left\| e^{k+2}\right\| ^{2}\right) \nonumber \\{} & {} +\frac{6}{\mu } C_{s}^{2} \tau \sum _{k=2}^{n-1}\left( \left\| \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} e^{k-2}\right\| ^{2}+\left\| \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} e^{k}\right\| ^{2}+\left\| \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} e^{k+2}\right\| ^{2}\right) \nonumber \\{} & {} + \frac{8}{\mu } C_{s}^{2} \tau \sum _{k=2}^{n-1}\left( \left\| f^{k-1}\right\| ^{2}+\left\| f^{k+1}\right\| ^{2}\right) \nonumber \\{} & {} +\frac{8}{\mu } C_{s}^{2} \tau \sum _{k=2}^{n-1}\left( \left\| \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} f^{k-1}\right\| ^{2}+\left\| \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} f^{k+1}\right\| ^{2}\right) \nonumber \\{} & {} +\frac{10C_{s}^{2}T\tau }{\mu }(\tau ^{2}+h^{2})^{2}\nonumber \\\le & {} \frac{C_{16}^{2}}{2}\tau \sum _{k=1}^{n}\left( \left\| \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} e^{k}\right\| ^{2}+\left\| \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} f^{k}\right\| ^{2}\right) \nonumber \\{} & {} +C_{16}^{2}\tau \left\| \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} e^{n+1}\right\| ^{2}+\frac{C_{17}^{2}}{2}(\tau ^{2}+h^{2})^{2}. \end{aligned}$$
(A.15)

where \(C_{16}^{2}=\frac{16}{\mu } C_{s}^{2}\), \(C_{17}^{2}=\frac{10C_{s}^{2}T }{\mu }\), we obtain

$$\begin{aligned} \begin{aligned} (\textrm{II}) +(\textrm{IV})\le&\left( \frac{1}{2}+C_{16}^{2} \tau \right) E^{n+1}+\frac{2 \tau }{\mu } \sum _{k=2}^{n}\left( \Vert \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} e^{k}\Vert ^{2}+\Vert \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} f^{k}\Vert ^{2}\right) \\&+C_{16}^{2} \tau \sum _{k=1}^{n}\left( \Vert \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} e^{k}\Vert ^{2}+\Vert \left( -\varDelta _{h}\right) ^{\frac{\alpha }{2}} f^{k}\Vert ^{2}\right) +C_{17}^{2}\left( \tau ^{2}+h^{2}\right) ^{2} \end{aligned} \end{aligned}$$
(A.16)

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Lei, S., Wang, Y. & Du, R. A finite difference scheme for the two-dimensional Gray-Scott equation with fractional Laplacian. Numer Algor 94, 1185–1215 (2023). https://doi.org/10.1007/s11075-023-01532-x

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