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Implicit Runge-Kutta and spectral Galerkin methods for the two-dimensional nonlinear Riesz space fractional diffusion equation

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  • Zhao, Jingjun
  • Zhang, Yanming
  • Xu, Yang

Abstract

A numerical method with high accuracy both in time and in space is proposed for the two-dimensional nonlinear Riesz space fractional diffusion equation. The main idea is based on a spectral Galerkin method in spatial direction and an s-stage implicit Runge-Kutta method in temporal direction. A rigorous stability and error analysis is performed for the proposed method. It is shown that the proposed method is stable and convergent. The optimal spatial error estimate is also derived. Numerical experiments are provided to illustrate the theoretical results.

Suggested Citation

  • Zhao, Jingjun & Zhang, Yanming & Xu, Yang, 2020. "Implicit Runge-Kutta and spectral Galerkin methods for the two-dimensional nonlinear Riesz space fractional diffusion equation," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    • Handle: RePEc:eee:apmaco:v:386:y:2020:i:c:s009630032030463x
    DOI: 10.1016/j.amc.2020.125505
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    References listed on IDEAS

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    1. Cheng, Xiujun & Duan, Jinqiao & Li, Dongfang, 2019. "A novel compact ADI scheme for two-dimensional Riesz space fractional nonlinear reaction–diffusion equations," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 452-464.
    2. Bu, Weiping & Tang, Yifa & Wu, Yingchuan & Yang, Jiye, 2015. "Crank–Nicolson ADI Galerkin finite element method for two-dimensional fractional FitzHugh–Nagumo monodomain model," Applied Mathematics and Computation, Elsevier, vol. 257(C), pages 355-364.
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    Cited by:

    1. Saffarian, Marziyeh & Mohebbi, Akbar, 2022. "Finite difference/spectral element method for one and two-dimensional Riesz space fractional advection–dispersion equations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 348-370.
    2. Wang, Jin-Liang & Li, Hui-Feng, 2021. "Memory-dependent derivative versus fractional derivative (II): Remodelling diffusion process," Applied Mathematics and Computation, Elsevier, vol. 391(C).

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