Abstract
For solving time-dependent one-dimensional spatial-fractional diffusion equations of variable coefficients, we establish a banded M-splitting iteration method applicable to compute approximate solutions for the corresponding discrete linear systems resulting from certain finite difference schemes at every temporal level, and demonstrate its asymptotic convergence without imposing any extra condition. Also, we provide a multistep variant for the banded M-splitting iteration method, and prove that the computed solutions of the discrete linear systems by employing this iteration method converge to the exact solutions of the spatial fractional diffusion equations. Numerical experiments show the accuracy and efficiency of the multistep banded M-splitting iteration method.
Similar content being viewed by others
References
Bai, Z.-Z.: Motivations and realizations of Krylov subspace methods for large sparse linear systems. J. Comput. Appl. Math. 283, 71–78 (2015)
Bai, Z.-Z., Lu, K.-Y., Pan, J.-Y.: Diagonal and Toeplitz splitting iteration methods for diagonal-plus-Toeplitz linear systems from spatial fractional diffusion equations. Numer. Linear Algebra Appl. 24(e2093), 1–15 (2017)
Bai, Z.-Z., Wang, D.-R.: Generalized matrix multisplitting relaxation methods and their convergence. Numer. Math. J. Chin. Univ. (Engl. Ser.) 2, 87–100 (1993)
Berman, A., Plemmons, R.J.: Nonnegative Matrices in the Mathematical Sciences (Revised Reprint of the 1979 Original). SIAM, Philadelphia (1994)
Breiten, T., Simoncini, V., Stoll, M.: Low-rank solvers for fractional differential equations. Electron. Trans. Numer. Anal. 45, 107–132 (2016)
Carreras, B.A., Lynch, V.E., Zaslavsky, G.M.: Anomalous diffusion and exit time distribution of particle tracers in plasma turbulence model. Phys. Plasmas 8, 5096–5103 (2001)
Deng, W.-H.: Finite element method for the space and time fractional Fokker–Planck equation. SIAM J. Numer. Anal. 47, 204–226 (2008/2009)
Donatelli, M., Mazza, M., Serra-Capizzano, S.: Spectral analysis and structure preserving preconditioners for fractional diffusion equations. J. Comput. Phys. 307, 262–279 (2016)
Ervin, V.J., Roop, J.P.: Variational formulation for the stationary fractional advection dispersion equation. Numer. Methods Partial Differ. Equ. 22, 558–576 (2006)
Hu, J.-G.: The estimate of \(\Vert M^{-1}N\Vert _{\infty }\) and the optimally scaled matrix. J. Comput. Math. 2, 122–129 (1984)
Kirchner, J.W., Feng, X.-H., Neal, C.: Fractal stream chemistry and its implications for contaminant transport in catchments. Nature 403, 524–527 (2000)
Kreer, M., Kızılersü, A., Thomas, A.W.: Fractional Poisson processes and their representation by infinite systems of ordinary differential equations. Stat. Probab. Lett. 84, 27–32 (2014)
Lei, S.-L., Sun, H.-W.: A circulant preconditioner for fractional diffusion equations. J. Comput. Phys. 242, 715–725 (2013)
Li, X.-J., Xu, C.-J.: A space–time spectral method for the time fractional diffusion equation. SIAM J. Numer. Anal. 47, 2108–2131 (2009)
Li, X.-J., Xu, C.-J.: Existence and uniqueness of the weak solution of the space-time fractional diffusion equation and a spectral method approximation. Commun. Comput. Phys. 8, 1016–1051 (2010)
Lin, F.-R., Yang, S.-W., Jin, X.-Q.: Preconditioned iterative methods for fractional diffusion equation. J. Comput. Phys. 256, 109–117 (2014)
Magin, R.L.: Fractional Calculus in Bioengineering. Begell House Publishers, Danbury (2006)
Meerschaert, M.M., Scheffler, H.-P., Tadjeran, C.: Finite difference methods for two-dimensional fractional dispersion equation. J. Comput. Phys. 211, 249–261 (2006)
Meerschaert, M.M., Tadjeran, C.: Finite difference approximations for fractional advection-dispersion flow equations. J. Comput. Appl. Math. 172, 65–77 (2004)
Meerschaert, M.M., Tadjeran, C.: Finite difference approximations for two-sided space-fractional partial differential equations. Appl. Numer. Math. 56, 80–90 (2006)
Metzler, R., Klafter, J.: The random walk’s guide to anomalous diffusion: a fractional dynamics approach. Phys. Rep. 339, 1–77 (2000)
Ortega, J.M., Rheinboldt, W.C.: Iterative Solution of Nonlinear Equations in Several Variables. SIAM, Philadelphia (2000)
Pan, J.-Y., Ke, R.-H., Ng, M.K., Sun, H.-W.: Preconditioning techniques for diagonal-times-Toeplitz matrices in fractional diffusion equations. SIAM J. Sci. Comput. 36, A2698–A2719 (2014)
Podlubny, I.: Fractional Differential Equations, Mathematics in Science and Engineering, vol. 198. Academic Press, San Diego (1999)
Raberto, M., Scalas, E., Mainardi, F.: Waiting-times and returns in high-frequency financial data: an empirical study. Phys. A Stat. Mech. Appl. 314, 749–755 (2002)
Razminia, K., Razminia, A., Baleanu, D.: Investigation of the fractional diffusion equation based on generalized integral quadrature technique. Appl. Math. Model. 39, 86–98 (2015)
Sabatelli, L., Keating, S., Dudley, J., Richmond, P.: Waiting time distributions in financial markets. Eur. Phys. J. B Condens. Matter Phys. 27, 273–275 (2002)
Samko, S.G., Kilbas, A.A., Marichev, O.I.: Fractional Integrals and Derivatives: Theory and Applications. Gordon and Breach Science, Yverdon (1993)
Stewart, G.W.: Matrix Algorithms. SIAM, Philadelphia (1998)
Upadhyay, R.K., Mondal, A.: Dynamics of fractional order modified Morris–Lecar neural model. Netw. Biol. 5, 113–136 (2015)
Varga, R.S.: Matrix Iterative Analysis. Prentice Hall, Englewood Cliffs (1962)
Varga, R.S.: Geršgorin and His Circles. Springer, Berlin (2004)
Wang, H., Wang, K.-X., Sircar, T.: A direct \({{\cal{O}}}(N\log ^2N)\) finite difference method for fractional diffusion equations. J. Comput. Phys. 229, 8095–8104 (2010)
Zaslavsky, G.M.: Chaos, fractional kinetics, and anomalous transport. Phys. Rep. 371, 461–580 (2002)
Acknowledgements
The authors are very much indebted to Prof. Michiel E. Hochstenbach for constructive suggestions and valuable discussions. The referees provided very useful comments and suggestions, which greatly improved the original manuscript of this paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Michiel E. Hochstenbach.
This study was supported by the National Natural Science Foundation (No. 11671393), P.R. China.
7 Appendix: Proof of Theorem 4.1
7 Appendix: Proof of Theorem 4.1
In fact, it holds that
As \(u_{\star }^{\tau }\) is the exact solution of the fractional diffusion equation (1.1), from the approximation property of the finite-difference formulas it satisfies
Hence, by making use of the discrete linear system (2.3) we can obtain the truncated error equation
where
is the corresponding error term. With applications of the Lipschitz conditions in (4.2) and the definitions of the diagonal matrices \(D^{\tau }\) and \(W^{\tau }\) in (2.4), it can be verified straightforwardly that this error term satisfies
The error equation (7.2), together with the upper bound about \(\Vert (A^{\tau })^{-1}\Vert _{\infty }\) in Lemma 2.1, straightforwardly lead to the estimate
Note that \(u^{0}=u_{\star }^{0}\). Then it holds that
Moreover, by the Lipschitz continuity of the solution \(u_{\star }(x,t)\) of the fractional diffusion equation (1.1), we can obtain
On the other hand, based on the discrete linear system (2.3) and the MBMS iteration method (4.1), we can obtain the iterative error equation
which implies
Therefore, it follows from Lemma 2.1 and Theorem 3.1 that
Note that \(u^{\tau ,0}=2u^{\tau -1,k_o}-u^{\tau -2,k_o}\) if \(\tau \ge 2\), and \(u^{\tau ,0}=u^0\) if \(\tau =1\). Based on the equivalent expressions
for \(\tau \ge 2\), and
for \(\tau =1\), by utilizing (7.4) we have the following inequalities:
if \(\tau \ge 2\), and
if \(\tau =1\).
The substitution of (7.6) into (7.5) directly results in the recurrence formula
for \(\tau \ge 2\). As for \(\tau =1\), it follows from (7.5) and (7.4) that
for \(\tau =2\) the recurrence formula (7.8) particularly reads as
Here we have used the fact
which is readily implied by the restriction imposed on the positive integer \(k_o\). We further remark that the restriction on \(k_o\) is equivalent to the condition
which is equivalent to \(\theta <1\), too.
In addition, denote by
Then, for \(\tau \ge 3\), we can rewrite the second-order difference inequality (7.8) as
which, by induction, leads to
Since \(\tilde{\theta }<0\) and \(\sqrt{1+s} \le 1+\frac{1}{2} s\) (for \(\forall s \ge 0\)), it holds that
Thereby, by making use of (7.9) and (7.10), from (7.12) we can obtain the estimate
for \(\tau \ge 3\). Here the last inequality has been derived by employing the bounds
and
see (7.11).
Recalling (7.9) and (7.10), we see that (7.13) holds true for all \(\tau \ge 1\), too. Now, the error bound (4.3) follows straightforwardly by substitutions of both (7.3) and (7.13) into (7.1). \(\Box \)
Rights and permissions
About this article
Cite this article
Bai, ZZ., Lu, KY. On banded M-splitting iteration methods for solving discretized spatial fractional diffusion equations. Bit Numer Math 59, 1–33 (2019). https://doi.org/10.1007/s10543-018-0727-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10543-018-0727-8