This article deals with coupled nonlinear stochastic partial differential equations. It is a reaction-diffusion system, known as the stochastic Gray-Scott model. The numerical approximation of the stochastic Gray-Scott model is discussed with the proposed stochastic forward Euler (SFE) scheme and the proposed stochastic non-standard finite difference (NSFD) scheme. Both schemes are consistent with the given system of equations. The linear stability analysis is discussed. The proposed SFE scheme is conditionally stable and the proposed stochastic NSFD is unconditionally stable. The convergence of the schemes is also discussed in the mean square sense. The simulations of the numerical solution have been obtained by using the MATLAB package for the various values of the parameters. The effects of randomness are discussed. Regarding the graphical behavior of the stochastic Gray-Scott model, self-replicating behavior is observed.
Citation: Xiaoming Wang, Muhammad W. Yasin, Nauman Ahmed, Muhammad Rafiq, Muhammad Abbas. Numerical approximations of stochastic Gray-Scott model with two novel schemes[J]. AIMS Mathematics, 2023, 8(3): 5124-5147. doi: 10.3934/math.2023257
This article deals with coupled nonlinear stochastic partial differential equations. It is a reaction-diffusion system, known as the stochastic Gray-Scott model. The numerical approximation of the stochastic Gray-Scott model is discussed with the proposed stochastic forward Euler (SFE) scheme and the proposed stochastic non-standard finite difference (NSFD) scheme. Both schemes are consistent with the given system of equations. The linear stability analysis is discussed. The proposed SFE scheme is conditionally stable and the proposed stochastic NSFD is unconditionally stable. The convergence of the schemes is also discussed in the mean square sense. The simulations of the numerical solution have been obtained by using the MATLAB package for the various values of the parameters. The effects of randomness are discussed. Regarding the graphical behavior of the stochastic Gray-Scott model, self-replicating behavior is observed.
[1] | E. Trofimchuk, M. Pinto, S. Trofimchuk, Traveling waves for a model of the Belousov-Zhabotinsky reaction, J. Differ. Equ., 254 (2013), 3690–3714. https://doi.org/10.1016/j.jde.2013.02.005 doi: 10.1016/j.jde.2013.02.005 |
[2] | Y. F. Jia, Y. Li, J. H. Wu, Coexistence of activator and inhibitor for Brusselator diffusion system in chemical or biochemical reactions, Appl. Math. Lett., 53 (2016), 33–38. https://doi.org/10.1016/j.aml.2015.09.018 doi: 10.1016/j.aml.2015.09.018 |
[3] | H. Shoji, T. Ohta, Computer simulations of three-dimensional Turing patterns in the Lengyel-Epstein model, Phys. Rev. E (3), 91 (2015), 032913. https://doi.org/10.1103/physreve.91.032913 doi: 10.1103/physreve.91.032913 |
[4] | P. Liu, J. P. Shi, Y. W. Wang, X. H. Feng, Bifurcation analysis of reaction-diffusion Schnakenberg model, J. Math. Chem., 51 (2013), 2001–2019. http://doi.org/10.1007/s10910-013-0196-x doi: 10.1007/s10910-013-0196-x |
[5] | M. H. Wei, J. H. Wu, G. H. Guo, Steady state bifurcations for a glycolysis model in biochemical reaction, Nonlinear Anal.: Real World Appl., 22 (2015), 155–175. https://doi.org/10.1016/j.nonrwa.2014.08.003 doi: 10.1016/j.nonrwa.2014.08.003 |
[6] | K. J. Lee, W. D. McCormick, J. E. Pearson, H. L. Swinney, Experimental observation of self-replicating spots in a reaction-diffusion system, Nature, 369 (1994), 215–218. http://doi.org/10.1038/369215a0 doi: 10.1038/369215a0 |
[7] | W. N. Reynolds, J. E. Pearson, S. Ponce-Dawson, Dynamics of self-replicating patterns in reaction diffusion systems, Phys. Rev. Lett., 72 (1994), 2797. https://doi.org/10.1103/PhysRevLett.72.2797 doi: 10.1103/PhysRevLett.72.2797 |
[8] | A. Tok-Onarcan, N. Adar, I. Dag, Wave simulations of Gray-Scott reaction-diffusion system, Math. Methods Appl. Sci., 42 (2019), 5566–5581. https://doi.org/10.1002/mma.5534 doi: 10.1002/mma.5534 |
[9] | V. Y. Shevchenko, A. I. Makogon, M. M. Sychov, Modeling of reaction-diffusion processes of synthesis of materials with regular (periodic) microstructure, Open Ceram., 6 (2021), 100088. https://doi.org/10.1016/j.oceram.2021.100088 doi: 10.1016/j.oceram.2021.100088 |
[10] | K. J. Lee, W. D. McCormick, Q. Ouyang, H. L. Swinney, Pattern formation by interacting chemical fronts, Science, 261 (1993), 192–194. https://doi.org/10.1126/science.261.5118.192 doi: 10.1126/science.261.5118.192 |
[11] | K. J. Lee, W. D. McCormick, J. E. Pearson, H. L. Swinney, Experimental observation of self-replicating spots in a reaction-diffusion system, Nature, 369 (1994), 215–218. http://doi.org/10.1038/369215a0 doi: 10.1038/369215a0 |
[12] | M. Bar, Reaction-diffusion patterns and waves: From chemical reactions to cardiac arrhythmias, In: Spirals and vortices, 2019,239–251. |
[13] | T. Ueno, R. Yoshida, Pattern formation in heterostructured gel by the ferrocyanidea-iodatea-sulfite reaction, J. Phys. Chem. A, 123 (2019), 5013–5018. https://doi.org/10.1021/acs.jpca.9b02264 doi: 10.1021/acs.jpca.9b02264 |
[14] | P. Gray, S. K. Scott, Autocatalytic reactions in the isothermal, continuous stirred tank reactor: Oscillations and instabilities in the system A+ 2B$\rightarrow $3B; B$\rightarrow $ C, Chem. Eng. Sci., 39 (1984), 1087–1097. https://doi.org/10.1016/0009-2509(84)87017-7 doi: 10.1016/0009-2509(84)87017-7 |
[15] | T. Shardlow, Numerical simulation of stochastic PDEs for excitable media, J. Comput. Appl. Math., 175 (2005), 429–446. https://doi.org/10.1016/j.cam.2004.06.020 doi: 10.1016/j.cam.2004.06.020 |
[16] | I. BabuAika, F. Nobile, R. Tempone, A stochastic collocation method for elliptic partial differential equations with random input data, SIAM J. Numer. Anal., 45 (2007). |
[17] | A. M. Davie, J. G. Gaines, Convergence of numerical schemes for the solution of parabolic stochastic partial differential equations, Math. Comput., 70 (2001), 121–134. http://doi.org/10.1090/S0025-5718-00-01224-2 doi: 10.1090/S0025-5718-00-01224-2 |
[18] | M. W. Yasin, M. S. Iqbal, N. Ahmed, A. Akgul, A. Raza, M. Rafiq, et al., Numerical scheme and stability analysis of stochastic Fitzhugha-Nagumo model, Results Phys., 32 (2022), 105023. https://doi.org/10.1016/j.rinp.2021.105023 doi: 10.1016/j.rinp.2021.105023 |
[19] | D. Bolin, K. Kirchner, M. Kovacs, Numerical solution of fractional elliptic stochastic PDEs with spatial white noise, IMA J. Numer. Anal., 40 (2020), 1051–1073. https://doi.org/10.1093/imanum/dry091 doi: 10.1093/imanum/dry091 |
[20] | M. Namjoo, A. Mohebbian, Analysis of the stability and convergence of a finite difference approximation for stochastic partial differential equations, Comput. Methods Diffe. Equ., 7 (2019), 334–358. |
[21] | I. Gyongy, T. Martine, On numerical solution of stochastic partial differential equations of elliptic type, Stochastics, 78 (2006), 213–231. https://doi.org/10.1080/17442500600805047 doi: 10.1080/17442500600805047 |
[22] | C. Roth, A combination of finite difference and Wong-Zakai methods for hyperbolic stochastic partial differential equations, Stoch. Anal. Appl., 24 (2006), 221–240. https://doi.org/10.1080/07362990500397764 doi: 10.1080/07362990500397764 |
[23] | M. S. Iqbal, M. W. Yasin, N. Ahmed, A. Akgul, M. Rafiq, A. Raza, Numerical simulations of nonlinear stochastic Newell-Whitehead-Segel equation and its measurable properties, J. Comput. Appl. Math., 418 (2023), 114618. https://doi.org/10.1016/j.cam.2022.114618 doi: 10.1016/j.cam.2022.114618 |
[24] | Q. Du, T. Zhang, Numerical approximation of some linear stochastic partial differential equations driven by special additive noises, SIAM J. Numer. Anal., 40 (2002), 1421–1445. https://doi.org/10.1137/S0036142901387956 doi: 10.1137/S0036142901387956 |
[25] | R. Pettersson, M. Signahl, Numerical approximation for a white noise driven SPDE with locally bounded drift, Potential Anal., 22 (2005), 375–393. http://doi.org/10.1007/s11118-004-1329-4 doi: 10.1007/s11118-004-1329-4 |
[26] | M. W. Yasin, M. S. Iqbal, A. R. Seadawy, M. Z. Baber, M. Younis, S. T. R. Rizvi, Numerical scheme and analytical solutions to the stochastic nonlinear advection diffusion dynamical model, Internat. J. Nonlinear Sci. Numer. Simul., 2021. https://doi.org/10.1515/ijnsns-2021-0113 |
[27] | H. Tiesler, R. M. Kirby, D. Xiu, T. Preusser, Stochastic collocation for optimal control problems with stochastic PDE constraints, SIAM J. Control Optim., 50 (2012), 2659–2682. https://doi.org/10.1137/110835438 doi: 10.1137/110835438 |
[28] | H. G. Matthies, A. Keese, Galerkin methods for linear and nonlinear elliptic stochastic partial differential equations, Comput. methods appl. Mech. Eng., 194 (2005), 1295–1331. https://doi.org/10.1016/j.cma.2004.05.027 doi: 10.1016/j.cma.2004.05.027 |
[29] | G. J. Lord, J. Rougemont, A numerical scheme for stochastic PDEs with Gevrey regularity, IMA J. Numer. Anal., 24 (2004), 587–604. https://doi.org/10.1093/imanum/24.4.587 doi: 10.1093/imanum/24.4.587 |
[30] | M. A. E. Abdelrahman, H. A. Alkhidhr, A. H. Amin, E. K. El-Shewy, A new structure of solutions to the system of ISALWs via stochastic sense, Results Phys., 37 (2022), 105473. https://doi.org/10.1016/j.rinp.2022.105473 doi: 10.1016/j.rinp.2022.105473 |
[31] | R. A. Alomair, S. Z. Hassan, M. A. Abdelrahman, A. H. Amin, E. K. El-Shewy, New solitary optical solutions for the NLSE with d-potential through Brownian process, Results Phys., 40 (2022), 105814. https://doi.org/10.1016/j.rinp.2022.105814 doi: 10.1016/j.rinp.2022.105814 |
[32] | M. AE. Abdelrahman, S. Z. Hassan, D. M. Alsaleh, R. A. Alomair, The new structures of stochastic solutions for the nonlinear Schrodinger's equations, J. Low Freq. Noise V. A., 41 (2022). https://doi.org/10.1177/14613484221095280 |
[33] | M. S. Iqbal, A. R. Seadawy, M. Z. Baber, M. W. Yasin, N. Ahmed, Solution of stochastic Allen-Cahn equation in the framework of soliton theoretical approach, Internat. J. Modern Phys. B, 2022. https://doi.org/10.1142/S0217979223500510 |
[34] | M. Baccouch, H. Temimi, M. Ben-Romdhane, A discontinuous Galerkin method for systems of stochastic differential equations with applications to population biology, finance, and physics, J. Comput. Appl. Math., 388 (2021), 113297. https://doi.org/10.1016/j.cam.2020.113297 doi: 10.1016/j.cam.2020.113297 |
[35] | M. Baccouch, B. Johnson, A high-order discontinuous Galerkin method for Itô stochastic ordinary differential equations, J. Comput. Appl. Math., 308 (2016), 138–165. https://doi.org/10.1016/j.cam.2016.05.034 doi: 10.1016/j.cam.2016.05.034 |
[36] | R. D. Richtmyer, K. W. Morton, Difference methods for initial-value problems, 1994. |
[37] | B. Gustafsson, The convergence rate for difference approximations to mixed initial boundary value problems, Math. Comput., 29 (1975), 396–406. https://doi.org/10.2307/2005559 doi: 10.2307/2005559 |
[38] | J. Gary, A generalization of the Lax-Richtmyer theorem on finite difference schemes, SIAM J. Numer. Anal., 3 (1966), 467–473. https://doi.org/10.1137/0703040 doi: 10.1137/0703040 |
[39] | C. Roth, Difference methods for stochastic partial differential equations, ZAMM-Z. Angew. Math. Me., 82 (2002), 821–830. |
[40] | N. kaur, V. Joshi, Numerical solution of Gray Scott reaction-diffusion equation using Lagrange Polynomial, J. Phys.: Conf. Ser., 1531 (2020), 012058. 10.1088/1742-6596/1531/1/012058 doi: 10.1088/1742-6596/1531/1/012058 |
[41] | J. J. Wang, Y. F. Jia, Analysis on bifurcation and stability of a generalized Gray-Scott chemical reaction model, Phys. A, 528 (2019), 121394. https://doi.org/10.1016/j.physa.2019.121394 doi: 10.1016/j.physa.2019.121394 |