High order stable numerical algorithms for generalized time-fractional deterministic and stochastic telegraph models

Anant Pratap Singh, Priyanka Rajput, Rahul Kumar Maurya, Vineet Kumar Singh
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Abstract

The aim of this manuscript is to design and analyze a hybrid stable numerical algorithm for generalized fractional derivative (GFD) defined in Caputo sense \(\mathscr {D}^{\alpha }_{0, Z,\omega }\) on non-uniform grid points in the temporal direction. An efficient and hybrid high order discretization is proposed for GFD by incorporating a \((3 - \alpha )\)-th order approximation using the moving refinement grid method for the initial interval in the temporal direction. The physical applications of the developed high order approximation are employed to design a hybrid numerical algorithm to determine the solution of the generalized time-fractional telegraph equation (GTFTE) and the generalized time-fractional stochastic telegraph equation (GTFSTE). The proposed numerical techniques are subjected to rigorous error analysis and a thorough investigation of theoretical results i.e. solvability, unconditional stability, convergence analysis, and comparative study are conducted with the existing scheme (Kumar et al. in Numer Methods Partial Differ Equ 35(3):1164–1183, 2019). Several test functions are utilized to verify that second-order convergence is attained in time which is higher than the order of convergence produced by the existing scheme (Kumar et al. 2019). In spatial direction, fourth-order convergence is obtained utilising the compact finite difference methods in spatial approximation on uniform meshes. A reduced first-order convergence in the temporal direction is reported for the GTFSTE model. Further, certain scaling and weight functions are used to show cast the impact of scaling and weight functions in the GFD.

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广义时间分数确定性和随机电报模型的高阶稳定数值算法
本手稿旨在设计和分析一种混合稳定数值算法,用于在时间方向上的非均匀网格点上以 Caputo 意义定义的广义分式导数(GFD)(\mathscr {D}^{\alpha }_{0, Z,\omega }\ )。通过使用移动细化网格法对时间方向上的初始区间进行 \((3 - \alpha )\)-th 阶近似,为 GFD 提出了一种高效的混合高阶离散化方法。所开发的高阶近似的物理应用被用于设计一种混合数值算法,以确定广义时间分数电报方程(GTFTE)和广义时间分数随机电报方程(GTFSTE)的解。对所提出的数值技术进行了严格的误差分析,并对理论结果(即可解性、无条件稳定性、收敛分析)进行了深入研究,还与现有方案进行了比较研究(Kumar 等人,载于《Numer Methods Partial Differ Equ》35(3):1164-1183, 2019)。利用几个测试函数验证了在时间上达到了二阶收敛,高于现有方案产生的收敛阶数(Kumar 等人,2019 年)。在空间方向上,利用紧凑有限差分法在均匀网格上进行空间逼近,获得了四阶收敛。GTFSTE 模型在时间方向上的一阶收敛性有所降低。此外,还使用了某些缩放和权重函数,以显示缩放和权重函数在 GFD 中的影响。
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期刊介绍: Computational & Applied Mathematics began to be published in 1981. This journal was conceived as the main scientific publication of SBMAC (Brazilian Society of Computational and Applied Mathematics). The objective of the journal is the publication of original research in Applied and Computational Mathematics, with interfaces in Physics, Engineering, Chemistry, Biology, Operations Research, Statistics, Social Sciences and Economy. The journal has the usual quality standards of scientific international journals and we aim high level of contributions in terms of originality, depth and relevance.
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