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Lagrange’s Spectral Collocation Method for Numerical Approximations of Two-Dimensional Space Fractional Diffusion Equation

机译:二维空间分数阶扩散方程数值逼近的拉格朗日光谱配置方法

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Due to the ability to model various complex phenomena where classical calculus failed, fractional calculus is getting enormous attention recently. There are several approaches available for numerical approximations of various types of fractional differential equations. For fractional diffusion equations spectral collocation is one of the efficient and most popular ap-proximation techniques. In this research, we introduce spectral collocation method based on Lagrange’s basis polynomials for numerical approximations of two-dimensional (2D) space fractional diffusion equations where spatial fractional derivative is described in Riemann-Liouville sense. We consider four different types of nodes to generate Lagrange’s basis polynomials and as collocation points in the proposed spectral collocation technique. Spectral collocation method converts the diffusion equation into a system of ordinary differential equations (ODE) for time variable and we use 4~(th) order Runge-Kutta method to solve the resulting system of ODE. Two examples are considered to verify the efficiency of different types of nodes in the proposed method. We compare approximated solution with exact solution and find that Lagrange’s spectral collocation method gives very high accuracy approximation. Among the four types of nodes, nodes from Jacobi polynomial give highest accuracy and nodes from Chebyshev polynomials of 1~(st) kind give lowest accuracy in the proposed method.
机译:由于能够对经典演算失败的各种复杂现象进行建模,最近,分数演算得到了极大的关注。有多种方法可用于各种类型的分数阶微分方程的数值逼近。对于分数扩散方程,频谱配置是有效且最流行的近似算法之一。在这项研究中,我们针对二维(2D)空间分数扩散方程的数值逼近,引入了基于拉格朗日基多项式的频谱配位方法,其中空间分数导数以Riemann-Liouville的方式描述。我们考虑四种不同类型的节点来生成Lagrange的基础多项式,并将其作为建议的频谱配置技术中的配置点。频谱搭配方法将扩散方程转换为时间变量的常微分方程组(ODE),并使用4阶Runge-Kutta方法求解所得的ODE系统。考虑两个例子来验证所提出方法中不同类型节点的效率。我们将近似解与精确解进行了比较,发现拉格朗日的频谱配置方法可提供非常高的精确度近似。在四种类型的节点中,Jacobi多项式的节点精度最高,而1〜(st)类Chebyshev多项式的节点精度最低。

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