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Fast finite difference methods for space-time fractional partial differential equations in three space dimensions with nonlocal boundary conditions

机译:具有非局部边界条件的三个空间维时空分数阶偏微分方程的快速有限差分方法

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Fractional partial differential equations (FPDEs) provide very competitive tools to model challenging phenomena involving anomalous diffusion or long-range memory and spatial interactions. However, numerical methods for space-time FPDEs generate dense stiffness matrices and involve numerical solutions at all the previous time steps, and so have O(N-2 + MN) memory requirement and O(MN3 + (MN)-N-2) computational complexity where N and M are the numbers of spatial unknowns and time steps, respectively.We develop and analyze a finite difference method (FDM) for space-time FPDEs in three space dimensions with a combination of Dirichlet and fractional Neumann boundary conditions, in which a shifted Grfinwald discretization is used in space and an L-1 discretization is used in time so the derived FDM has virtually first-order accuracy. We then derive different fast FDMs by carefully analyzing the structure of the stiffness matrix of numerical discretization as well as the coupling in the time direction. The resulting fast FDMs have an almost linear computational complexity and linear storage with respect to the number of spatial unknowns as well as time steps. Numerical experiments are presented to demonstrate the utility of the methods. (C) 2019 IMACS. Published by Elsevier B.V. All rights reserved.
机译:分数阶偏微分方程(FPDE)提供了非常有竞争力的工具,可以对涉及异常扩散或远距离记忆和空间相互作用的具有挑战性的现象进行建模。但是,用于时空FPDE的数值方法会生成密集的刚度矩阵,并且在所有先前的时间步中都涉及数值解,因此对O(N-2 + MN)的存储要求和对O(MN3 +(MN)-N-2的要求也是如此)计算复杂度,其中N和M分别是空间未知数和时间步长。我们结合Dirichlet和分数Neumann边界条件,在三个空间维度上开发并分析了时空FPDE的有限差分法(FDM)。在空间中使用移位的Grfinwald离散化,在时间上使用L-1离散化,因此派生的FDM实际上具有一阶精度。然后,我们通过仔细分析数值离散化的刚度矩阵的结构以及沿时间方向的耦合,得出不同的快速FDM。相对于空间未知数和时间步长,所得的快速FDM具有几乎线性的计算复杂度和线性存储。数值实验表明了该方法的实用性。 (C)2019年IMACS。由Elsevier B.V.发布。保留所有权利。

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