Fractional differential equations (FDEs) describe subdiffusion behavior of dynamical systems. Its non-local structure requires to take into account the whole evolution history during the time integration, which then possibly causes additional memory use to store the history, growing in time. An alternative to a quadrature of the history integral is to approximate the fractional kernel with the sum of exponentials, which is equivalent to consider the FDE solution as a sum of solutions to a system of ODEs. One possibility to construct this system is to approximate the Laplace spectrum of the fractional kernel with a rational function. In this paper, we use the adaptive Antoulas--Anderson (AAA) algorithm for the rational approximation of the kernel spectrum which yields only a small number of real valued poles. We propose a numerical scheme based on this idea and study its stability and convergence properties. Moreover, we apply the algorithm to a time-fractional Cahn-Hilliard problem.
翻译:分形差异方程式描述动态系统的亚扩散行为。 其非本地结构需要考虑到时间整合期间的整个进化历史, 这可能引发更多的记忆用于存储历史, 并随着时间的增长而增长。 历史组成部分的二次方程式的替代办法是将分核内核与指数之和相近, 这相当于将FDE 解决方案视为ODE 系统解决方案之和。 构建这个系统的一个可能性是将分层内核的拉位频谱与合理功能相近。 在本文中, 我们使用适应的 Antoulas- Anderson (AAAA) 算法来合理接近内核频谱, 它只产生少量的实际价值极。 我们基于这个想法提出一个数字方案, 并研究其稳定性和趋同性。 此外, 我们将算法应用于一个时间误差的 Cahn- Hilliard 问题 。