The Sinc-Nystr\"{o}m method in time is a high-order spectral method for solving evolutionary differential equations and it has wide applications in scientific computation. But in this method we have to solve all the time steps implicitly at one-shot, which may results in a large-scale nonsymmetric dense system that is expensive to solve. In this paper, we propose and analyze a parallel-in-time (PinT) preconditioner for solving such Sinc-Nystr\"{o}m systems, where both the parabolic and hyperbolic PDEs are investigated. Attributed to the special Toeplitz-like structure of the Sinc-Nystr\"{o}m systems, the proposed PinT preconditioner is indeed a low-rank perturbation of the system matrix and we show that the spectrum of the preconditioned system is highly clustered around one, especially when the time step size is refined. Such a clustered spectrum distribution matches very well with the numerically observed mesh-independent GMRES convergence rates in various examples. Several linear and nonlinear ODE and PDE examples are presented to illustrate the convergence performance of our proposed PinT preconditioners, where the achieved exponential order of accuracy are especially attractive to those applications in need of high accuracy.
翻译:Sinc- Nystr\"{( o}m) 方法在时间上是一种解决进化差异方程式的高阶光谱方法,它具有广泛的科学计算应用。 但是在这种方法中,我们必须在一瞬间隐含地解决所有时间步骤,这可能导致大规模非对称密集系统,解决费用昂贵。 在本文中,我们提议和分析一个平行时间( PinT) 的先决条件, 解决这种Sinc- Nystr\\}{( o}m) 系统, 进行对parblic 和双曲双曲 PDE 的调查。 与Sinc- Nystr\\{ o}m 系统类似于Teplitz的特殊结构有关。 提议的PinT 先决条件实际上是一个系统矩阵的低端渗透。 我们显示, 先决条件系统的频谱高度集中在一个系统, 特别是当时间步尺寸得到改进时。 这种集群频谱分布非常符合各种示例中观察到的MMSERS( IMER) 和超导性性能性能性能显示我们所实现的PDE( PDE) 的高度精确性能性, 和PDEDALentalityality( ) 例中显示, 。