Explicit step-truncation tensor methods have recently proven successful in integrating initial value problems for high-dimensional partial differential equations (PDEs). However, the combination of non-linearity and stiffness may introduce time-step restrictions which could make explicit integration computationally infeasible. To overcome this problem, we develop a new class of implicit rank-adaptive algorithms for temporal integration of nonlinear evolution equations on tensor manifolds. These algorithms are based on performing one time step with a conventional time-stepping scheme, followed by an implicit fixed point iteration step involving a rank-adaptive truncation operation onto a tensor manifold. Implicit step truncation methods are straightforward to implement as they rely only on arithmetic operations between tensors, which can be performed by efficient and scalable parallel algorithms. Numerical applications demonstrating the effectiveness of implicit step-truncation tensor integrators are presented and discussed for the Allen-Cahn equation, the Fokker-Planck equation, and the nonlinear Schr\"odinger equation.
翻译:显式步幅截断张量方法最近已被证明可以成功地集成高维偏微分方程(PDE)的初始值问题。然而,非线性和刚性的结合可能引入时间步长限制,这可能使显式积分在计算上变得不可行。为了解决这个问题,我们开发了一类新的隐式秩自适应算法,用于张量流形上非线性演化方程的时间积分。这些算法基于使用传统时间步长方案执行一个时间步骤,然后进行隐式固定点迭代步骤,其中包括一个截断张量流形的秩自适应截断操作。隐式步幅截断方法易于实现,因为它们仅依赖于张量之间的算术运算,这些运算可以通过高效且可扩展的并行算法来执行。为了展示隐式步幅截断张量积分器的有效性,本文介绍并讨论了在Allen-Cahn方程,福克-普朗克方程和非线性薛定谔方程中的数值应用。