The time-ordered exponential is defined as the function that solves a system of coupled first-order linear differential equations with generally non-constant coefficients. In spite of being at the heart of much system dynamics, control theory, and model reduction problems, the time-ordered exponential function remains elusively difficult to evaluate. The *-Lanczos algorithm is a (symbolic) algorithm capable of evaluating it by producing a tridiagonalization of the original differential system. In this paper, we explain how the *-Lanczos algorithm is built from a generalization of Krylov subspaces, and we prove crucial properties, such as the matching moment property. A strategy for its numerical implementation is also outlined and will be subject of future investigation.
翻译:时间顺序指数被定义为解决一阶线性方程式系统与一般非恒定系数相结合的函数。 尽管时间顺序指数是许多系统动态、控制理论和模型减少问题的核心,但时间顺序指数功能仍然难以评估。 *-Lanczos 算法是一种(共振)算法,它能够通过生成原始差分系统的三对形来评估它。在本文中,我们解释了 *-Lanczos 算法是如何从Krylov 子空间的笼统化中建立起来的,我们证明了关键属性,例如匹配的时空属性。它的数字执行战略也得到了概述,并将成为未来调查的对象。