For several classes of mathematical models that yield linear systems, the splitting of the matrix into its Hermitian and skew Hermitian parts is naturally related to properties of the underlying model. This is particularly so for discretizations of dissipative Hamiltonian ODEs, DAEs and port Hamiltonian systems where, in addition, the Hermitian part is positive definite or semi-definite. It is then possible to develop short recurrence optimal Krylov subspace methods in which the Hermitian part is used as a preconditioner. In this paper we develop new, right preconditioned variants of this approach which as their crucial new feature allow the systems with the Hermitian part to be solved only approximately in each iteration while keeping the short recurrences. This new class of methods is particularly efficient as it allows, for example, to use few steps of a multigrid solver or a (preconditioned) CG method for the Hermitian part in each iteration. We illustrate this with several numerical experiments for large scale systems.
翻译:对于产生线性系统的几类数学模型来说,将矩阵分解成其埃米提亚部分和扭曲赫米提亚部分自然地与基本模型的特性相关。对于分离的散落汉密尔顿核糖核酸、DAEs和港汉密尔顿核酸系统来说尤其如此,此外,Hermitian部分是肯定的或半限定的。然后有可能开发短时间重现的最佳Krylov子空间方法,将赫米提亚部分用作先决条件。在本文中,我们开发了这一方法的新的、正确的、有先决条件的变体,作为这些变体的关键新特性,使赫米提亚部分的系统只在每次循环中大致解决,同时保持短时间重现。这一新的方法类别特别有效,例如它允许在每次循环中使用赫米提亚部分使用几步多电网求解器或(预设的)CG方法。我们用一些大规模系统的数字实验来说明这一点。