English

A Unifying Framework for Doubling Algorithms

Numerical Analysis 2026-02-10 v1 Numerical Analysis

Abstract

The existing doubling algorithms have been proven efficient for several important nonlinear matrix equations arising from real-world engineering applications. In a nutshell, the algorithms iteratively compute a basis matrix, in one of the two particular forms, for the eigenspace of some matrix pencil associated with its eigenvalues in certain complex region such as the left-half plane or the open unit disk, and their success critically depends on that the interested eigenspace do have a basis matrix taking one of the two particular forms. However, that requirement in general cannot be guaranteed. In this paper, a new doubling algorithm, called the QQ-doubling algorithm, is proposed. It includes the existing doubling algorithms as special cases and does not require that the basis matrix takes one of the particular forms. An application of the QQ-doubling algorithm to solve eigenvalue problems is investigated with numerical experiments that demonstrate its superior robustness to the existing doubling algorithms.

Keywords

Cite

@article{arxiv.2602.07250,
  title  = {A Unifying Framework for Doubling Algorithms},
  author = {Changli Liu and Tiexiang Li and Jungong Xue and Ren-Cang Li and Wen-Wei Lin},
  journal= {arXiv preprint arXiv:2602.07250},
  year   = {2026}
}