On the Two-parameter Matrix pencil Problem

TL;DR

This paper provides a comprehensive solution to the two-parameter matrix pencil problem by transforming it into simpler eigenvalue problems, analyzing symmetries, and presenting an algorithm with numerical examples.

Contribution

It introduces an inflation process and symmetry analysis to reduce the two-parameter MPP to manageable eigenvalue problems, offering a full solution methodology.

Findings

Two-parameter MPP is equivalent to three one-parameter MPPs via inflation.

Symmetry analysis reduces problem dimensions, simplifying numerical solutions.

For square matrices with m=n+1, solutions are guaranteed and countable under certain conditions.

Abstract

The multiparameter matrix pencil problem (MPP) is a generalization of the one-parameter MPP: given a set of $m\times n$ complex matrices $A_0,\ldots, A_r$, with $m\ge n+r-1$, it is required to find all complex scalars $\lambda_0,\ldots,\lambda_r$, not all zero, such that the matrix pencil $A(\lambda)=\sum_{i=0}^r\lambda_iA_i$ loses column rank and the corresponding nonzero complex vector $x$ such that $A(\lambda)x=0$. This problem is related to the well-known multiparameter eigenvalue problem except that there is only one pencil and, crucially, the matrices are not necessarily square. In this paper, we give a full solution to the two-parameter MPP. Firstly, an inflation process is implemented to show that the two-parameter MPP is equivalent to a set of three $m^2\times n^2$ simultaneous one-parameter MPPs. These problems are given in terms of Kronecker commutator operators (involving the original matrices) which exhibit several symmetries. These symmetries are analysed and are then used to deflate the dimensions of the one-parameter MPPs to $\frac{m(m-1)}{2}\times\frac{n(n+1)}{2}$ thus simplifying their numerical solution. In the case that $m=n+1$ it is shown that the two-parameter MPP has at least one solution and generically $\frac{n(n+1)}{2}$ solutions and furthermore that, under a rank assumption, the Kronecker determinant operators satisfy a commutativity property. This is then used to show that the two-parameter MPP is equivalent to a set of three simultaneous eigenvalue problems. A general solution algorithm is presented and numerical examples are given to outline the procedure of the proposed algorithm.