Equivalences for Linearizations of Matrix Polynomials
Robert M. Corless, Leili Rafiee Sevyeri, B. David Saunders

TL;DR
This paper explores new methods for establishing equivalences between matrix polynomials and their linearizations, providing explicit constructions and analyzing their limitations using algebraic and computational techniques.
Contribution
It introduces a novel approach using Hermite Normal Form algorithms to find unimodular cofactors that demonstrate equivalence of matrix polynomials and their linearizations.
Findings
New explicit constructions for linearizations in different polynomial bases
Comparison of unimodular pairs with those from strict equivalence
Discussion on limitations of computational methods for finding unimodular cofactors
Abstract
One useful standard method to compute eigenvalues of matrix polynomials of degree at most in (denoted of grade , for short) is to first transform to an equivalent linear matrix polynomial , called a companion pencil, where and are usually of larger dimension than but is now only of grade in . The eigenvalues and eigenvectors of can be computed numerically by, for instance, the QZ algorithm. The eigenvectors of , including those for infinite eigenvalues, can also be recovered from eigenvectors of if is what is called a "strong linearization" of . In this paper we show how to use algorithms for computing the Hermite Normal Form of a companion matrix for a scalar polynomial…
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