Amirhossein Amiraslani

Pseudospectra of Matrix Polynomials that Are Expressed in Alternative Bases

Abstract.Spectra and pseudospectra of matrix polynomials are of interest in geometric intersection problems, vibration problems, and analysis of dynamical systems. In this note we consider the effect of the choice of polynomial basis on the pseudospectrum and on the conditioning of the spectrum of regular matrix polynomials. In particular, we consider the direct use of the Lagrange basis on distinct interpolation nodes, and give a geometric characterization of “good” nodes. We also give some tools for computation of roots at infinity via a new, natural, reversal. The principal achievement of the paper is to connect pseudospectra to the well-established theory of Lebesgue functions and Lebesgue constants, by separating the influence of the scalar basis from the natural scale of the matrix polynomial, which allows many results from interpolation theory to be applied.

Rayleigh quotient algorithms for nonsymmetric matrix pencils

A classical Rayleigh-quotient iterative algorithm (known as “broken iteration”) for finding eigenvalues and eigenvectors is applied to semisimple regular matrix pencils A − λB. It is proved that cubic convergence is attained for eigenvalues and superlinear convergence of order three for eigenvectors. Also, each eigenvalue has a local basin of attraction. A closely related Newton algorithm is examined. Numerical examples are included.

Block LU factors of generalized companion matrix pencils

We present formulas for computations involving companion matrix pencils as may arise in considering polynomial eigenvalue problems. In particular, we provide explicit companion matrix pencils for matrix polynomials expressed in a variety of polynomial bases including monomial, orthogonal, Newton, Lagrange, and Bernstein/Bezier bases. Additionally, we give a pair of explicit LU factors associated with each pencil and a prescription for block pivoting when required.

The equivalence of the constrained Rayleigh quotient and Newton methods for matrix polynomials expressed in different polynomial bases along with the confluent case

We show that using the constrained Rayleigh quotient method to find the eigenvalues of matrix polynomials in different polynomial bases is equivalent to applying the Newton method to certain functions. We find those functions explicitly for a variety of polynomial bases including monomial, orthogonal, Newton, Lagrange and Bernstein bases. In order to do so, we provide explicit symbolic formulas for the right and left eigenvectors of the generalized companion matrix pencils for matrix polynomials expressed in those bases. Using the properties of the Newton basis, we also find two different formulas for the companion matrix pencil corresponding to the Hermite interpolation. We give pairs of explicit LU factors associated with these pencils. Additionally, we explicitly find the right and left eigenvectors for each of these pencils.

Notes on linear factor polynomial deflation in polynomial bases

Scalar polynomials as approximations to more general scalar functions lead to the study of scalar polynomials represented in a variety of classical systems of polynomials, including orthogonal systems and Lagrange polynomials, for example. This article, motivated in part by analogy with the existing methods for linear factor polynomial deflation in the monomial basis, finds forward and backward deflation formulae for several such representations. It also finds the sensitivity factor of the deflation process for each representation.