On the distance from a matrix polynomial to matrix polynomials with two prescribed eigenvalues
For researchers in matrix polynomial theory, this is an incremental extension of existing results to a two-eigenvalue case.
This paper extends previous work on computing the spectral norm distance from a matrix polynomial to one with a prescribed multiple eigenvalue, now handling two distinct prescribed eigenvalues. It provides lower and upper bounds for this distance, supported by numerical examples.
Consider an $n \times n$ matrix polynomial $P(λ)$. A spectral norm distance from $P(λ)$ to the set of $n \times n$ matrix polynomials that have a given scalar $μ\in\mathbb{C}$ as a multiple eigenvalue was introduced and obtained by Papathanasiou and Psarrakos. They computed lower and upper bounds for this distance, constructing an associated perturbation of $P(λ)$. In this paper, we extend this result to the case of two given distinct complex numbers $μ_{1}$ and $μ_{2}$. First, we compute a lower bound for the spectral norm distance from $P(λ)$ to the set of matrix polynomials that have $μ_1,μ_2$ as two eigenvalues. Then we construct an associated perturbation of $P(λ)$, such that the perturbed matrix polynomial has two given scalars $μ_1$ and $μ_2$ in its spectrum. Finally, we derive an upper bound for the distance by the constructed perturbation of $P(λ)$. Numerical examples are provided to illustrate the validity of the method.