Definite Matrix Polynomials and their Linearization by Definite Pencils
نویسندگان
چکیده
Hyperbolic matrix polynomials are an important class of Hermitian matrix poly-nomials that contain overdamped quadratics as a special case. They share with definite pencils the spectral property that their eigenvalues are real and semisimple. We extend the definition of hyperbolic matrix polynomial in a way that relaxes the requirement of definiteness of the leading coefficient matrix, yielding what we call definite polynomials. We show that this class of polynomials has an elegant characterization in terms of definiteness intervals on the extended real line, and that it includes definite pencils as a special case. A fundamental question is whether a definite matrix polynomial P can be linearized in a structure-preserving way. We show that the answer to this question is affirmative: P is definite if and only if it has a definite linearization in H(P), a certain vector space of Hermitian pencils; and for definite P we give a complete characterization of all the linearizations in H(P) that are definite. For the important special case of quadratics, we show how a definite quadratic polynomial can be transformed into a definite linearization with a positive definite leading coefficient matrix—a form that is particularly attractive numerically.
منابع مشابه
Hermitian Matrix Polynomials with Real Eigenvalues of Definite Type. Part I: Classification
The spectral properties of Hermitian matrix polynomials with real eigenvalues have been extensively studied, through classes such as the definite or definitizable pencils, definite, hyperbolic, or quasihyperbolic matrix polynomials, and overdamped or gyroscopically stabilized quadratics. We give a unified treatment of these and related classes that uses the eigenvalue type (or sign characterist...
متن کاملLinearization of Lagrange and Hermite interpolating matrix polynomials
This paper considers interpolating matrix polynomials P (λ) in Lagrange and Hermite bases. A classical approach to investigate the polynomial eigenvalue problem P (λ)x = 0 is linearization, by which the polynomial is converted into a larger matrix pencil with the same eigenvalues. Since the current linearizations of degree n Lagrange polynomials consist of matrix pencils with n + 2 blocks, they...
متن کاملSymmetric Linearizations for Matrix Polynomials
A standard way of treating the polynomial eigenvalue problem P (λ)x = 0 is to convert it into an equivalent matrix pencil—a process known as linearization. Two vector spaces of pencils L1(P ) and L2(P ), and their intersection DL(P ), have recently been defined and studied by Mackey, Mackey, Mehl, and Mehrmann. The aim of our work is to gain new insight into these spaces and the extent to which...
متن کاملEla Linearizations of Singular Matrix Polynomials and the Recovery of Minimal Indices∗
A standard way of dealing with a regular matrix polynomial P (λ) is to convert it into an equivalent matrix pencil – a process known as linearization. Two vector spaces of pencils L1(P ) and L2(P ) that generalize the first and second companion forms have recently been introduced by Mackey, Mackey, Mehl and Mehrmann. Almost all of these pencils are linearizations for P (λ) when P is regular. Th...
متن کاملRayleigh-Ritz and Lanctos Methods for Symmetric Matrix Pencils*
We are concerned with eigenvalue problems for definite and indefinite symmetric matrix pencils. First, Rayleigh-Ritz methods are formulated and, using Krylov subspaces, a convergence analysis is presented for definite pencils. Second, generalized symmetric Lanczos algorithms are introduced as a special Rayleigh-Ritz method. In particular, an a posteriori convergence criterion is demonstrated by...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- SIAM J. Matrix Analysis Applications
دوره 31 شماره
صفحات -
تاریخ انتشار 2009