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The first Frobenius companion pencil preserves the finite and infinite polynomial spectrum
Statement
Let be a regular grade- matrix polynomial with , and let be the pencil of First Frobenius companion pencil of a matrix polynomial. A square matrix polynomial is unimodular when its determinant is a nonzero constant. The pencil is a strong linearization of if there are unimodular polynomial matrices with and unimodular polynomial matrices with . Such matrices exist. In particular, ; finite eigenvectors correspond by ; and the infinite eigenspaces correspond by from to . The algebraic multiplicity of infinity in both problems is . Thus if is invertible there are no infinite eigenvalues; if is singular there is at least one, with geometric multiplicity , which need not equal its algebraic multiplicity.
Facts & Assumptions
Given: A regular square matrix polynomial of grade over .
Regular matrix polynomials and homogeneous eigenpairs: ; finite multiplicities are zero orders of , while the multiplicity at infinity is the zero order of at .
First Frobenius companion pencil of a matrix polynomial: has top block row , lower rows on adjacent blocks, and .
Proof
For , partition the columns of as and , and the rows as the top block row and the lower block rows; write the resulting blocks as . The lower-left block is upper block-bidiagonal with on its diagonal and on its superdiagonal. Thus for the nilpotent upper block shift , so is polynomial and . The lower equations with zero right-hand side are ; solving them gives . Substitution into the top row shows that the Schur complement is . To compute the determinant, swap the top and lower row groups, with sign , obtaining . Left multiplication by has determinant one and gives , whose determinant is . Since , the total sign is , so . For , directly.
For the partition in step 1.1, left multiplication by clears the top-left block and leaves in the top-right block, since . Left multiplication of the lower rows by makes the lower-left block and the lower-right block . Right multiplication by clears that lower-right block; a block-column permutation then gives . Each operation and its inverse has polynomial entries and determinant a nonzero constant, so their products are unimodular.
Put . If , then , so step 1.1 gives . Both sides are polynomials in . Fix any ; the identity holds for every , so their coefficients in powers of agree. Each such coefficient is a polynomial in and agrees for every ; as univariate polynomials with infinitely many common values they are identical, so the identity holds also at . For finite , the lower rows of force ; if then , and the top row is . Conversely, for each nonzero with , the lift in [F2] is nonzero and the lower rows vanish while the top row is . At infinity, , so its kernel consists exactly of with .
For the reversal pencil , reorder the block columns as . Its lower equations are ; on the first reordered block columns their coefficient matrix is lower block-bidiagonal with on its diagonal and on its subdiagonal, so its determinant is and its inverse is polynomial by the finite nilpotent-shift expansion. Solving these equations gives ; substitution into the top row gives . The same row elimination, normalization by this polynomial inverse, column clearing, and block permutation used in step 2.1 therefore give by unimodular polynomial matrices. For the reversal pencil equals directly.
The reversal determinant identity is . If , write with ; then , whose zero order at is exactly . Step 3.1 shows the reversal pencil has the same zero order, and step 2.2 identifies the homogeneous companion spectrum and eigenspaces. In the permutation expansion of , every product has factors of degree at most ; degree can occur only by taking the coefficient from each factor, so its coefficient is . Thus invertibility of is equivalent to and no infinity eigenvalue; singularity gives and positive multiplicity at infinity. The geometric multiplicity is by step 2.2 and is not used to infer the zero order.
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Sources
- D. Steven Mackey, Niloufer Mackey, and Françoise Tisseur, Polynomial Eigenvalue Problems: Theory, Computation, and Structure, §3 (standard reference, not scraped)
- Françoise Tisseur and Karl Meerbergen, The Quadratic Eigenvalue Problem, §§3.1 and 3.4 (standard reference, not scraped)