Mixed polynomial matrix (Eq. 12.8)
DefinitionDiscreteConvex_MixedMatrices_IsMixedPolyMatrixalgebradiscrete-convex-analysis
(Eq. (12.8)) is a mixed polynomial matrix with respect to : has all coefficients over (axiom (MP-Q)) embedded into via Polynomial.map, has coefficients over (axiom (MP-T)), and the family of all nonzero coefficients of all entries of (indexed by row, column, and degree) is algebraically independent over .
(Murota, Discrete Convex Analysis, SIAM 2003, DOI 10.1137/1.9780898718508, p.355, Eq. (12.8).)
Definition code
import Mathlib
/-!
Murota, *Discrete Convex Analysis*, SIAM 2003, p.355, Eq. (12.8), axioms (MP-Q), (MP-T): the
definition of a mixed polynomial matrix, in `DiscreteConvex.MixedMatrices`.
-/
namespace DiscreteConvex.MixedMatrices
/-- `A(s) = Q(s) + T(s)` (Eq. (12.8)) is a **mixed polynomial matrix** with respect to `(K, F)`:
`Q(s)` has all coefficients over `K` (axiom (MP-Q)) embedded into `F[s]` via `Polynomial.map`,
`T(s)` has coefficients over `F` (axiom (MP-T)), and the family of all nonzero coefficients of all
entries of `T(s)` is algebraically independent over `K`. -/
def IsMixedPolyMatrix {R K F : Type*} [Fintype R] [Field K] [Field F] [Algebra K F]
(A : Matrix R R (Polynomial F)) (Q : Matrix R R (Polynomial K)) (T : Matrix R R (Polynomial F)) :
Prop :=
(∀ i j, A i j = (Q i j).map (algebraMap K F) + T i j) ∧
AlgebraicIndependent K
(fun e : {p : R × R × ℕ // (T p.1 p.2.1).coeff p.2.2 ≠ 0} =>
(T e.1.1 e.1.2.1).coeff e.1.2.2)
end DiscreteConvex.MixedMatrices
Source
Murota, Discrete Convex Analysis, SIAM 2003, DOI 10.1137/1.9780898718508, p.355, Eq. (12.8)