Proposition 12.6 -- nonsingularity of a mixed matrix
OpenDiscreteConvex.MixedMatrices.mixed_matrix_nonsingular_iffalgebracombinatoricsdiscrete-convex-analysis
Proposition 12.6 (p.357). A square mixed matrix is nonsingular if and only if there exist and such that both and are nonsingular.
This is the combinatorial certificate underlying every later result of the chapter: it reduces the (numerically delicate) nonsingularity of a matrix mixing exact and generic entries to a combinatorial search over row/column splits, each half checked in its own, easier arithmetic (numeric determinant for , a bipartite matching argument for , since 's entries are free parameters).
(Murota, Discrete Convex Analysis, SIAM 2003, DOI 10.1137/1.9780898718508, p.357, Proposition 12.6.)
Preamble
import Mathlib import Definitions.Def_DiscreteConvex_MixedMatrices_IsMixedMatrix import Definitions.Def_DiscreteConvex_MixedMatrices_IsNonsingularSub
Formal statement
namespace DiscreteConvex.MixedMatrices
/-- Proposition 12.6 (Murota, *Discrete Convex Analysis*, SIAM 2003, p.357). A square mixed
matrix `A = Q + T` is nonsingular if and only if there exist `I ⊆ R` and `J ⊆ C` such that both
`Q[I,J]` and `T[R\I,C\J]` are nonsingular. -/
theorem mixed_matrix_nonsingular_iff {R C K F : Type*} [Fintype R] [Fintype C] [Field K] [Field F]
[Algebra K F] [DecidableEq R] [DecidableEq C]
(A : Matrix R C F) (Q : Matrix R C K) (T : Matrix R C F) (hA : IsMixedMatrix A Q T)
(hsq : Fintype.card R = Fintype.card C) :
IsNonsingularSub A (Finset.univ : Finset R) (Finset.univ : Finset C) ↔
∃ I : Finset R, ∃ J : Finset C, IsNonsingularSub Q I J ∧ IsNonsingularSub T Iᶜ Jᶜ := by sorry
end DiscreteConvex.MixedMatrices
Source
Murota, Discrete Convex Analysis, SIAM 2003, DOI 10.1137/1.9780898718508, p.357, Proposition 12.6
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.