Proposition 2.4: sufficiency of the zero-marginal perturbation criterion
OpenQAlgorithms.Papers.Independent.Intakethird100.P12.zero_marginal_sufficiencyLet be the dimensions of finite-dimensional complex Hilbert spaces with chosen orthonormal bases. Let be positive semidefinite operators of trace one. Write for all joint density matrices with these two partial traces, and for its extreme points over the real scalars. Coordinates in the tensor product use lexicographic order.
Let have rank .
Set and . Let be a permutation unitary, a complex matrix, and a strictly positive definite matrix satisfying
Here denotes conjugate transpose. Both marginals of are computed in the original tensor coordinates.
Suppose that every Hermitian matrix of order satisfies
Then
This supplies the converse to the necessary perturbation condition, without assuming any factorization of midpoint summands.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P12
namespace QAlgorithms.Papers.Independent.Intakethird100.P12
open scoped ComplexConjugate ComplexOrder
/-- Proposition 2.4, PDF p.7: injectivity is a hypothesis, extremality the conclusion.
No midpoint factorization is imposed as an additional hypothesis. -/
theorem zero_marginal_sufficiency {d1 d2 k : ℕ}
(rho1 : Matrix (Fin d1) (Fin d1) ℂ) (rho2 : Matrix (Fin d2) (Fin d2) ℂ)
(hm1 : IsDensityMatrix rho1) (hm2 : IsDensityMatrix rho2)
(rho : Matrix (Fin d1 × Fin d2) (Fin d1 × Fin d2) ℂ)
(hmem : rho ∈ finiteCouplingSet rho1 rho2) (hrank : rho.rank = k)
(hkn : k < d1*d2) (p : Equiv.Perm (Fin (d1*d2)))
(A : Matrix (Fin k) (Fin (d1*d2-k)) ℂ) (K : Matrix (Fin k) (Fin k) ℂ)
(hK : K.PosDef) (hblock : permuteMatrix p (flatMatrix rho) = rankBlockMatrix hkn.le K A)
(hinjective : NoZeroMarginalPerturbation hkn.le p A) :
rho ∈ Set.extremePoints ℝ (finiteCouplingSet rho1 rho2) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P12
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What the Lean code literally says, in plain math · gpt-6.1-sol
For any natural numbers , let be complex positive semidefinite matrices of sizes , each with trace , and let consist of all positive semidefinite matrices of trace on the product index set whose two partial traces are ; explicitly, these partial traces have entries and , respectively. Suppose , , and . Write , and flatten a product-indexed matrix by . For every permutation of , every complex matrix , and every positive definite complex matrix , assume
where the blocks use the first and last coordinates and denotes conjugate transpose. For each complex matrix , define a product-indexed matrix by
Assume that every Hermitian for which both partial traces vanish,
equals zero. Then is an extreme point of over the real numbers. The hypotheses exclude full rank; they also rule out and zero marginal dimensions because have trace .
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.