Explicit single-copy PPT channel with fidelity above the distillation threshold
OpenQAlgorithms.Papers.Independent.Intakethird100.P43.single_copy_fidelityAll operators act on a finite bipartite space in a fixed product basis. Write for Bob's partial transpose and , where . A density operator is positive semidefinite with complex trace exactly one. An admissible PPT map is complex-linear, positive and trace preserving, and is positive on every positive operator. A PPT channel is additionally completely positive; complete positivity of the transpose-conjugated map is not required. Fidelity means the overlap .
Let , , and let be an NPT density operator. Let be the spectral projector of on its strictly negative eigenvalues, and let be the sum of their absolute values. The norm is the operator norm. For
satisfies the isotropic admissibility constraints, and its channel , defined by the two-coefficient formula with , satisfies
This is the constructive single-copy threshold witness; it does not claim single-copy perfect distillation.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P43
noncomputable section
open scoped Matrix ComplexConjugate ComplexOrder
namespace QAlgorithms.Papers.Independent.Intakethird100.P43
attribute [local instance] Classical.propDecidable Classical.decEq
open QAlgorithms.Papers.Independent.Information100.P04
(gamma copies bellProjector negativeProjector werner)
open QAlgorithms.Papers.Independent.Information100.P30 (IsPositiveMap)
/-- PDF p.2, (6)–(7): the explicit single-copy witness, its admissibility and its
channel fidelity, strictly above 1/m. Negativity reuses the frozen first-party scalar;
first- and second-party partial transposes are full transposes and have equal trace norms.
NPT makes P_neg nonzero and the operator-norm reciprocal in the interval nondegenerate. -/
theorem single_copy_fidelity (d m : ℕ) (hd : 0 < d) (hm : 2 ≤ m)
(rho : Matrix (Fin d × Fin d) (Fin d × Fin d) ℂ)
(hrho : IsDensityMatrix rho) (hnpt : ¬ (gamma rho).PosSemidef)
(epsilon : ℝ) (hepsilon : 0 < epsilon)
(hbound : epsilon ≤ min (2 : ℝ) ((specNorm (gamma (negativeProjector rho)))⁻¹)) :
let A := negativeSpaceWitness rho m epsilon
RainsFeasibleEffect m A ∧ IsPositiveConjugatePPTChannel (isotropicPreparation m A) ∧
effectProb A rho = (1 + epsilon * Entanglement.negativity rho) / (m : ℝ) ∧
effectProb (bellProjector m) (isotropicPreparation m A rho) = (1 + epsilon * Entanglement.negativity rho) / (m : ℝ) ∧
1 / (m : ℝ) < effectProb (bellProjector m) (isotropicPreparation m A rho) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P43
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For every pair of natural numbers and , every complex matrix indexed by that is positive semidefinite with trace one, and every real , define and suppose that is not positive semidefinite and
where is obtained by applying the function that is one on negative eigenvalues and zero elsewhere through the continuous functional calculus. Set , let have entry when both row and column pairs have equal components and zero otherwise, and define
Then is Hermitian and , , , and are positive semidefinite. The map is positive and trace preserving, satisfies for every , and is completely positive, meaning that its blockwise extension by an identity map preserves positivity for every finite auxiliary size, including zero. Furthermore,
where , , and . The norm is the Euclidean operator norm; its reciprocal in the hypothesis is defined to be zero if the norm is zero, in which case no positive satisfies the hypothesis.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.