PPT support-overlap weak duality with one-sided constraints
OpenQAlgorithms.Papers.Independent.Intakethird100.P90.ppt_support_weak_dualityAll systems are finite-dimensional complex Hilbert spaces with fixed orthonormal product bases and positive local dimensions. A state is a positive semidefinite operator of trace one. All logarithms are base two and all operational rates are measured in standard Bell pairs (ebits) per input copy, with deterministic operations and error tending to zero. Write for distillable entanglement and entanglement cost under completely PPT-preserving CPTP operations; an explicit LOCC subscript denotes unrestricted two-way local operations and classical communication.
Let be a bipartite state, its support projection, and the normalized PPT states. Define the two optimization values independently. Then
The maximum and minimum are attained. The dual has only the displayed one-sided inequalities. The result asserts weak duality and does not identify the values by an additional equality.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P90
noncomputable section
open scoped Matrix ComplexConjugate ComplexOrder
namespace QAlgorithms.Papers.Independent.Intakethird100.P90
attribute [local instance] Classical.propDecidable Classical.decEq
open QAlgorithms
open QAlgorithms.Papers.Independent.Dependency50.P36
(relativeEntropy rains target canonicalMatrix allowed pptDistillable)
open QAlgorithms.Papers.Independent.Information100.P04 (gamma copies IsPPT)
open QAlgorithms.Papers.Independent.Next46.P42 (regroupProduct)
open QAlgorithms.Papers.Independent.Information100.P06 (supportProjection)
open QAlgorithms.Papers.Independent.Information100.P21 (FiniteLOCC)
open QAlgorithms.Papers.Independent.Gap48.P32 (antisymmetricQutrit)
/-- arXiv:1606.09421v3, PDF p.7, Eq.(16): weak duality with exactly the
two ONE-SIDED constraints. The source's maximum and minimum are attained;
no equality of these independently defined values is claimed here. -/
theorem ppt_support_weak_duality {A B : Type} [Fintype A] [Fintype B]
[DecidableEq A] [DecidableEq B] [Nonempty A] [Nonempty B]
(rho : Matrix (A × B) (A × B) ℂ) (hstate : IsDensityMatrix rho) :
supportOverlap rho ≤ supportDual rho ∧
(∃ sigma : Matrix (A × B) (A × B) ℂ, IsPPT sigma ∧
(supportProjection rho * sigma).trace.re = supportOverlap rho) ∧
(∃ Y, supportDualFeasible rho (supportDual rho) Y) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P90
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For any nonempty finite types , each equipped with decidable equality, and every complex matrix indexed by with and , write , and let be the functional-calculus value at of the function that is zero at zero and one elsewhere. Define
Then ; there exists a matrix satisfying , , and for which ; and there exists a Hermitian with and . The infimum ranges over all real , with no separate sign restriction.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.