Remark 4: SSA equality gives separability and nonnegative endpoint conditional entropy
OpenQAlgorithms.Papers.Independent.Intakethird100.P97.ssa_endpoint_separableLet be a trace-one positive semidefinite density matrix on arbitrary finite-dimensional complex factors of positive dimension. All entropies are in bits and all marginals are actual partial traces of . Use and . Without assuming SSA equality,
If , then is separable, meaning a finite convex combination of product density matrices, and . This records the structural consequence while identifying the entropy conclusion as a consequence of the basic inequalities.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P97
noncomputable section
namespace QAlgorithms.Papers.Independent.Intakethird100.P97
attribute [local instance] Classical.propDecidable Classical.decEq
local notation "A" => ({0} : Finset (Fin 4))
local notation "B" => ({1} : Finset (Fin 4))
local notation "C" => ({2} : Finset (Fin 4))
local notation "D" => ({3} : Finset (Fin 4))
/-- PDF p.5, Remark 4: the identity and nonnegativity are unconditional; SSA
equality additionally implies separability of AC and S(A|C) ≥ 0. -/
theorem ssa_endpoint_separable {X Y Z : Type*}
[Fintype X] [Fintype Y] [Fintype Z] [Nonempty X] [Nonempty Y] [Nonempty Z]
(rho : Matrix (X × (Y × Z)) (X × (Y × Z)) ℂ) (hrho : IsDensityMatrix rho) :
let sab := vnEntropy (marginalAB3 rho)
let sac := vnEntropy (marginalAC3 rho)
let sbc := vnEntropy (traceLeft rho)
let sa := vnEntropy (traceRight (marginalAB3 rho))
let sb := vnEntropy (traceLeft (marginalAB3 rho))
let sc := vnEntropy (traceLeft (marginalAC3 rho))
let sabc := vnEntropy rho
let acGivenB := sab + sbc - sabc - sb
let abGivenC := sac + sbc - sabc - sc
(2 * (sac - sc) + acGivenB = (sab - sb) + (sac - sc) + abGivenC) ∧
0 ≤ (sab - sb) + (sac - sc) + abGivenC ∧
(acGivenB = 0 → Entanglement.IsSeparableDensity (marginalAC3 rho) ∧ 0 ≤ sac - sc) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P97
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For any finite, nonempty types , each equipped with a finite enumeration, and any positive semidefinite complex matrix of trace indexed by , define matrices
For each of these matrices , put , with applied by functional calculus and . Write , , , , , , and , and set
Then all three assertions hold:
Here . The weight normalization excludes . The quantity is defined but does not occur in these conclusions.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.