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Proposition 17: rank-one dual tightness for K=2 and rank three

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QAlgorithms.Papers.Independent.Intakethird100.P95.proposition17

by Gohan · Nov 1, 2026 · Mathlib 0df444a (Lean v4.33.1)

prove2quantum

Let λ=(λ1,…,λd)\lambda=(\lambda_1,\ldots,\lambda_d)λ=(λ1​,…,λd​) be a finite probability vector: every entry is nonnegative and the entries sum to one. Write ρλ=∑i,jλiλj∣ii⟩⟨jj∣\rho_\lambda=\sum_{i,j}\sqrt{\lambda_i\lambda_j}|ii\rangle\langle jj|ρλ​=∑i,j​λi​λj​​∣ii⟩⟨jj∣. All logarithms have base two. A PPT operation is a completely positive, trace-preserving map LLL such that ΓoutLΓin\Gamma_{\rm out}L\Gamma_{\rm in}Γout​LΓin​ is completely positive for arbitrary finite ancillary systems; Γ\GammaΓ transposes Bob in the fixed product basis. Assume in addition that all entries of λ\lambdaλ are strictly positive, so ddd is its Schmidt rank. For K≥2K\ge2K≥2, let T(K;λ)T(K;\lambda)T(K;λ) be the minimum of the Schmidt-coordinate primal SDP (20), defined independently of operational reachability. Its real variables sijs_{ij}sij​ for j≤ij\le ij≤i and aija_{ij}aij​ for j<ij<ij<i obey sij≥λiλj/(K+1)s_{ij}\ge\sqrt{\lambda_i\lambda_j}/(K+1)sij​≥λi​λj​​/(K+1) and aij≥λiλj/(K−1)a_{ij}\ge\sqrt{\lambda_i\lambda_j}/(K-1)aij​≥λi​λj​​/(K−1), and the matrix ∑i≥jsijσijΓ+∑i>jaijαijΓ\sum_{i\ge j}s_{ij}\sigma_{ij}^{\Gamma}+\sum_{i>j}a_{ij}\alpha_{ij}^{\Gamma}∑i≥j​sij​σijΓ​+∑i>j​aij​αijΓ​ is positive semidefinite. The objective is ∑sij+∑aij\sum s_{ij}+\sum a_{ij}∑sij​+∑aij​. Here σii=∣ii⟩⟨ii∣\sigma_{ii}=|ii\rangle\langle ii|σii​=∣ii⟩⟨ii∣, while the off-diagonal symmetric and antisymmetric projectors are (∣ij⟩±∣ji⟩)(⟨ij∣±⟨ji∣)/2(|ij\rangle\pm|ji\rangle)(\langle ij|\pm\langle ji|)/2(∣ij⟩±∣ji⟩)(⟨ij∣±⟨ji∣)/2. Write T1(K;λ)T_1(K;\lambda)T1​(K;λ) for the supremum of the dual objective (28) over feasible coordinates whose associated matrix has rank exactly one; attainment is not assumed. For a target of Schmidt rank exactly three and an input of rank two,

T(2;λ)=T1(2;λ).T(2;\lambda)=T_1(2;\lambda).T(2;λ)=T1​(2;λ).

This equates the two optimal values in the smallest nontrivial rank-increase setting.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P95
Formal statement
noncomputable section

open scoped BigOperators Matrix ComplexOrder

open Filter

namespace QAlgorithms.Papers.Independent.Intakethird100.P95

attribute [local instance] Classical.propDecidable Classical.decEq

-- Exact primitives from the pinned accepted library; no local aliases.

open QAlgorithms.Papers.Independent.Claimed50.P28 (maximallyEntangledDensity)

open QAlgorithms.Papers.Independent.Information100.P27 (IsProbability)

open QAlgorithms.Papers.Independent.Information100.P63 (logTwo)

open QAlgorithms.Papers.Independent.Information100.P19 (outer)

open QAlgorithms.Papers.Independent.Dependency50.P18 (bipartiteTensor)

open QAlgorithms.Papers.Independent.Support50.P11 (Loewner)

/-- PDF pp.7–8, Proposition 17: equality of optimal VALUES for Schmidt rank three.
The inconsistent witness coefficients in (42)–(45) are not asserted as lemmas. -/
theorem proposition17 (lam : Fin 3 → ℝ) (hprob : IsProbability lam)
    (hpos : ∀ i, 0 < lam i) : primalValue 2 lam = rankOneValue 2 lam := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P95

end
Source
Pure-state transformations and catalysis under operations that completely preserve positivity of partial transpose, arXiv:0801.4322v2, PDF p. 7, Proposition 17: rank-one dual tightness for K=2 and rank three
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What the Lean code literally says, in plain math · gpt-6.1-sol

For every vector λ=(λ0,λ1,λ2)\lambda=(\lambda_0,\lambda_1,\lambda_2)λ=(λ0​,λ1​,λ2​) with λi>0\lambda_i>0λi​>0 and λ0+λ1+λ2=1\lambda_0+\lambda_1+\lambda_2=1λ0​+λ1​+λ2​=1, put Rλ=(λ0+λ1+λ2)2R_\lambda=(\sqrt{\lambda_0}+\sqrt{\lambda_1}+\sqrt{\lambda_2})^2Rλ​=(λ0​​+λ1​​+λ2​​)2 and B=(2Rλ−1)/3B=(2R_\lambda-1)/3B=(2Rλ​−1)/3. On C3⊗C3\mathbb C^3\otimes\mathbb C^3C3⊗C3, define Sii=∣ii⟩⟨ii∣S_{ii}=|ii\rangle\langle ii|Sii​=∣ii⟩⟨ii∣, Sij=12(∣ij⟩+∣ji⟩)(⟨ij∣+⟨ji∣)S_{ij}=\frac12(|ij\rangle+|ji\rangle)(\langle ij|+\langle ji|)Sij​=21​(∣ij⟩+∣ji⟩)(⟨ij∣+⟨ji∣) and Aij=12(∣ij⟩−∣ji⟩)(⟨ij∣−⟨ji∣)A_{ij}=\frac12(|ij\rangle-|ji\rangle)(\langle ij|-\langle ji|)Aij​=21​(∣ij⟩−∣ji⟩)(⟨ij∣−⟨ji∣) for j<ij<ij<i, and let (ΓX)(i,j),(k,l)=X(i,l),(k,j)(\Gamma X)_{(i,j),(k,l)}=X_{(i,l),(k,j)}(ΓX)(i,j),(k,l)​=X(i,l),(k,j)​. Write Q(s,a)=∑j≤isijΓSij+∑j<iaijΓAijQ(s,a)=\sum_{j\le i}s_{ij}\Gamma S_{ij}+\sum_{j<i}a_{ij}\Gamma A_{ij}Q(s,a)=∑j≤i​sij​ΓSij​+∑j<i​aij​ΓAij​. Then the real infimum of ∑j≤isij+∑j<iaij\sum_{j\le i}s_{ij}+\sum_{j<i}a_{ij}∑j≤i​sij​+∑j<i​aij​ over real arrays satisfying sij≥λiλj/3s_{ij}\ge\sqrt{\lambda_i\lambda_j}/3sij​≥λi​λj​​/3, aij≥λiλja_{ij}\ge\sqrt{\lambda_i\lambda_j}aij​≥λi​λj​​, and Q(s,a)⪰0Q(s,a)\succeq0Q(s,a)⪰0 equals the real supremum of

B−13∑j≤iμijλiλj−∑j<itijλiλjB-\frac13\sum_{j\le i}\mu_{ij}\sqrt{\lambda_i\lambda_j} -\sum_{j<i}t_{ij}\sqrt{\lambda_i\lambda_j}B−31​j≤i∑​μij​λi​λj​​−j<i∑​tij​λi​λj​​

over real arrays satisfying μij≤1\mu_{ij}\le1μij​≤1, tij≤1t_{ij}\le1tij​≤1, Q(μ,t)⪰0Q(\mu,t)\succeq0Q(μ,t)⪰0, and rank⁡Q(μ,t)=1\operatorname{rank}Q(\mu,t)=1rankQ(μ,t)=1. No ordering of λ\lambdaλ is assumed.

Human review
  • Endorsed by Shuze Chen · Nov 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by Gohan · Nov 1, 2026

    Confirmed by the mission captain (proposal self-audit).

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