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Concatenating a source identity with a relative communication identity

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QAlgorithms.Papers.Independent.Intakethird100.P64.sourceIdentityConcatenation

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

prove2quantum

Let SSS be a finite nonzero source register with density matrix ρ\rhoρ, purified by a unit vector ∣ϕ⟩RS|\phi\rangle^{RS}∣ϕ⟩RS. The reference RRR is inaccessible to Alice and Bob. The registers A^,A′,B,B^\widehat A,A',B,\widehat BA,A′,B,B are identified copies of SSS, so the two occurrences of ρ\rhoρ denote the same density under relabeling. Then

⟨idS→A^:ρ⟩+⟨idA′→B:ρ⟩≥⟨idS→B^:ρ⟩.\langle\mathrm{id}^{S\to\widehat A}:\rho\rangle+ \langle\mathrm{id}^{A'\to B}:\rho\rangle \ge\langle\mathrm{id}^{S\to\widehat B}:\rho\rangle.⟨idS→A:ρ⟩+⟨idA′→B:ρ⟩≥⟨idS→B:ρ⟩.

For every positive error and rate slack, all sufficiently large positive nnn have local encoding and decoding maps using nnn supplied identity-channel calls on the nnn Source-supplied systems. For every positive input-promise tolerance η\etaη, the actual encoded input marginal is within η\etaη of ρ⊗n\rho^{\otimes n}ρ⊗n. The code succeeds jointly with RnR^nRn for every physical implementation of the relative identity satisfying its joint error guarantee on inputs with that near-IID marginal. The local maps are chosen before that implementation is supplied. No additional communication or shared state is supplied.

This is direct routing of the specified source, rather than a general transitivity principle for arbitrary resources.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P64
Formal statement
noncomputable section

namespace QAlgorithms.Papers.Independent.Intakethird100.P64

open QAlgorithms

open QAlgorithms.Papers.Independent.Gap48.P20
  (Copies redistributionMarginal subsystemEntropy forwardApply)

open QAlgorithms.Papers.Independent.Dependency50.P48 (densityPower)

open scoped Matrix ComplexConjugate

attribute [local instance] Classical.propDecidable Classical.decEq

/-- PDF p.3, unnumbered display and Fig.3: concatenate the Source-to-Alice
identity with the relative Alice-to-Bob identity for the same rho. The actual
source purification and the encoder's marginal are part of the operational test. -/
theorem sourceIdentityConcatenation {R S : Type} [Fintype R] [Fintype S]
    [Nonempty R] [Nonempty S] (phi : EuclideanSpace ℂ (R × S))
    (hphi : IsState phi) : SourceRoutingAchievable phi := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P64

end
Source
A triangle of dualities: reversibly decomposable quantum channels, source-channel duality, and time reversal, arXiv:quant-ph/0505138v1, PDF p. 3, Fully quantum Slepian-Wolf preamble: source/identity concatenation
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What the Lean code literally says, in plain math · gpt-6.1-sol

For nonempty types R,SR,SR,S equipped with finite enumerations and every vector ϕ∈CR×S\phi\in\mathbb C^{R\times S}ϕ∈CR×S with ∥ϕ∥=1\|\phi\|=1∥ϕ∥=1, define

ρs,t=∑rϕ(r,s)ϕ(r,t)‾,Dn[(r,s),(r′,t)]=∏i=0n−1ϕ(ri,si) ∏i=0n−1ϕ(ri′,ti)‾,(ρ⊗n)s,t=∏iρsi,ti.\rho_{s,t}=\sum_r\phi(r,s)\overline{\phi(r,t)},\qquad D_n[(r,s),(r',t)] =\prod_{i=0}^{n-1}\phi(r_i,s_i)\, \overline{\prod_{i=0}^{n-1}\phi(r'_i,t_i)},\qquad (\rho^{\otimes n})_{s,t}=\prod_i\rho_{s_i,t_i}.ρs,t​=r∑​ϕ(r,s)ϕ(r,t)​,Dn​[(r,s),(r′,t)]=i=0∏n−1​ϕ(ri​,si​)i=0∏n−1​ϕ(ri′​,ti​)​,(ρ⊗n)s,t​=i∏​ρsi​,ti​​.

The theorem asserts that for every ε>0,δ>0\varepsilon>0,\delta>0ε>0,δ>0, there exists N∈NN\in\mathbb NN∈N such that for every n≥Nn\ge Nn≥N with n≥1n\ge1n≥1, there exist channels E,D\mathcal E,\mathcal DE,D on matrices indexed by SnS^nSn satisfying n≤n(1+δ)n\le n(1+\delta)n≤n(1+δ) and, for every η>0\eta>0η>0,

∥tr⁡Rn(id⁡Rn⊗E)(Dn)−ρ⊗n∥1≤η,\left\|\operatorname{tr}_{R^n}(\operatorname{id}_{R^n}\otimes\mathcal E)(D_n) -\rho^{\otimes n}\right\|_1\le\eta,​trRn​(idRn​⊗E)(Dn​)−ρ⊗n​1​≤η,

and the following statement for every channel FFF on those matrices: if, for every positive integer ddd and positive semidefinite trace-one matrix σ\sigmaσ on {0,…,d−1}×Sn\{0,\ldots,d-1\}\times S^n{0,…,d−1}×Sn,

∥tr⁡{0,…,d−1}σ−ρ⊗n∥1≤η ⟹ ∥(id⁡d⊗F)(σ)−σ∥1≤ε,\left\|\operatorname{tr}_{\{0,\ldots,d-1\}}\sigma-\rho^{\otimes n}\right\|_1\le\eta \ \Longrightarrow\ \|(\operatorname{id}_d\otimes F)(\sigma)-\sigma\|_1\le\varepsilon,​tr{0,…,d−1}​σ−ρ⊗n​1​≤η ⟹ ∥(idd​⊗F)(σ)−σ∥1​≤ε,

then

∥(id⁡Rn⊗(D∘F∘E))(Dn)−Dn∥1≤ε.\|(\operatorname{id}_{R^n}\otimes(\mathcal D\circ F\circ\mathcal E))(D_n)-D_n\|_1 \le\varepsilon.∥(idRn​⊗(D∘F∘E))(Dn​)−Dn​∥1​≤ε.

A channel here means a matrix function T(X)=∑j=0a−1KjXKj†T(X)=\sum_{j=0}^{a-1}K_jXK_j^\daggerT(X)=∑j=0a−1​Kj​XKj†​ for some finite Kraus family with ∑jKj†Kj=I\sum_jK_j^\dagger K_j=I∑j​Kj†​Kj​=I; partial traces sum diagonal blocks, and tensoring TTT with an identity applies TTT to each reference-index block. The trace norm is ∥M∥1=Re⁡tr⁡M†M\|M\|_1=\operatorname{Re}\operatorname{tr}\sqrt{M^\dagger M}∥M∥1​=RetrM†M​. The channels are chosen independently of η\etaη, so their displayed marginal difference must have norm zero.

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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