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Corollary 1: evaluation along every successive binary partition

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QAlgorithms.Papers.Independent.Intakethird100.P63.corollary1_binaryEvaluation

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

prove2quantum

All states below are positive trace-class density operators of trace one on completed complex Hilbert tensor products, represented in countable orthonormal coordinates. Finite dimensional systems are included. Entropies use natural logarithms and the convention 0log⁡0=00\log 0=00log0=0. Every subsystem entropy occurring in an entropy difference is finite; this is the proof-supported finite-entropy reading of the source, and imposes no finite Hilbert dimension.

Let N≥2N\ge2N≥2 and let ρ\rhoρ be an NNN-party state. Consider any finite full binary partition tree whose root is the full party set, whose children are disjoint nonempty clusters partitioning their parent, and whose leaves are the singleton parties. If Lv,RvL_v,R_vLv​,Rv​ are the two child clusters of internal node vvv, define I(A:B)=SA+SB−SA∪BI(A:B)=S_A+S_B-S_{A\cup B}I(A:B)=SA​+SB​−SA∪B​ using the actual marginals. Then

I{1,…,N}=∑v internalI(Lv:Rv).I_{\{1,\ldots,N\}}=\sum_{v\text{ internal}} I(L_v:R_v).I{1,…,N}​=v internal∑​I(Lv​:Rv​).

The result evaluates total correlation using arbitrary successive binary choices, including the final split into two singletons.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P63
Formal statement
noncomputable section

open scoped ENNReal BigOperators

namespace QAlgorithms.Papers.Independent.Intakethird100.P63

attribute [local instance] Classical.propDecidable Classical.decEq

-- Reuse the accepted nuclear trace-class, positive, trace-one predicate verbatim.

open QAlgorithms.Papers.Independent.Dependency50.P33 (IsDensity)

open QAlgorithms.Papers.Independent.Dependency50.P13 (finiteRelativeEntropy)

/-- Corollary 1, PDF p.3: every valid full binary partition tree evaluates the same
total correlation, retaining all within-cluster terms until the singleton leaves. -/
theorem corollary1_binaryEvaluation {n : ℕ} (hn : 2 ≤ n)
    (rho : (Matrix (Fin n → ℕ) (Fin n → ℕ) ℂ)) (hrho : IsDensity rho)
    (hfinite : FiniteSubsystemEntropies rho)
    (t : BinaryTree n) (ht : t.Valid) (hroot : t.parties = Finset.univ) :
    clusterInformation rho Finset.univ = t.information rho := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P63

end
Source
On Mutual Information in Multipartite Quantum States and Equality in Strong Subadditivity of Entropy, arXiv:quant-ph/0311193v1, PDF p. 3, Corollary 1: evaluation by arbitrary successive binary partitions
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What the Lean code literally says, in plain math · gpt-6.1-sol

For every natural number n≥2n\ge2n≥2 and complex kernel ρ\rhoρ on Nn\mathbb N^nNn, assume that it admits an entrywise expansion ρ(i,j)=∑rar(i)br(j)‾\rho(i,j)=\sum_r a_r(i)\overline{b_r(j)}ρ(i,j)=∑r​ar​(i)br​(j)​ with square-summable vectors and summable products ∥ar∥∥br∥\|a_r\|\|b_r\|∥ar​∥∥br​∥, that every finite quadratic form ∑i,j∈Fzi‾ρ(i,j)zj\sum_{i,j\in F}\overline{z_i}\rho(i,j)z_j∑i,j∈F​zi​​ρ(i,j)zj​ is real and nonnegative for arbitrary finite FFF and arbitrary complex zzz, and that its real diagonal is summable with sum 111. For C⊆U={0,…,n−1}C\subseteq U=\{0,\ldots,n-1\}C⊆U={0,…,n−1}, let RC(x,y)=∑z∈NCcρ(x⊕Cz,y⊕Cz)R_C(x,y)=\sum_{z\in\mathbb N^{C^c}}\rho(x\oplus_C z,y\oplus_C z)RC​(x,y)=∑z∈NCc​ρ(x⊕C​z,y⊕C​z), with configurations joined according to CCC and its complement. Define H(K)H(K)H(K) as the infimum in [0,∞][0,\infty][0,∞] of ∑kmax⁡{−wklog⁡wk,0}\sum_k\max\{-w_k\log w_k,0\}∑k​max{−wk​logwk​,0} over representations K(i,j)=∑kwkuk(i)uk(j)‾K(i,j)=\sum_k w_k u_k(i)\overline{u_k(j)}K(i,j)=∑k​wk​uk​(i)uk​(j)​, with nonnegative summable weights of sum 111 and square-summable vectors that are unit and pairwise orthogonal at distinct positive-weight indices; the empty infimum is +∞+\infty+∞. Assume H(RC)≠+∞H(R_C)\ne+\inftyH(RC​)=+∞ for every CCC, including the empty set, and put S(C)=H(RC).toRealS(C)=H(R_C).\mathrm{toReal}S(C)=H(RC​).toReal. Let ttt be any binary tree labelled by UUU, with each leaf valid and each internal node having valid children with disjoint leaf-label sets, and assume its root label set is all of UUU. Define J(leaf⁡(i))=0J(\operatorname{leaf}(i))=0J(leaf(i))=0 and J(split⁡(l,r))=S(Al)+S(Ar)−S(Al∪Ar)+J(l)+J(r)J(\operatorname{split}(l,r))=S(A_l)+S(A_r)-S(A_l\cup A_r)+J(l)+J(r)J(split(l,r))=S(Al​)+S(Ar​)−S(Al​∪Ar​)+J(l)+J(r), where Al,ArA_l,A_rAl​,Ar​ are the children's label sets. Then

∑i∈US({i})−S(U)=J(t).\sum_{i\in U}S(\{i\})-S(U)=J(t).i∈U∑​S({i})−S(U)=J(t).
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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