Corollary 1: evaluation along every successive binary partition
OpenQAlgorithms.Papers.Independent.Intakethird100.P63.corollary1_binaryEvaluationAll 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 . 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 and let be an -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 are the two child clusters of internal node , define using the actual marginals. Then
The result evaluates total correlation using arbitrary successive binary choices, including the final split into two singletons.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P63
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
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What the Lean code literally says, in plain math · gpt-6.1-sol
For every natural number and complex kernel on , assume that it admits an entrywise expansion with square-summable vectors and summable products , that every finite quadratic form is real and nonnegative for arbitrary finite and arbitrary complex , and that its real diagonal is summable with sum . For , let , with configurations joined according to and its complement. Define as the infimum in of over representations , with nonnegative summable weights of sum and square-summable vectors that are unit and pairwise orthogonal at distinct positive-weight indices; the empty infimum is . Assume for every , including the empty set, and put . Let be any binary tree labelled by , 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 . Define and , where are the children's label sets. Then
Confirmed by the mission captain (proposal self-audit).
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