Irreducible product-source rate-sum converse
OpenQAlgorithms.Papers.Independent.Intakethird100.P11.irreducibleProduct_converseLet be a finite label set, with , and let , be unit vectors in finite-dimensional complex Hilbert spaces. Set . Assume that its positive-probability support admits no partition into two nonempty mutually orthogonal classes. Write for the base-two von Neumann entropy of its average density operator, and for its marginal ensembles. Every achievable real pair satisfies
An achievable pair uses independent blind local CPTP encoders, one noiseless quantum link from each sender, and a joint CPTP decoder, without supplied shared entanglement or side messages. For every , every sufficiently large positive integer blocklength admits positive compressed dimensions with , , and ensemble-average pure-input overlap with the reconstructed density operator at least . Draws are independent and identically distributed; this is squared fidelity, without a purifying reference.
This is a necessary sum-rate constraint for globally irreducible product sources; it does not by itself characterize a complete rate region.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P11
noncomputable section
namespace QAlgorithms.Papers.Independent.Intakethird100.P11
open MeasureTheory Filter
open scoped BigOperators ComplexConjugate Matrix
open QAlgorithms.Papers.Independent.Dependency50.P19 (both)
open QAlgorithms.Papers.Independent.Information100.P27 (shannon)
attribute [local instance] Classical.propDecidable Classical.decEq
/-- PDF p.6, Theorem III.3, (10): the rate-sum converse for globally irreducible
product sources. Irreducibility of the separate marginal ensembles is insufficient. -/
theorem irreducibleProduct_converse {I A B : Type*}
[Fintype I] [Fintype A] [Fintype B] [DecidableEq A] [DecidableEq B]
(p : I → ℝ) (hp : ∀ i, 0 ≤ p i) (htotal : ∑ i, p i = 1)
(phi : I → EuclideanSpace ℂ A) (psi : I → EuclideanSpace ℂ B)
(hphi : ∀ i, IsState (phi i)) (hpsi : ∀ i, IsState (psi i))
(hirr : EnsembleIrreducible p (fun i => tensorVec (phi i) (psi i)))
(ra rb : ℝ) (hach : FiniteAchievable p (fun i => tensorVec (phi i) (psi i)) ra rb) :
(vnEntropy (sourceMean p phi) + vnEntropy (sourceMean p psi) +
vnEntropy (sourceMean p (fun i => tensorVec (phi i) (psi i)))) / 2 ≤ ra + rb := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P11
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
Let be finite types, with decidable equality on , let satisfy , and let and have norm for every , including labels of weight zero. Put . Assume that some , and that every subset of labels containing and excluding positive-weight labels has labels inside and outside with and . Let , and assume that for every , all sufficiently large positive lengths admit positive dimensions and separate encoders and a joint decoder, each of the form with finitely many and , such that their composite satisfies
where and . Then
where , with applied by continuous functional calculus. No separate nonnegativity assumptions on are present. Although empty finite types are permitted by the type parameters, the probability and unit-norm hypotheses exclude them here.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.