Remark 2 / Eq.(27): input independence at full rank
OpenQAlgorithms.Papers.Independent.Intakethird100.P65.fullRank_input_independenceAll systems have finite positive dimension and fixed computational bases. Matrix order is Loewner order and logarithms are base two.
Let be CPTP, with a reference copy of . Let be a unit vector whose input marginal is positive definite. With the normalized maximally entangled state,
The left side is defined using . Thus every full-rank purified input gives the same channel max-information. The claim is not extended to rank-deficient input marginals.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P65
noncomputable section
open Filter QAlgorithms
open scoped BigOperators Matrix ComplexConjugate ComplexOrder Topology
namespace QAlgorithms.Papers.Independent.Intakethird100.P65
attribute [local instance] Classical.propDecidable Classical.decEq
open QAlgorithms.Papers.Independent.Dependency50.P09 (transposeBob)
open QAlgorithms.Papers.Independent.Dependency50.P35 (maxRelative)
open QAlgorithms.Papers.Independent.Independent2.P01 (dampingKraus damping)
open QAlgorithms.Papers.Independent.Gap48.P33 (phaseFlipChannel)
open QAlgorithms.Papers.Independent.Information100.P06 (Below)
open QAlgorithms.Papers.Independent.Information100.P34 (choi)
open QAlgorithms.Papers.Independent.Information100.P62 (Stochastic)
open QAlgorithms.Papers.Independent.Information100.P63 (Mat)
open QAlgorithms.Papers.Independent.Information100.P67 (IsSubnormalized purifiedDistance)
open QAlgorithms.Papers.Independent.Information100.P69 (replacer permute)
open QAlgorithms.Papers.Independent.Information100.P71 (diamond channelPower channelRelative)
open QAlgorithms.Papers.Independent.Support50.P39 (quantumMutualInformation)
variable {A B C D R : Type} [Fintype A] [DecidableEq A]
[Fintype B] [DecidableEq B] [Fintype C] [DecidableEq C]
[Fintype D] [DecidableEq D] [Fintype R] [DecidableEq R]
variable [Nonempty A] [Nonempty B] [Nonempty C] [Nonempty D] [Nonempty R]
/-- Remark 2, Eq.(27), PDF p.8: full rank is essential. The reference is a
copy of the input; any normalized pure purification is allowed. -/
theorem fullRank_input_independence (N : Superop A B) (hN : IsChannel N)
(psi : EuclideanSpace ℂ (A × A)) (hpsi : ‖psi‖ = 1)
(hfull : (traceLeft (pureDensity psi)).PosDef) :
(channelInfo N : EReal) = maxInfo (idTensorSuperop N (pureDensity psi)) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P65
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For finite index types , with decidable equality, let have a finite Kraus representation with . Let have Euclidean norm , and assume the matrix is positive definite. For a vector , write ; for a matrix on , define . Define
Let have entry when both its row and column pairs have equal coordinates, and entry otherwise, and set , where conversion of either extended-real infinity is . Then, as an equality in the extended reals,
Thus the hypothesis concerns the second marginal of , with no specified value for that marginal beyond positive definiteness.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.