Section 3.5: computed projective representation of a POVM
OpenQAlgorithms.Papers.Independent.Intakethird100.P51.naimarkLet be a finite POVM: and . Define
Then , the sum to the identity and satisfy , and for every density matrix ,
This is the computed projective dilation of the specified POVM; effects may be singular.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P51
noncomputable section
open scoped Matrix ComplexOrder ComplexConjugate Matrix.Norms.L2Operator
open MeasureTheory
namespace QAlgorithms.Papers.Independent.Intakethird100.P51
attribute [local instance] Classical.propDecidable Classical.decEq
-- Exact interfaces from the frozen accepted library; no local redeclarations.
open QAlgorithms.Papers.Independent.Information100.P63 (Mat)
open QAlgorithms.Papers.Independent.Information100.P56 (entropy holevo IsLaw)
open QAlgorithms.Papers.Independent.Information100.P27 (average)
open QAlgorithms.Papers.Independent.Dependency50.P21 (relativeEntropy marginalAB channelAdjoint)
open QAlgorithms.Papers.Independent.Dependency50.P35 (marginalAC)
open QAlgorithms.Papers.Independent.Gap48.P19 (shannonNats)
open QAlgorithms.Papers.Independent.Gap48.P33 (measurementInformation)
section Statements
variable {A B C D J K O : Type}
variable [Fintype A] [Fintype B] [Fintype C] [Fintype D] [Fintype J] [Fintype K] [Fintype O]
variable [DecidableEq A] [DecidableEq B] [DecidableEq C] [DecidableEq D]
variable [DecidableEq J] [DecidableEq K] [DecidableEq O]
/-- Section 3.5, PDF p.11: the computed Naimark representation, with unchanged
outcome probabilities and genuinely projective enlarged effects. -/
theorem naimark [Nonempty A] [Nonempty O] (E : O → Mat A) (hE : IsPOVM E) :
let V := krausV (fun b => cfc Real.sqrt (E b))
Vᴴ * V = 1 ∧ IsPOVM (coordinatePVM (A := A) (O := O)) ∧
(∀ b c : O, coordinatePVM (A := A) b * coordinatePVM c =
if b = c then coordinatePVM b else 0) ∧
(∀ rho : Mat A, IsDensityMatrix rho → ∀ b,
effectProb (coordinatePVM b) (V * rho * Vᴴ) = effectProb (E b) rho) := by sorry
end Statements
end QAlgorithms.Papers.Independent.Intakethird100.P51
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For finite nonempty index types with decidable equality, let , , be positive semidefinite complex matrices on satisfying . Define the matrix by , where the square root is obtained by continuous functional calculus, and define , where has its sole nonzero entry at . Then ; each is positive semidefinite and ; for every , if and otherwise; and, for every positive semidefinite matrix on of trace and every ,
Zero effects, singular density matrices, and singleton index types are included.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.