Synthesized complementary information uncertainty
OpenQAlgorithms.Papers.Independent.Intakethird100.P23.synthesized_information_uncertaintyLet be an isometry, so , defining a memoryless channel to Bob and its fixed complementary channel to Eve. All binary inputs are uniform and entropies are in bits. At recursion depth , let and apply the coherent Arikan encoder , where . Amplitude synthesis retains previous bits and averages future bits; phase synthesis retains future bits and averages previous bits, with Bob's coherent copy register retained. Write for the root fidelity of a binary channel .
For every recursion depth and position , let be Bob's synthesized phase channel and Eve's synthesized amplitude channel, both constructed from this same and encoder. Then
Both informations are symmetric Holevo informations. This complementarity bounds simultaneous phase information at Bob and amplitude information at Eve.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P23
namespace QAlgorithms.Papers.Independent.Intakethird100.P23
open scoped BigOperators ComplexConjugate Matrix
open Filter
open QAlgorithms (Qubits)
open QAlgorithms.Papers.Independent.Information100.P67 (IsDegradable)
attribute [local instance] Classical.propDecidable
/-- Synthesized complementary information uncertainty, Eq.(11), PDF p.8.
Neither degradability nor an uncertainty relation is a hypothesis. -/
theorem synthesized_information_uncertainty {b e : ℕ}
(U : Matrix (Fin b × Fin e) Bool ℂ) (hU : Uᴴ * U = 1)
(n : ℕ) (i : Fin (2 ^ n)) :
symmetricInformation (phaseSplit U n i) +
symmetricInformation (environmentSplit U n i) ≤ 1 := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P23
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What the Lean code literally says, in plain math · gpt-6.1-sol
For all natural numbers , every complex matrix with rows indexed by and Boolean columns satisfying , every natural number , including zero, and every index , define the following matrices, identifying bits with . Let
and put and . Let retain the bits with and set the other bits to zero, and let retain the bits with and set the others to zero. For , define
For a square matrix , write , with the scalar function applied through real continuous functional calculus. Then
There is no restriction on or any degradation assumption in this statement. If or , the isometry hypothesis is impossible.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.