Fully quantum reverse Shannon with feedback and a relative input promise
OpenQAlgorithms.Papers.Independent.Intakethird100.P64.fullyQuantumReverseShannonLet be finite nonzero complex registers. Alice controls and retains ; Bob receives . Let be an isometry, let be a density matrix on , and let be a unit purification of . Set . Entropies are in bits and .
Then the following asymptotic resource inequality holds:
For every error and rate slack , there are and a threshold such that every , admits local physical encoding and decoding operations. They consume at most forward qubits and normalized Bell pairs. These operations are chosen before any test input. For every finite reference and joint density whose marginal is within full trace norm of , the complete output on is within full trace norm of . No nonlocal assistance is left uncounted.
This is the simulation arm of reversible feedback-channel decomposition; the source attributes its coherent construction to [9].
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P64
noncomputable section
namespace QAlgorithms.Papers.Independent.Intakethird100.P64
open QAlgorithms
open QAlgorithms.Papers.Independent.Gap48.P20
(Copies redistributionMarginal subsystemEntropy forwardApply)
open QAlgorithms.Papers.Independent.Dependency50.P48 (densityPower)
open scoped Matrix ComplexConjugate
attribute [local instance] Classical.propDecidable Classical.decEq
/-- PDF p.2, (5), attributed there to [9]: fully quantum reverse Shannon.
U is a feedback isometry, rho is a density matrix, phi its normalized purification,
and the two coefficients are computed from (id_R tensor U)phi. Simulation includes
Alice's feedback and every allowed reference correlation, under the near-IID promise. -/
theorem fullyQuantumReverseShannon {R S A B : Type}
[Fintype R] [Fintype S] [Fintype A] [Fintype B]
[Nonempty R] [Nonempty S] [Nonempty A] [Nonempty B]
(U : Matrix (A × B) S ℂ) (hU : Uᴴ * U = 1)
(rho : Matrix S S ℂ) (hrho : IsDensityMatrix rho)
(phi : EuclideanSpace ℂ (R × S)) (hphi : IsState phi)
(hpurification : traceLeft (pureDensity phi) = rho) :
RelativeSimulationAchievable U rho
(mutualRB (feedbackOutputVector U phi) / 2) (mutualAB (feedbackOutputVector U phi) / 2) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P64
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
Let be nonempty types equipped with finite enumerations, let satisfy , let be positive semidefinite with , and let satisfy and . Put , form its outer-product matrix, and let denote the entropy of its reduction to registers , namely with applied by continuous functional calculus. Define
The theorem asserts that for every , there exist and such that for every with , there are natural numbers and matrices
satisfying , , , and , where and . Define
Then, for every positive integer and every positive semidefinite trace-one matrix on ,
Here , partial traces sum diagonal blocks, tensoring a matrix function with an identity means applying it separately to each reference-index block, and . The natural code parameters may be zero; the asserted block lengths are positive.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.