One-ebit cost and asymptotic PPT relative entropy of rho_v
OpenQAlgorithms.Papers.Independent.Intakethird100.P90.rhoV_cost_relative_entropyAll systems are finite-dimensional complex Hilbert spaces with fixed orthonormal product bases and positive local dimensions. A state is a positive semidefinite operator of trace one. All logarithms are base two and all operational rates are measured in standard Bell pairs (ebits) per input copy, with deterministic operations and error tending to zero. Write for distillable entanglement and entanglement cost under completely PPT-preserving CPTP operations; an explicit LOCC subscript denotes unrestricted two-way local operations and classical communication.
Put , , and . Let denote the positive-block regularization of relative entropy to normalized PPT states. Then
Both values are exactly one ebit per copy; this statement does not replace PPT operations by LOCC.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P90
noncomputable section
open scoped Matrix ComplexConjugate ComplexOrder
namespace QAlgorithms.Papers.Independent.Intakethird100.P90
attribute [local instance] Classical.propDecidable Classical.decEq
open QAlgorithms
open QAlgorithms.Papers.Independent.Dependency50.P36
(relativeEntropy rains target canonicalMatrix allowed pptDistillable)
open QAlgorithms.Papers.Independent.Information100.P04 (gamma copies IsPPT)
open QAlgorithms.Papers.Independent.Next46.P42 (regroupProduct)
open QAlgorithms.Papers.Independent.Information100.P06 (supportProjection)
open QAlgorithms.Papers.Independent.Information100.P21 (FiniteLOCC)
open QAlgorithms.Papers.Independent.Gap48.P32 (antisymmetricQutrit)
/-- arXiv:1606.09421v3, PDF pp.3--4, Proposition 2: both printed equalities. -/
theorem rhoV_cost_relative_entropy :
asymptoticEntanglementCost false rhoV = 1 ∧ regularizedPptRelativeEntropy rhoV = 1 := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P90
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
Let for , where the kets are coordinate basis vectors on , and set , with . The assertion is
as equalities in the extended real line. Here , , and a channel is a finite Kraus sum satisfying . A PPT channel is a channel whose partial-transpose conjugate is also a channel. The quantity is the infimum of real such that, for every , all sufficiently large positive natural admit , including , and a PPT channel with and . The matrix has entry when both row and column have equal party indices, and otherwise; tensor-power entries are products of the single-copy entries, with party registers grouped and then relabelled by the fixed finite-index bijections indicated by the hat. The other quantity is
where when , and otherwise, with matrix logarithms interpreted by spectral functional calculus and .
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.