Abstract main result: both low-noise capacities agree with one-shot coherent information to leading orders
OpenQAlgorithms.Papers.Independent.Intakethird100.P50.lowNoise_capacities_leadingAll systems are nonzero finite-dimensional complex Hilbert spaces. A channel is complex-linear, completely positive and trace preserving. Its receiver and full complementary channel are obtained from the same isometric dilation. Write and for the unassisted operational quantum and private capacities, allowing arbitrary collective codes over independent uses with vanishing reliability error and environmental leakage. Write , where the maximum includes every density operator. Entropies and logarithms are in bits, with . The diamond norm has no factor .
Fix the input/output space . There are constants and , uniform over all channels and their dilations, such that and imply
This quantifies the joint leading-order agreement asserted in the abstract using Theorem 12.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P50
noncomputable section
open scoped BigOperators Matrix ComplexConjugate ComplexOrder
open Filter
namespace QAlgorithms.Papers.Independent.Intakethird100.P50
variable {A B E F : Type}
variable [Fintype A] [DecidableEq A] [Fintype B] [DecidableEq B]
variable [Fintype E] [DecidableEq E] [Fintype F] [DecidableEq F]
open QAlgorithms.Papers.Independent.Information100.P67
(IsIsometry receiverChannel complementaryChannel maximumCoherentInformation
dilationPower idealJoint)
open QAlgorithms.Papers.Independent.Information100.P80 (log2)
open QAlgorithms.Papers.Independent.Information100.P69 (diamond choi)
open QAlgorithms.Papers.Independent.Support50.P07 (fullTracePrivateCapacity)
open QAlgorithms.Papers.Independent.Frontier18.P17 (clock)
/-- Abstract, PDF p.1, pinned to Theorem 12, PDF p.12: both operational capacities
agree with unrestricted one-shot coherent information up to O(eps^(3/2) log(1/eps)).
Constants are uniform over channels and dilations for each fixed input dimension. -/
theorem lowNoise_capacities_leading [Nonempty A] :
∃ C : ℝ, 0 ≤ C ∧ ∃ delta : ℝ, 0 < delta ∧ delta ≤ 1 ∧
∀ (E : Type) [Fintype E] [DecidableEq E] [Nonempty E],
∀ V : Matrix (A × E) A ℂ, IsIsometry V →
∀ eps ∈ Set.Ioo 0 delta,
diamond (channelDifference (receiverChannel V) id) ≤ eps →
|dilationQuantumCapacity V - maximumCoherentInformation V| ≤
C * eps ^ (3 / 2 : ℝ) * (-log2 eps) ∧
|fullTracePrivateCapacity V - maximumCoherentInformation V| ≤
C * eps ^ (3 / 2 : ℝ) * (-log2 eps) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P50
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For every finite nonempty type equipped with decidable equality, there exist real constants and such that, for every finite nonempty type equipped with decidable equality, every complex matrix satisfying , and every real , the assumption implies
Here , , and
using spectral functional calculus. For a map with input index type , denotes the real supremum of over all complex matrices on with , where , and amplification applies separately to each reference matrix block. A channel means a map for a finite family with . The number is the real supremum of nonnegative rates admitting, for every natural block length , a positive message dimension , a channel encoding that dimension into , and a channel decoding back into it, such that the overlap of with tends to one, and, for every , eventually ; here . The number is the real supremum of nonnegative rates such that, for every and , some positive ensures that every admits a positive number of density matrices on and positive semidefinite measurement matrices on summing to the identity, with and , where, writing ,
Tensor powers act on tensor products of matrix units by the corresponding tensor products of their images. The constants are chosen before , so the same constants apply to all those choices; and are excluded from the asserted bounds.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.