Proposition 1 (Secret Key Capacity); precise result selected for the p.1 paper seed
OpenQAlgorithms.Papers.Independent.Intakethird100.P76.secret_key_capacityLet be finite nonempty alphabets and let be a normalized discrete memoryless broadcast channel. All entropies and information quantities are in bits. For an input law , information quantities below use exactly the induced law .
Alice draws a uniform finite message , uses a possibly stochastic encoder to excite channel uses, and observes . A public forward message is visible to Bob and Eve. Their keys are and . All design maps are fixed publicly before observations. Message and public alphabets follow the fixed-rate ceiling convention; the key alphabet at rate has exactly labels. A weakly achievable rate has one sequence of such codes with disagreement tending to zero, , and .
Let be bounded and nonnegative, and let be admissible, meaning that a normalized input law of expected cost at most exists. Every operational code obeys almost surely; each single-letter optimization obeys . Excitation and public rates are unrestricted.
The operational forward secret-key capacity equals an attained auxiliary maximum:
Every auxiliary law is constructed as , and the input obeys the expected-cost constraint. The maximum ranges over finite nonempty auxiliary alphabets.
This identifies the operational capacity without defining it by the proposed information formula.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P76
namespace QAlgorithms.Papers.Independent.Intakethird100.P76
noncomputable section
open scoped BigOperators
open Filter Set
attribute [local instance] Classical.propDecidable
-- Exact pinned primitives, inspected at their definitions before reuse.
open QAlgorithms.Papers.Independent.Information100.P56 (IsLaw)
open QAlgorithms.Papers.Independent.Frontier30.P12 (IsStochastic)
variable {S X Y Z : Type} [Fintype S] [Fintype X] [Fintype Y] [Fintype Z]
[Nonempty S] [Nonempty X] [Nonempty Y] [Nonempty Z]
variable {n u w : ℕ}
/-- PDF p.4, Proposition 1, (8), with factorization (10) and attained maximum. -/
theorem secret_key_capacity (W : DMBC S X Y Z) (cost : S → ℝ) (Gamma : ℝ)
(hcost : AdmissibleCost cost Gamma) :
∃ u w : ℕ, 0 < u ∧ 0 < w ∧ ∃ A : Aux S X u w,
CostFeasibleInput cost Gamma A.input ∧
IsGreatest (auxValues W cost Gamma) (auxObjective W A) ∧
senderExcitedCapacity W cost (some Gamma) = (auxObjective W A : EReal) := by sorry
end
end QAlgorithms.Papers.Independent.Intakethird100.P76
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What the Lean code literally says, in plain math · gpt-6.1-sol
For finite types , let supply their nonemptiness and a probability law for each . Let and satisfy , the existence of a real with for every , and the existence of a probability law with . There exist positive natural numbers , a feasible probability law , and stochastic kernels , , for , whose value
is a member of, and at least every member of, the set obtained by allowing all positive finite auxiliary sizes and all such feasible laws and kernels; furthermore, the sender-excited capacity equals , embedded in the extended real numbers. Here , and conditional mutual information means with Shannon entropies in bits. The capacity in this equality is the extended-real supremum of nonnegative real rates with the following property: for every positive block length , there is a code with positive message, public-message, and key counts , a probability law on for each message, maps to the public alphabet and to the key alphabet, and a map to the same key alphabet; there are fixed nonnegative real constants such that , , and ; every with satisfies ; and under the mass function , the disagreement probability tends to zero, tends to zero, and for every , eventually .
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.