Lemma 2: secrecy plus correctness implies security
OpenQAlgorithms.Papers.Independent.Intakethird100.P22.secrecy_correctness_securityLet be a normalized classical-device law with a common finite nonempty key alphabet and finite nonempty transcript, Eve-output and Eve-input alphabets. The marginal is independent of . The ideal pass law replaces the keys by a uniform perfectly correlated pair, independent of the actual marginal. The intermediate law copies Alice's key into Bob's register and preserves . Let be the abort probability, with an identical normalized abort branch in all three systems. Write for the operational NS distance, and for the pass-weighted secrecy, disagreement and security errors, respectively. Thus , , and .
For any nonnegative error budgets and ,
Separate secrecy and correctness estimates therefore imply security.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P22
noncomputable section
open scoped BigOperators
namespace QAlgorithms.Papers.Independent.Intakethird100.P22
attribute [local instance] Classical.propDecidable Classical.decEq
open QAlgorithms.Papers.Independent.Advance50.P47
(Box IsCorrelation IsNoSignaling HasLocalModel correlationMixture prBox)
open QAlgorithms.Papers.Independent.Information100.P56 (IsLaw)
open QAlgorithms.Papers.Independent.Information100.P27 (shannon)
open QAlgorithms.Papers.Independent.Gap48.P25 (classicalMI)
/-- PDF pp.32–33, Lemma 2, (105)–(112): the comma in (105) means subtraction,
as made explicit in (106),(112). Both error budgets are nonnegative. -/
theorem secrecy_correctness_security {K T E Z : Type}
[Fintype K] [Fintype T] [Fintype E] [Fintype Z]
[Nonempty K] [Nonempty T] [Nonempty E] [Nonempty Z]
(r : KeyOutput K T E Z) (z : Z) (es ec : ℝ) (hes : 0 ≤ es) (hec : 0 ≤ ec)
(hs : cdSecrecyError r ≤ es) (hc : correctnessError r z ≤ ec) :
securityError r ≤ es + ec := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P22
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
For finite nonempty types , let have abort probability and pass and abort arrays , each nonnegative, normalized over at every , and with independent of . Define
For arrays on , define as the supremum of
over positive integers and nonnegative kernels satisfying and . For every and real numbers , if
then
Here for the first distance and for the second.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.