Optimal Werner-state fidelity on the NPT branch and its boundary
OpenQAlgorithms.Papers.Independent.Intakethird100.P43.werner_fidelityAll operators act on a finite bipartite space in a fixed product basis. Write for Bob's partial transpose and , where . A density operator is positive semidefinite with complex trace exactly one. An admissible PPT map is complex-linear, positive and trace preserving, and is positive on every positive operator. A PPT channel is additionally completely positive; complete positivity of the transpose-conjugated map is not required. Fidelity means the overlap .
Let be independent integers and . Let swap the two local factors, , , and
Let be the negative spectral projector of and set . Then is admissible and its isotropic PPT channel attains the maximal fidelity , optimized over all admissible positive PPT maps:
Here is the trace norm. At , the negative projector is zero and . This gives an attained optimum, also attained by a channel.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P43
noncomputable section
open scoped Matrix ComplexConjugate ComplexOrder
namespace QAlgorithms.Papers.Independent.Intakethird100.P43
attribute [local instance] Classical.propDecidable Classical.decEq
open QAlgorithms.Papers.Independent.Information100.P04
(gamma copies bellProjector negativeProjector werner)
open QAlgorithms.Papers.Independent.Information100.P30 (IsPositiveMap)
/-- PDF p.3, (8)–(9): Werner optimality, with independent input and output dimensions.
SOURCE CORRECTION: (8) prints 0<=p<=1, but (9)'s value is valid only for p>=1/2.
We restrict to 1/2<=p<=1, as required by the preceding NPT construction; at p=1/2
P_neg=0 and A=I/m is used directly. At d=m=2,p=0 the printed value is zero,
contradicting the achievable product-state overlap 1/2. The PDF has no extra /m on
Tr[A rho(p)]. Independent moderation of this correction is required. -/
theorem werner_fidelity (d m : ℕ) (hd : 2 ≤ d) (hm : 2 ≤ m)
(p : ℝ) (hp : 1/2 ≤ p) (hpone : p ≤ 1) :
let rho := werner d p
let A := negativeSpaceWitness rho m 2
RainsFeasibleEffect m A ∧ IsPositiveConjugatePPTChannel (isotropicPreparation m A) ∧
effectProb A rho = traceNorm (gamma rho) / (m : ℝ) ∧
effectProb (bellProjector m) (isotropicPreparation m A rho) = traceNorm (gamma rho) / (m : ℝ) ∧
traceNorm (gamma rho) / (m : ℝ) = ((d : ℝ) - 2 + 4*p) / ((m : ℝ)*d) ∧
IsGreatest (positivePPTFidelityValues rho m) (traceNorm (gamma rho) / (m : ℝ)) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P43
end
Read-back
What the Lean code literally says, in plain math · gpt-6.1-sol
For every pair of natural numbers and every real , including both endpoints, let be one if and , and zero otherwise, and set
Define , let be the matrix obtained by functional calculus from the indicator of strictly negative eigenvalues, and set . Let have entry when both row and column pairs have equal components and zero otherwise, and define . Then is Hermitian and , , , and are positive semidefinite. The map is positive, trace preserving, completely positive, and has for every , where complete positivity requires preservation of positivity under blockwise extension by every finite identity map, including auxiliary size zero. Moreover,
This value is the greatest element of the set of numbers as ranges over all complex-linear maps to matrices indexed by that are positive, preserve every matrix’s trace, and satisfy for every : the value belongs to this set and bounds every member above, without any complete-positivity requirement on the maps defining the set.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.