Local frame-potential inequality and exact gap identity
OpenQAlgorithms.Papers.Independent.Intakethird100.P71.framePotential_gapLet be the prior of any projective experiment on qudits, , and let be its conjugation twirl by normalized local Haar measure. Define and , with independent snapshots. If is the second EF and , then
Thus exactly when these second moments agree, and local invariance of the whole prior law implies zero gap. At zero gap, inversion of the complete twirled measurement channel reconstructs every density matrix without bias from the original posterior. The twirled moment averages jointly over the local unitary and the snapshot. Equality of second moments does not assert equality of the full laws.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P71
noncomputable section
open MeasureTheory
open scoped Matrix ComplexConjugate ENNReal Matrix.Norms.Elementwise
namespace QAlgorithms.Papers.Independent.Intakethird100.P71
attribute [local instance] Classical.propDecidable
local notation "Config" n:max d:max =>
QAlgorithms.Papers.Independent.Information100.P21.Config (P := Fin n) (fun _ => d)
local notation "Op" n:max d:max =>
QAlgorithms.Papers.Independent.Information100.P21.Op (Config n d)
attribute [local instance] QAlgorithms.Papers.Independent.Intakethird100.P71.matrixContinuousENorm
local notation "Unitary" n:max d:max => Matrix.unitaryGroup (Config n d) ℂ
local notation "Local" n:max d:max => Fin n → Matrix.unitaryGroup (Fin d) ℂ
open QAlgorithms.Papers.Independent.Information100.P63 (tensorPower)
/-- PDF p.12 Eqs.(42)–(45): frame-potential inequality, EF value of the
locally twirled limit, and the trace of the square gap identity. The second
moment in the difference averages over BOTH V and the snapshot. Zero gap
ensures exact reconstruction when the twirled channel is complete; it does not
imply invariance of the entire probability law. -/
theorem framePotential_gap {n d : ℕ} (hd : 2 ≤ d) (E : ProjectiveEnsemble n d)
(H : Measure (Local n d)) [IsProbabilityMeasure H] [H.IsMulLeftInvariant] :
framePotential (twirled H (prior E)) ≤ framePotential (prior E) ∧
framePotential (twirled H (prior E)) =
∑ A : Finset (Fin n), ∑ B : Finset (Fin n),
feature (prior E) A * regionalWg n d A B * feature (prior E) B ∧
(frameGap H (prior E) : ℂ) =
((snapshotMoment (prior E) 2 - snapshotMoment (twirled H (prior E)) 2) *
(snapshotMoment (prior E) 2 - snapshotMoment (twirled H (prior E)) 2)).trace ∧
(frameGap H (prior E) = 0 ↔ snapshotMoment (prior E) 2 = snapshotMoment (twirled H (prior E)) 2) ∧
(LocallyScrambled (prior E) → frameGap H (prior E) = 0) ∧
(frameGap H (prior E) = 0 → ∀ hc : Complete (twirled H (prior E)),
∀ rho : Op n d, IsDensityMatrix rho →
(∫ S, snapshotInverse (twirled H (prior E)) hc S ∂posteriorOf (prior E) rho) = rho) := by sorry
end QAlgorithms.Papers.Independent.Intakethird100.P71
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
Let , , , and . Let supply a probability law on global unitary matrices, set , and let be a probability measure on local unitary families invariant under left multiplication. Write , and define
For each site subset , put , where the partial trace sums matching complementary indices, and put . The theorem asserts
where the last equality embeds the real number in and uses the matrix square. It also asserts if and only if , and asserts that invariance for every local implies . Finally, if , then for every assumption that the map
is injective, its complex-linear inverse satisfies
for every positive semidefinite matrix of trace , where uses the original measure . All subset sums include the empty subset, and is allowed.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.