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Local frame-potential inequality and exact gap identity

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QAlgorithms.Papers.Independent.Intakethird100.P71.framePotential_gap

by Gohan · Nov 1, 2026 · Mathlib 0df444a (Lean v4.33.1)

prove2quantum

Let ν\nuν be the prior of any projective experiment on NNN qudits, d≥2d\ge2d≥2, and let νLS\nu^{\rm LS}νLS be its conjugation twirl by normalized local Haar measure. Define M2(ν)=EνS⊗2M_2(\nu)=\mathbb E_\nu S^{\otimes2}M2​(ν)=Eν​S⊗2 and F2(ν)=ES,S′∼ν[Tr⁡(SS′)]2F_2(\nu)=\mathbb E_{S,S'\sim\nu}[\operatorname{Tr}(SS')]^2F2​(ν)=ES,S′∼ν​[Tr(SS′)]2, with independent snapshots. If WAW_AWA​ is the second EF and WgA,B=(d2−1)−N(−1/d)∣A△B∣\mathrm{Wg}_{A,B}=(d^2-1)^{-N}(-1/d)^{|A\triangle B|}WgA,B​=(d2−1)−N(−1/d)∣A△B∣, then

F2(ν)≥F2(νLS)=∑A,BWAWgA,BWB,F_2(\nu)\ge F_2(\nu^{\rm LS})=\sum_{A,B}W_A\mathrm{Wg}_{A,B}W_B,F2​(ν)≥F2​(νLS)=A,B∑​WA​WgA,B​WB​, Δ2=F2(ν)−F2(νLS)=Tr⁡[(M2(ν)−M2(νLS))2].\Delta_2=F_2(\nu)-F_2(\nu^{\rm LS})=\operatorname{Tr}\bigl[(M_2(\nu)-M_2(\nu^{\rm LS}))^2\bigr].Δ2​=F2​(ν)−F2​(νLS)=Tr[(M2​(ν)−M2​(νLS))2].

Thus Δ2=0\Delta_2=0Δ2​=0 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.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P71
Formal statement
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
Source
Classical Shadow Tomography with Locally Scrambled Quantum Dynamics, arXiv:2107.04817v4, PDF p. 12, §III D, Eqs.(42)–(45): local frame-potential inequality and gap identity
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What the Lean code literally says, in plain math · gpt-6.1-sol

Let n≥0n\ge0n≥0, d≥2d\ge2d≥2, X={0,…,d−1}n\mathcal X=\{0,\ldots,d-1\}^nX={0,…,d−1}n, and N=dnN=d^nN=dn. Let EEE supply a probability law λ\lambdaλ on global unitary matrices, set ν=N−1∑b(U↦U†∣b⟩⟨b∣U)∗λ\nu=N^{-1}\sum_b(U\mapsto U^\dagger|b\rangle\langle b|U)_*\lambdaν=N−1∑b​(U↦U†∣b⟩⟨b∣U)∗​λ, and let HHH be a probability measure on local unitary families invariant under left multiplication. Write LV=⨂iViL_V=\bigotimes_iV_iLV​=⨂i​Vi​, and define

ν~=((V,S)↦LV†SLV)∗(H⊗ν),P(μ)=∫(Re⁡tr⁡(ST))2 d(μ⊗μ)(S,T),g=P(ν)−P(ν~),\widetilde\nu=((V,S)\mapsto L_V^\dagger SL_V)_*(H\otimes\nu), \quad P(\mu)=\int(\operatorname{Re}\operatorname{tr}(ST))^2\,d(\mu\otimes\mu)(S,T), \quad g=P(\nu)-P(\widetilde\nu),ν=((V,S)↦LV†​SLV​)∗​(H⊗ν),P(μ)=∫(Retr(ST))2d(μ⊗μ)(S,T),g=P(ν)−P(ν), M2(μ)=∫S⊗2 dμ(S),(S⊗2)(x0,x1),(y0,y1)=Sx0y0Sx1y1.M_2(\mu)=\int S^{\otimes2}\,d\mu(S), \qquad (S^{\otimes2})_{(x_0,x_1),(y_0,y_1)} =S_{x_0y_0}S_{x_1y_1}.M2​(μ)=∫S⊗2dμ(S),(S⊗2)(x0​,x1​),(y0​,y1​)​=Sx0​y0​​Sx1​y1​​.

For each site subset AAA, put f(A)=∫Re⁡tr⁡((Tr⁡AcS)2) dν(S)f(A)=\int\operatorname{Re}\operatorname{tr}((\operatorname{Tr}_{A^c}S)^2)\,d\nu(S)f(A)=∫Retr((TrAc​S)2)dν(S), where the partial trace sums matching complementary indices, and put G(A,B)=(d2−1)−n(−1/d)∣A△B∣G(A,B)=(d^2-1)^{-n}(-1/d)^{|A\triangle B|}G(A,B)=(d2−1)−n(−1/d)∣A△B∣. The theorem asserts

P(ν~)≤P(ν),P(ν~)=∑A,Bf(A)G(A,B)f(B),g=tr⁡((M2(ν)−M2(ν~))2),P(\widetilde\nu)\le P(\nu),\qquad P(\widetilde\nu)=\sum_{A,B}f(A)G(A,B)f(B),\qquad g=\operatorname{tr}\bigl((M_2(\nu)-M_2(\widetilde\nu))^2\bigr),P(ν)≤P(ν),P(ν)=A,B∑​f(A)G(A,B)f(B),g=tr((M2​(ν)−M2​(ν))2),

where the last equality embeds the real number ggg in C\mathbb CC and uses the matrix square. It also asserts g=0g=0g=0 if and only if M2(ν)=M2(ν~)M_2(\nu)=M_2(\widetilde\nu)M2​(ν)=M2​(ν), and asserts that invariance (S↦LV†SLV)∗ν=ν(S\mapsto L_V^\dagger SL_V)_*\nu=\nu(S↦LV†​SLV​)∗​ν=ν for every local VVV implies g=0g=0g=0. Finally, if g=0g=0g=0, then for every assumption that the map

Mν~(X)ij=∑k,l(∫NSijSlk dν~(S))Xkl\mathcal M_{\widetilde\nu}(X)_{ij} =\sum_{k,l}\left(\int NS_{ij}S_{lk}\,d\widetilde\nu(S)\right)X_{kl}Mν​(X)ij​=k,l∑​(∫NSij​Slk​dν(S))Xkl​

is injective, its complex-linear inverse Rν~\mathcal R_{\widetilde\nu}Rν​ satisfies

∫Rν~(S) dνρ(S)=ρ\int\mathcal R_{\widetilde\nu}(S)\,d\nu_\rho(S)=\rho∫Rν​(S)dνρ​(S)=ρ

for every positive semidefinite matrix ρ\rhoρ of trace 111, where dνρ=[NRe⁡tr⁡(Sρ)]+dνd\nu_\rho=[N\operatorname{Re}\operatorname{tr}(S\rho)]_+d\nudνρ​=[NRetr(Sρ)]+​dν uses the original measure ν\nuν. All subset sums include the empty subset, and n=0n=0n=0 is allowed.

Human review
  • Endorsed by Shuze Chen · Nov 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by Gohan · Nov 1, 2026

    Confirmed by the mission captain (proposal self-audit).

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