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Fixed-charge correction criterion

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QAlgorithms.Papers.Independent.Intakethird100.P44.fixed_charge_criterion

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

prove2quantum

All Hilbert spaces are finite dimensional and nonzero, and every channel is completely positive and trace preserving on the full matrix algebra. Let P1,…,PrP_1,\ldots,P_rP1​,…,Pr​ be nonzero orthogonal Hermitian sector projectors summing to III, let C=∑iciPiC=\sum_i c_iP_iC=∑i​ci​Pi​ have pairwise distinct real eigenvalues, and put P(X)=∑iPiXPi\mathcal P(X)=\sum_iP_iXP_iP(X)=∑i​Pi​XPi​. Let N(X)=∑nEnXEn†\mathcal N(X)=\sum_nE_nXE_n^\daggerN(X)=∑n​En​XEn†​ have a finite normalized Kraus family and satisfy PNP=PN\mathcal P\mathcal N\mathcal P=\mathcal P\mathcal NPNP=PN. Let WWW be an isometry from a nonzero logical space. Correctability means existence of a CPTP R\mathcal RR with PRP=PR\mathcal P\mathcal R\mathcal P=\mathcal P\mathcal RPRP=PR and RN(WXW†)=P(WXW†)\mathcal R\mathcal N(WXW^\dagger)=\mathcal P(WXW^\dagger)RN(WXW†)=P(WXW†) for every logical matrix XXX. Suppose Pi0W=WP_{i_0}W=WPi0​​W=W for some fixed sector i0i_0i0​. The code is correctable if and only if there is a complex array (cjnm)(c_{jnm})(cjnm​) with

W†En†PjEmW=cjnmW†Wfor all j,n,m.W^\dagger E_n^\dagger P_jE_mW=c_{jnm}W^\dagger W\quad\text{for all }j,n,m.W†En†​Pj​Em​W=cjnm​W†Wfor all j,n,m.

Here W†WW^\dagger WW†W is the logical identity. Fixed charge implies code-projector invariance, so the preceding sufficiency statement applies.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P44
Formal statement
noncomputable section

namespace QAlgorithms.Papers.Independent.Intakethird100.P44

open scoped Matrix ComplexConjugate ComplexOrder

open QAlgorithms.Papers.Independent.Information100.P60 (Mat)

open QAlgorithms.Papers.Independent.Information100.P67 (mapFirst)

open QAlgorithms.Papers.Independent.Claimed50.P48 (operatorTraceDual)

open QAlgorithms.Papers.Independent.Renew46.P43 (purification)

variable {H K L J E F B : Type*}

variable [Fintype H] [DecidableEq H] [Fintype K] [DecidableEq K]

variable [Fintype L] [DecidableEq L] [Fintype J] [DecidableEq J]

variable [Fintype E] [DecidableEq E] [Fintype F] [DecidableEq F]

variable [Fintype B] [DecidableEq B]

/-- PDF p.6, Eq.(22), together with the immediately preceding sufficiency
statement. W†W is the LOGICAL identity, and coefficients are uniform. -/
theorem fixed_charge_criterion [Nonempty H] [Nonempty L] {r : ℕ}
    (s : Sectors H r) (A : J → Mat H) (hA : IsKrausFamily A)
    (hphys : IsPhysicalChannel (sectorProject s) (sectorProject s) (krausApply A))
    (W : Matrix H L ℂ) (hW : Wᴴ * W = 1)
    (i0 : Fin r) (hcharge : s.P i0 * W = W) :
    PhysicallyCorrectable (sectorProject s) (krausApply A) W ↔
      ∃ c : Fin r → J → J → ℂ, ∀ j n m,
        Wᴴ * (A n)ᴴ * s.P j * A m * W = c j n m • (Wᴴ * W) := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P44

end
Source
Approximate recovery with locality and symmetry constraints, arXiv:1806.10324v2, PDF p. 6, §III B, Eq.(22): fixed-charge simplification
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What the Lean code literally says, in plain math · gpt-6.1-sol

Let H,LH,LH,L be nonempty finite index types with decidable equality, JJJ a finite index type, and rrr a natural number. Let PiP_iPi​, i<ri<ri<r, be nonzero Hermitian projections, mutually orthogonal and summing to III, with pairwise distinct real values viv_ivi​, and put P(X)=∑iPiXPi\mathcal P(X)=\sum_iP_iXP_iP(X)=∑i​Pi​XPi​. Let matrices AnA_nAn​, n∈Jn\in Jn∈J, satisfy ∑nAn†An=I\sum_nA_n^\dagger A_n=I∑n​An†​An​=I, put N(X)=∑nAnXAn†\mathcal N(X)=\sum_nA_nXA_n^\daggerN(X)=∑n​An​XAn†​, and assume P(N(P(X)))=P(N(X))\mathcal P(\mathcal N(\mathcal P(X)))=\mathcal P(\mathcal N(X))P(N(P(X)))=P(N(X)) for every XXX. Let WWW be an H×LH\times LH×L matrix satisfying W†W=IW^\dagger W=IW†W=I, and choose an index i0<ri_0<ri0​<r such that Pi0W=WP_{i_0}W=WPi0​​W=W. Then there exists a channel R(Y)=∑aVaYVa†R(Y)=\sum_aV_aYV_a^\daggerR(Y)=∑a​Va​YVa†​, for a finite family satisfying ∑aVa†Va=I\sum_aV_a^\dagger V_a=I∑a​Va†​Va​=I, with P(R(P(Y)))=P(R(Y))\mathcal P(R(\mathcal P(Y)))=\mathcal P(R(Y))P(R(P(Y)))=P(R(Y)) for every YYY and R(N(WXW†))=P(WXW†)R(\mathcal N(WXW^\dagger))=\mathcal P(WXW^\dagger)R(N(WXW†))=P(WXW†) for every X∈Mat⁡(L)X\in\operatorname{Mat}(L)X∈Mat(L), if and only if there exist complex coefficients cjnmc_{jnm}cjnm​ such that

W†An†PjAmW=cjnm(W†W)for every j<r, n,m∈J.W^\dagger A_n^\dagger P_jA_mW=c_{jnm}(W^\dagger W) \quad\text{for every }j<r,\ n,m\in J.W†An†​Pj​Am​W=cjnm​(W†W)for every j<r, n,m∈J.

No positivity or normalization of cjnmc_{jnm}cjnm​ is required. The assumptions exclude r=0r=0r=0 and empty JJJ.

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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