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The regularized exact rate is an asymptotic limit

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QAlgorithms.Papers.Independent.Intakethird100.P83.deterministicRegularization

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

prove2quantum

Let ρ\rhoρ be any normalized finite-dimensional bipartite state. Define E1(ρ)E_1(\rho)E1​(ρ) independently as the supremum of log⁡2k\log_2 klog2​k over real k>0k>0k>0 with FΓ(ρ,k)=1F_\Gamma(\rho,k)=1FΓ​(ρ,k)=1, and define EΓ,0(ρ)E_{\Gamma,0}(\rho)EΓ,0​(ρ) by the supremum of positive-blocklength ratios. Then

lim⁡n→∞, n≥1E1(ρ⊗n)n=EΓ,0(ρ):=sup⁡n≥1E1(ρ⊗n)n.\lim_{n\to\infty,\ n\ge1}\frac{E_1(\rho^{\otimes n})}{n}=E_{\Gamma,0}(\rho):=\sup_{n\ge1}\frac{E_1(\rho^{\otimes n})}{n}.n→∞, n≥1lim​nE1​(ρ⊗n)​=EΓ,0​(ρ):=n≥1sup​nE1​(ρ⊗n)​.

The limit is through positive integers and is finite. This is a regularization statement and does not assert additivity of the one-copy rate.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P83
Formal statement
noncomputable section

open scoped Matrix ComplexConjugate ComplexOrder

open Filter

namespace QAlgorithms.Papers.Independent.Intakethird100.P83

open QAlgorithms.Papers.Independent.Support50.P11 (Loewner)

open QAlgorithms.Papers.Independent.Dependency50.P32 (partialTranspose)

open QAlgorithms.Papers.Independent.Information100.P34 (supportProjector)

variable {A B C D : Type*}

variable [Fintype A] [Fintype B] [Fintype C] [Fintype D]

variable [DecidableEq A] [DecidableEq B] [DecidableEq C] [DecidableEq D]

/-- The asymptotic formula on PDF p.4. The printed subscript "lim_{n>=1}"
is interpreted as n tending to infinity through positive blocklengths;
exactRegularized is independently defined by a supremum, not by this limit. -/
theorem deterministicRegularization [Nonempty A] [Nonempty B]
    (rho : Matrix (A × B) (A × B) ℂ) (hrho : IsDensityMatrix rho) :
    Tendsto (fun n : ℕ => oneCopyExact (regroupedPower rho (n+1)) / (n+1 : ℝ))
      atTop (nhds (exactRegularized rho)) := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P83

end
Source
Improved Semidefinite Programming Upper Bound on Distillable Entanglement, arXiv:1601.07940v4, PDF p. 4, Unnumbered result: regularization equals the asymptotic limit
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What the Lean code literally says, in plain math · gpt-6.1-sol

For any finite nonempty types A,BA,BA,B with decidable equality and any positive semidefinite complex matrix ρ\rhoρ indexed by A×BA\times BA×B with trace 111, define X(a,b),(a′,b′)Γ=X(a,b′),(a′,b)X^\Gamma_{(a,b),(a',b')}=X_{(a,b'),(a',b)}X(a,b),(a′,b′)Γ​=X(a,b′),(a′,b)​, and let FX(k)F_X(k)FX​(k) be the real supremum of Re⁡tr⁡(XQ)\operatorname{Re}\operatorname{tr}(XQ)Retr(XQ) over matrices QQQ satisfying k>0k>0k>0, 0⪯Q⪯I0\preceq Q\preceq I0⪯Q⪯I, and −k−1I⪯QΓ⪯k−1I-k^{-1}I\preceq Q^\Gamma\preceq k^{-1}I−k−1I⪯QΓ⪯k−1I, where ⪯\preceq⪯ means positive semidefinite difference. Let D(X)D(X)D(X) be the real supremum of log⁡2k\log_2 klog2​k over real k>0k>0k>0 for which FX(k)=1F_X(k)=1FX​(k)=1, let X⊗mX^{\otimes m}X⊗m have entries ∏i=0m−1X(ai,bi),(ai′,bi′)\prod_{i=0}^{m-1}X_{(a_i,b_i),(a'_i,b'_i)}∏i=0m−1​X(ai​,bi​),(ai′​,bi′​)​, and define Dreg(ρ)=sup⁡m≥1D(ρ⊗m)/mD_{\mathrm{reg}}(\rho)=\sup_{m\ge1}D(\rho^{\otimes m})/mDreg​(ρ)=supm≥1​D(ρ⊗m)/m, again as a real supremum. Then

lim⁡n→∞D(ρ⊗(n+1))n+1=Dreg(ρ).\lim_{n\to\infty}\frac{D(\rho^{\otimes(n+1)})}{n+1}=D_{\mathrm{reg}}(\rho).n→∞lim​n+1D(ρ⊗(n+1))​=Dreg​(ρ).

Here nnn ranges over all natural numbers, so the sequence begins with the one-copy value and never divides by zero.

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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