OAI/NumberTheory/TwoPoint/Bounds/ActualPaddingCuts.lean

GitHub source file

5 declarations, 0 contain sorry, 0 declared as axioms

Loss of padding mass from the actual graph density and degree cutoffs. The second moment is applied before discarding the large bins.

  1. lemma OAI.TwoPointCorrelations.FiniteLaw.weighted_large_bin_cut line 13
  2. theorem OAI.TwoPointCorrelations.ModFiveThetaInput.actual_family_padding_large_bin_cut line 34
  3. lemma OAI.TwoPointCorrelations.actualPaddingDensity_sum_le_one line 71

    Source documentation

    The bin densities form a subprobability distribution even after restricting the available padding divisors.

    lemma actualPaddingDensity_sum_le_one (Q : Finset ℕ)
        (hQ : ∀ p ∈ Q, p.Prime) (D : Finset ℕ)
        (hD : D ⊆ retainedPrimeDivisors Q) (n : ℤ)
        (η c : ℝ) (hη : 0 < η) (bins : Finset ℤ) :
        (∑ j ∈ bins, paddingDensity D actualPaddingCoefficient (actualPaddingBin η c j)
          (actualPaddingVertex Q) n) ≤ 1 := by
    …

    Mentions: OAI.TwoPointCorrelations.retainedPrimeDivisors, OAI.TwoPointCorrelations.paddingDensity, OAI.TwoPointCorrelations.actualPaddingCoefficient, OAI.TwoPointCorrelations.actualPaddingBin, OAI.TwoPointCorrelations.actualPaddingVertex

  4. lemma OAI.TwoPointCorrelations.actualPadding_keep_loss line 103
  5. theorem OAI.TwoPointCorrelations.ModFiveThetaInput.eventually_actual_padding_keep_loss line 133

    Source documentation

    Both literal vertex cutoffs together remove only O(1/K) + L⁻¹⁰⁰ of the normalized, padding-weighted mass, summed over all selected bins.

    theorem ModFiveThetaInput.eventually_actual_padding_keep_loss
        (hP : ModFiveThetaInput) (E : Finset ℕ) :
        ∃ C : ℝ, 0 < C ∧ ∀ᶠ L : ℝ in atTop,
          ∀ (η c K : ℝ) (h J M B : ℕ) (data : ProhibitedPrimeFamily h J M),
          data.Q = paddingPrimeSupply E L →
          ∀ (site : ℤ) (bins : Finset ℤ), 0 < η → η ≤ 1 → 0 < K →
          ∀ (hB : ∀ p ∈ data.P ∪ data.Q, p ≤ B)
            (D : Finset ℕ), D ⊆ retainedPrimeDivisors data.Q →
          (data.residueLaw B hB).average (fun x =>
            (actualPaddingVertex data.Q (data.residueOrigin x + site)) ^ 2 *
              ∑ j ∈ bins, if ¬integerEdgeKeep D actualPaddingCoefficient
                (actualPaddingBin η c j) (actualPaddingVertex data.Q) L K
    …

    Mentions: OAI.TwoPointCorrelations.ModFiveThetaInput, OAI.TwoPointCorrelations.ProhibitedPrimeFamily, OAI.TwoPointCorrelations.paddingPrimeSupply, OAI.TwoPointCorrelations.retainedPrimeDivisors, OAI.TwoPointCorrelations.actualPaddingVertex, OAI.TwoPointCorrelations.integerEdgeKeep, OAI.TwoPointCorrelations.actualPaddingCoefficient, OAI.TwoPointCorrelations.actualPaddingBin