OAI/NumberTheory/TwoPoint/Bounds/RoughShiftAverage.lean

GitHub source file

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A finite rough-shift correlation inequality

The three terms are the explicit translation error, the low-frequency Cauchy--Schwarz term, and the high-frequency fourth-moment term. Sieve estimates and MRT scale estimates enter only through their numerical bounds.

  1. def OAI.TwoPointCorrelations.roughShiftProfile line 19
  2. def OAI.TwoPointCorrelations.roughShiftAverage line 22
  3. lemma OAI.TwoPointCorrelations.norm_roughShiftProfile_le line 25
  4. lemma OAI.TwoPointCorrelations.translated_roughShiftProfile_eq line 33
  5. lemma OAI.TwoPointCorrelations.rough_window_energy_sum_bound line 51
  6. theorem OAI.TwoPointCorrelations.rough_convolution_sum_bound line 69

    Source documentation

    All Fourier ingredients are now attached to the concrete two windows.

    theorem rough_convolution_sum_bound (f g : ℕ → ℂ) (hf : OneBounded f)
        (hg : OneBounded g) (Z : Finset ℕ) (D h Y : ℕ)
        (ε U V K : ℝ) (hε : 0 < ε) (hU : 0 ≤ U) (hK : 0 ≤ K)
        (hB : ∀ θ, ‖roughFourierPolynomial Z h θ‖ ≤ U)
        (hV : (∫ θ, ‖roughFourierPolynomial Z h θ‖ ^ 4
          ∂AddCircle.haarAddCircle) ≤ V)
        (hF : ∀ θ, (∑ v ∈ range Y, ‖forwardWindowPolynomial f D (v + 1) θ‖) ≤ K) :
        ‖∑ v ∈ range Y, ∫ θ,
          roughFourierPolynomial Z h θ * forwardWindowPolynomial f D (v + 1) θ *
            backwardWindowPolynomial g ((2 * h + 1) * D) (v + 1) θ
              ∂AddCircle.haarAddCircle‖ ≤
          ε * ((Y : ℝ) * (Real.sqrt D * Real.sqrt ((2 * h + 1) * D))) +
    …

    Mentions: OAI.TwoPointCorrelations.OneBounded, OAI.TwoPointCorrelations.roughFourierPolynomial, OAI.TwoPointCorrelations.forwardWindowPolynomial, OAI.TwoPointCorrelations.backwardWindowPolynomial

  7. lemma OAI.TwoPointCorrelations.normalized_translated_roughShift_bound line 99
  8. theorem OAI.TwoPointCorrelations.rough_shift_average_bound line 119

    Source documentation

    The finite correlation bound before inserting the sieve estimates and the size estimates for the published MRT error.

    theorem rough_shift_average_bound (f g : ℕ → ℂ) (hf : OneBounded f)
        (hg : OneBounded g) (Z : Finset ℕ) (D h Y : ℕ) (hD : 0 < D) (hY : 0 < Y)
        (hZ : ∀ z ∈ Z, z ≤ 2 * D)
        (ε U V K : ℝ) (hε : 0 < ε) (hU : 0 ≤ U) (hK : 0 ≤ K)
        (hB : ∀ θ, ‖roughFourierPolynomial Z h θ‖ ≤ U)
        (hV : (∫ θ, ‖roughFourierPolynomial Z h θ‖ ^ 4
          ∂AddCircle.haarAddCircle) ≤ V)
        (hF : ∀ θ, (∑ v ∈ range Y, ‖forwardWindowPolynomial f D (v + 1) θ‖) ≤ K) :
        ‖roughShiftAverage f g Z h Y‖ ≤
          2 * (D : ℝ) / Y * (∑ z ∈ Z, (z : ℝ)⁻¹) +
          (ε * ((Y : ℝ) * (Real.sqrt D * Real.sqrt ((2 * h + 1) * D))) +
            (U * ((2 * h + 1) * D) * K / ε ^ 4) * V) / ((Y : ℝ) * D) := by
    …

    Mentions: OAI.TwoPointCorrelations.OneBounded, OAI.TwoPointCorrelations.roughFourierPolynomial, OAI.TwoPointCorrelations.forwardWindowPolynomial, OAI.TwoPointCorrelations.roughShiftAverage