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LeanPool.Superdiffusion.Algsuperdiff.Section3.Provider.Localization.DeepLegSummability

DeepLegSummability #

Ported from scottnarmstrong/Superdiffusion at 7f20476385d4af418f110303085ad0740c9eba46. Module imports, support namespace and local option directives adapted for Lean Pool.

The shell-index monotonicity of the cutoff's ellipticity witness #

The cutoff local control is monotone in the shell index. Lowering the shell index deletes the leading terms of a nonnegative convergent series.

This is not Provider.Diffusivity.ApproximateRecurrence.Closure.cutoffLocalControl_mono, which is monotonicity in the scale ell at a fixed shell index and is proved termwise from localCubeControl_mono; this one moves the other argument and is a tail-truncation statement. The name is deliberately different so that a consumer may open both.

The cutoff's entry envelope on a cube is monotone in the shell index.

The cutoff's upper ellipticity constant is monotone in the shell index. This is the moving comparator's only j-dependence inside Ch02.normalizedBlockResponseUniformBound; the lower constant is the constant M.nu.

The isotropic normalizer's row bound #

The square-root normalizer of the isotropic comparator. At a0 = sigma * 1 the Chapter 2 normalizer is the diagonal gauge diag(sigma^{1/2}, sigma^{-1/2}), whose row bound is d (sigma + sigma^{-1}).

The plateau ceiling, uniform below a scale #

The annealed plateau, read uniformly below a scale. The upper plateau bound of Provider.Base.annealedPlateau is increasing in the scale, so its value at m bounds sigmaBar_k for every k <= m.

The ceiling is spelled with the constant Provider.Base.cutoffPlateauAmplitude, whose body is definitionally the plateau amplitude annealedPlateau displays: no statement in this module spells that product by hand. The two side conditions after the unfold (hpow, hcoef) are what the monotonicity step needs and are not a re-spelling of the ceiling.

The uniform bound at the moving comparator #

The uniform descendant bound at the moving comparator. CoarseGraining's Ch02.normalizedBlockResponseUniformBound at the cutoff family of shell index k and the isotropic comparator sigmaBar_k is bounded by an explicit expression in any upper bound L for the cutoff's cube ellipticity constant and any upper bound T for sigmaBar_k + sigmaBar_k⁻¹.

** The uniform-in-j pathwise leg bound at the moving comparator.** For every sample and every scale m and gap h, one constant bounds both breakdown legs of every descendant of □_m, at the MOVING comparator (a_{m-j-h}, sigmaBar_{m-j-h}), uniformly in the depth j.

It is entirely deterministic: CoarseGraining's uniform descendant bound is universally quantified in (a, a0), and the j-dependence of its explicit value is controlled by the shell monotonicity of the cutoff's ellipticity constant and by the annealed plateau.

(b) The two deep summability discharges #

The deep a-leg scale series is summable, pathwise. This is the first Summable premise of localization_mathcalE_estimate_ae, at its exact carriers.

The deep a^t-leg scale series is summable, pathwise. This is the second Summable premise of localization_mathcalE_estimate_ae, at its exact carriers.

(c) The endpoint, unconditional #

theorem Algsuperdiff.Section3.Provider.Localization.localization_mathcalE_estimate_ae_unconditional (d : ℕ) [NeZero d] :
∃ (Cs : ℝ) (Cg : ℝ) (Ci : ℝ), 0 < Cs ∧ 0 < Cg ∧ 0 < Ci ∧ ∀ (M : ABKModel d) (m0 : ℤ) (E : { E : ℝ // 1 ≤ E }), mStarStar M < m0 → Frozen.Section3.inductionState M (m0 - 1) E → Cs * (Disorder.cstar M)⁻¹ ≤ ↑E → Cg * (Disorder.cstar M)⁻¹ ≤ ↑E → Ci * (Disorder.cstar M)⁻¹ ≤ ↑E → M.gamma ≤ (↑E)⁻¹ ^ 10 → ∀ (Ccg : ℝ), 0 < Ccg → ∀ m ≤ m0, ∀ (hgap : ℕ), M.gamma * ↑hgap ≤ 1 → ∀ (s : ℝ) (hs8 : 8 * M.gamma ≤ s), s ≤ 1 → ∀ᵐ (omega : Cutoff.CutoffSample d) ∂↑(Cutoff.cutoffSampleLaw M), Observable.cutoffHomogenizationError M m ⟨s, ⋯⟩ omega ^ 2 ≤ 12 * (HCPolySupport.Book.Ch02.geometricDiscount s 2 * gridScaleSeries m s fun (j : ℕ) (R : HCPolySupport.TriadicCube d) => breakdownLegA R (Cutoff.coefficientCutoffTriadicCoeffFamily M (m - ↑j - ↑hgap) omega) (Observable.isotropicComparatorMatrix (Annealed.sigmaBar M (m - ↑j - ↑hgap)))) + 12 * (HCPolySupport.Book.Ch02.geometricDiscount s 2 * gridScaleSeries m s fun (j : ℕ) (R : HCPolySupport.TriadicCube d) => breakdownLegB R (Cutoff.coefficientCutoffTriadicCoeffFamily M (m - ↑j - ↑hgap) omega) (Observable.isotropicComparatorMatrix (Annealed.sigmaBar M (m - ↑j - ↑hgap)))) + 4 * (8 * (324 * BadEvents.responseSensitivityConst d * (16 * Ccg + 8 * Ccg ^ 2) * ((Disorder.cstar M)⁻¹ * M.gamma))) * MultiscaleEstimate.waveSizesTotalW2 M m hgap s ↑omega + (8 * ⨆ (j : ℕ), Real.rpow 3 (-(s / 4) * 2 * ↑j) * badGridAverage M Ccg m hgap s j omega) * HCPolySupport.Book.Ch02.HomogenizationErrorOnCube (HCPolySupport.originCube d m) (s / 4) HCPolySupport.Book.Ch02.MultiscaleExponent.infinity (HCPolySupport.Book.Ch02.MultiscaleExponent.finite 2) (Cutoff.coefficientCutoffTriadicCoeffFamily M m omega) (Observable.isotropicComparatorMatrix (Annealed.sigmaBar M m)) ^ 2 + 1024 * (Cs * (48 * Ccg)) * M.gamma ^ 2 * (↑hgap ^ 2 + (s ^ 2)⁻¹ + ↑E ^ 4 * |Real.log M.gamma| ^ 4)

(c) l.localization.mathcalE, with both deep Summable premises discharged. This is localization_mathcalE_estimate_ae with its TWO conditional-A premises removed; every hypothesis that remains is a source binder of the printed lemma or the parametric good-event constant Ccg. The five-term display, the null-set placement and every constant are character identical to the proved endpoint's; nothing here re-proves the analysis.