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LeanPool.HighContrastHomogenization.Support.Book.Ch05.Theorems.Section56.SmallContrastAlgebraicDecay.Final

Coarse-graining support: Support.Book.Ch05.Theorems.Section56.SmallContrastAlgebraicDecay.Final #

Imported from the Apache-2.0 CoarseGraining development at commit c7ddd76c08ade64fed1b8d2ca51be14dfee8deb4.

Proposition p.small.contrast.algebraic.decay.homogenization.scale #

theorem HCPolySupport.Book.Ch05.Section56.SmallContrastAlgebraicDecay.smallContrastAlgebraicDecay_homogenizationScale {d : ℕ} [NeZero d] (params : QuantitativeCoarseGrainedEllipticityParams d) :
∃ (α : ℝ) (δ0 : ℝ) (C : ℝ), 0 < α ∧ 0 < δ0 ∧ 0 < C ∧ ∀ {P : Ch04.RestrictionCoeffLaw d} (hP : Ch04.RestrictionLawCarrier P) (hStruct : Ch04.RestrictionStructuralLaw P) (hP4 : QuantitativeCoarseGrainedEllipticity P), hP4.params = params → widetildeThetaAtScale P 0 hP4 - 1 ≤ δ0 → ∀ (m : ℕ) (e : Vec d), vecNormSq e = 1 → have p_e := specialPAtScale hP hStruct (↑m) e; have q_e := specialQAtScale hP hStruct (↑m) e; Ch04.expectedResponseJCubeSet P (originCube d ↑m) p_e q_e ≤ C * Real.rpow 3 (-α * ↑m)

Proposition p.small.contrast.algebraic.decay.homogenization.scale.

The constants are selected from the parameter record before the probability law, so they are independent of the measure.