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LeanPool.HighContrastHomogenization.Support.Book.Ch05.Theorems.Section54.VarianceBoundGoodScale.RefinedAssembly

Coarse-graining support: #

Support.Book.Ch05.Theorems.Section54.VarianceBoundGoodScale.RefinedAssembly

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

Refined matrix assembly #

This file plugs the refined scalar probe estimates into the finite-dimensional matrix upgrade. The per-scale budget is now expressed in terms of delta and \widetilde\Theta_0.

Refined coordinate-probe scalar variance budget at scale j.

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    Refined plus-pair scalar variance budget at scale j.

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      Refined minus-pair scalar variance budget at scale j.

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        Refined finite-probe matrix variance budget at one scale.

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          theorem HCPolySupport.Book.Ch05.Section54.VarianceBoundGoodScale.fluctuationNormSq_integral_le_refinedMatrixVarianceBound {d : ℕ} [NeZero d] {P : Ch04.RestrictionCoeffLaw d} (hP : Ch04.RestrictionLawCarrier P) (hStruct : Ch04.RestrictionStructuralLaw P) (hP4 : QuantitativeCoarseGrainedEllipticity P) {delta : ℝ} (hdelta_nonneg : 0 ≤ delta) (m j : ℕ) (hj : j ≤ m) (hgood_upper : hP.barSigmaAtScale hStruct 0 ≤ (1 + delta) * hP.barSigmaAtScale hStruct ↑m) (hgood_lower : (hP.barSigmaStarAtScale hStruct 0)⁻¹ ≤ (1 + delta) * (hP.barSigmaStarAtScale hStruct ↑m)⁻¹) :

          Per-scale matrix variance bound using the refined scalar probe estimates.

          The variance sum is bounded by the beta-weighted refined per-scale budgets.