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LeanPool.HighContrastHomogenization.Support.Deterministic.MultiscaleQuantitiesBasic.Theta

Coarse-graining support: Support.Deterministic.MultiscaleQuantitiesBasic.Theta #

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

Boundary-facing theta statements #

theorem HCPolySupport.thetaRatio_boundary_coefficient_le_of_mem_descendantsAtScale {d : ℕ} {Q R : TriadicCube d} {k : ℤ} (a : CoeffField d) (s t : ℝ) (hs : 0 ≤ s) (ht : 0 ≤ t) (hR : R ∈ descendantsAtScale Q k) (hBsum : Summable fun (n : ℕ) => geometricWeight s 1 n * (maxDescendantBBlockNormAtScale Q (Q.scale - ↑n) a).rpow (1 / 2)) (hSigmaSum : Summable fun (n : ℕ) => geometricWeight t 1 n * (maxDescendantSigmaStarInvNormAtScale Q (Q.scale - ↑n) a).rpow (1 / 2)) :
Real.rpow 3 (-↑(Q.scale - k).toNat) * (ThetaRatio R s t a).rpow (1 / 2) ≤ Real.rpow 3 (-(1 - s - t) * ↑(Q.scale - k).toNat) * (ThetaRatio Q s t a).rpow (1 / 2)
theorem HCPolySupport.weighted_descendant_product_sq_le_thetaRatio {d : ℕ} {Q R : TriadicCube d} {k : ℤ} (a : CoeffField d) (s t : ℝ) (hs : 0 ≤ s) (ht : 0 ≤ t) (hR : R ∈ descendantsAtScale Q k) (hBsum : Summable fun (n : ℕ) => geometricWeight s 1 n * (maxDescendantBBlockNormAtScale Q (Q.scale - ↑n) a).rpow (1 / 2)) (hSigmaSum : Summable fun (n : ℕ) => geometricWeight t 1 n * (maxDescendantSigmaStarInvNormAtScale Q (Q.scale - ↑n) a).rpow (1 / 2)) :