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LeanPool.HighContrastHomogenization.Provider.Quenched.SmallContrastTerminalComparability

High-contrast homogenization: Provider.Quenched.SmallContrastTerminalComparability #

Imported from the Apache-2.0 HighContrastHomogenization development at commit 7a13dbcd8d6609264a713373f5c69ceeac870472.

The terminal reference comparability #

The deterministic comparability consumed by the caps: the Dagger reference is dominated by the terminal adapted mean with the factor ฮบ_๐„ ยท C(K) ยท boundaryConst ยท 3^{gG}. The chain is window-free: the annealed envelope bounds the terminal mean by the scaled reference, the sharp reverses the order, the annealed block dominates its own sharp, and the reference is dominated by ฮบ_๐„ times its sharp. This is the formalizable content of the printed ๐„-preliminaries at the terminal scale.

The zero-aligned cell is the adapted cell itself.

theorem HCPolySupport.HighContrast.Quenched.terminal_reference_comparability {d : โ„•} [NeZero d] (hd : 2 โ‰ค d) {g : โ„} (hg : g โˆˆ Set.Ico 0 1) {P : MeasureTheory.Measure (CoeffSpace d)} [MeasureTheory.IsProbabilityMeasure P] {E : BlockMat d} {ฮจ : โ„ โ†’ โ„} {K : โ„} {S : CoeffSpace d โ†’ โ„} (hdag : CoarseEllipticityDagger P g E ฮจ K S) {l : โ„ค} (hl : โ†‘(kZero d) โ‰ค l) {Cd : โ„} (hCd : max 1 (12 * โ†‘d * โˆšโ†‘d) โ‰ค Cd) {n : Mat d} (hn : Matrix.PosDef n) {sK : โ„ค} (hsK : growthBar K โ‰ค 3 ^ sK) (t : โ„ค) {G : โ„•} (hDelta : 0 โ‰ค t + โ†‘G - 1 - sK) (hsub : adaptedCell (roundedGrid l n) t โІ centeredCube d (t + โ†‘G)) (hint : HasFiniteAdaptedMean P (roundedGrid l n) t) :
1 โ‰ค kappaRef E * (sourceMomentOne K * boundaryConst Cd g n * 3 ^ (g * (โ†‘(t + โ†‘G) - โ†‘t))) โˆง โˆ€ (X : BlockVec d), blockVecDot X (blockMatVecMul E X) โ‰ค kappaRef E * (sourceMomentOne K * boundaryConst Cd g n * 3 ^ (g * (โ†‘(t + โ†‘G) - โ†‘t))) * blockVecDot X (blockMatVecMul (adaptedMean P (roundedGrid l n) t) X)

The terminal reference comparability. The reference quadratic form is dominated by ฮบ_๐„ ยท C(K) ยท boundaryConst ยท 3^{gG} times the terminal mean's quadratic form.