Documentation

LeanPool.HighContrastHomogenization.Support.Deterministic.CoarsePoincareRHS.LocalNoteTerms.Intrinsic

Coarse-graining support: Support.Deterministic.CoarsePoincareRHS.LocalNoteTerms.Intrinsic #

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

theorem HCPolySupport.ZeroTraceDirichletCorrectorData.sq_negativeBesovSeminormTwo_le_descendantMean_add_intrinsicError_two {d : ℕ} {Q : TriadicCube d} {a : CoeffField d} {g : Vec d → Vec d} (ρ : ZeroTraceDirichletCorrectorData Q a g) {u : Vec d → Vec d} (w : AHarmonicFunction a (cubeSet Q)) {lam Lam : ℝ} (s : ℝ) {η : ℝ} (hs : 0 < s) (hη : 0 < η) (hη_lt : η < 1) (hEll : IsEllipticFieldOn lam Lam (cubeSet Q) a) (hu : MemVectorL2 (cubeSet Q) u) (hgrad : CubeAverageGradientEnergyControl Q a (fun (x : Vec d) => w.toH1.grad x) (coefficientEnergyDensity a fun (x : Vec d) => w.toH1.grad x)) (hsum : Summable fun (n : ℕ) => geometricWeight s 2 n * maxDescendantSigmaStarInvNormAtScale Q (Q.scale - ↑n) a) (huw : ∀ x ∈ cubeSet Q, u x = w.toH1.grad x + ρ.toH10.grad x) (hmem : MemVectorL2 (cubeSet Q) g) (hg : MeasureTheory.MemLp g 2 (normalizedCubeMeasure Q)) (hgradρ : MeasureTheory.MemLp (fun (x : Vec d) => ρ.toH10.grad x) 2 (normalizedCubeMeasure Q)) (hBg : 0 ≤ cubeBesovPositiveVectorSeminormTwo Q s fun (x : Vec d) => g x - cubeAverageVec Q g) (huBdd : BddAbove (Set.range fun (N : ℕ) => cubeBesovNegativeVectorPartialSeminormTwo Q s N u)) (hwBdd : BddAbove (Set.range fun (N : ℕ) => cubeBesovNegativeVectorPartialSeminormTwo Q s N fun (x : Vec d) => w.toH1.grad x)) (hgBdd : BddAbove (Set.range fun (N : ℕ) => cubeBesovPositiveVectorPartialSeminormTwo Q s N fun (x : Vec d) => g x - cubeAverageVec Q g)) (hchildBdd : ∀ R ∈ descendantsAtDepth Q 1, BddAbove (Set.range fun (N : ℕ) => cubeBesovNegativeVectorPartialSeminormTwo R s N u)) :