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LeanPool.HighContrastHomogenization.Support.Sobolev.Foundations.CubeNeumannW22CZ.WeakInteriorDQ.WeakDerivativeTestClosure

Coarse-graining support: #

Support.Sobolev.Foundations.CubeNeumannW22CZ.WeakInteriorDQ.WeakDerivativeTestClosure

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

theorem HCPolySupport.HasWeakPartialDerivOn.integral_mul_deriv_eq_neg_integral_mul_of_eLpNorm_approx {d : ℕ} {U : Set (Vec d)} {i : Fin d} {u gi ψ Dψ : Vec d → ℝ} (huweak : HasWeakPartialDerivOn U i u gi) (hu : MemScalarL2 U u) (hgi : MemScalarL2 U gi) (hψ : MemScalarL2 U ψ) (hDψ : MemScalarL2 U Dψ) (ψn : ℕ → Vec d → ℝ) (hψn_smooth : ∀ (n : ℕ), ContDiff ℝ (↑⊤) (ψn n)) (hψn_compact : ∀ (n : ℕ), HasCompactSupport (ψn n)) (hψn_sub : ∀ (n : ℕ), tsupport (ψn n) ⊆ U) (hψn_mem : ∀ (n : ℕ), MemScalarL2 U (ψn n)) (hDψn_mem : ∀ (n : ℕ), MemScalarL2 U fun (x : Vec d) => euclideanCoordDeriv i (ψn n) x) (hψn_to_ψ : Filter.Tendsto (fun (n : ℕ) => MeasureTheory.eLpNorm (fun (x : Vec d) => ψn n x - ψ x) 2 (volumeMeasureOn U)) Filter.atTop (nhds 0)) (hDψn_to_Dψ : Filter.Tendsto (fun (n : ℕ) => MeasureTheory.eLpNorm (fun (x : Vec d) => euclideanCoordDeriv i (ψn n) x - Dψ x) 2 (volumeMeasureOn U)) Filter.atTop (nhds 0)) :
∫ (x : Vec d) in U, u x * Dψ x = -∫ (x : Vec d) in U, gi x * ψ x

Extend the weak-partial-derivative identity from admissible smooth compact tests to any test reached as an L² limit together with its coordinate derivative.

This is the closure step needed for cube boundary tests: the geometric cutoff argument supplies the approximating sequence ψn; this lemma performs the functional-analytic handoff to the weak derivative identity.