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LeanPool.HighContrastHomogenization.Support.Sobolev.CubeEmbedding.FoldExtensionFiniteP.Basic

Coarse-graining support: Support.Sobolev.CubeEmbedding.FoldExtensionFiniteP #

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

Finite-p even-fold extension on an axis box #

The W^{1,p} companion to foldExtension. Smooth convex-domain approximants are cut off outside the tripled box, transported by the fold, and closed using finite-exponent Hölder pairings against compactly supported test functions.

theorem HCPolySupport.tendsto_eLpNorm_grad_convexApproxSmoothW1p {d : ℕ} {U : Set (Vec d)} (hU : IsOpenBoundedConvexDomain U) (p : FiniteLpExponent) (u : W1pFunction U p.exponent) {x0 : Vec d} {r : ℝ} (hball : Metric.closedBall x0 r ⊆ U) (hr : 0 < r) (i : Fin d) :
theorem HCPolySupport.HasWeakGradientOn.of_tendsto_eLpNorm_finiteLp {d : ℕ} {U : Set (Vec d)} (p : FiniteLpExponent) {u : Vec d → ℝ} {Du : Vec d → Vec d} {u_n : ℕ → Vec d → ℝ} {Du_n : ℕ → Vec d → Vec d} (hu : MeasureTheory.MemLp u p.exponent (MeasureTheory.volume.restrict U)) (hDu : GradMemLpOn U p.exponent Du) (hu_n : ∀ (n : ℕ), MeasureTheory.MemLp (u_n n) p.exponent (MeasureTheory.volume.restrict U)) (hDu_n : ∀ (n : ℕ), GradMemLpOn U p.exponent (Du_n n)) (hweak : ∀ (n : ℕ), HasWeakGradientOn U (u_n n) (Du_n n)) (htend_u : Filter.Tendsto (fun (n : ℕ) => MeasureTheory.eLpNorm (fun (x : Vec d) => u_n n x - u x) p.exponent (MeasureTheory.volume.restrict U)) Filter.atTop (nhds 0)) (htend_Du : ∀ (i : Fin d), Filter.Tendsto (fun (n : ℕ) => MeasureTheory.eLpNorm (fun (x : Vec d) => Du_n n x i - Du x i) p.exponent (MeasureTheory.volume.restrict U)) Filter.atTop (nhds 0)) :
structure HCPolySupport.FoldExtensionFiniteP {d : ℕ} (lo hi : Vec d) (p : FiniteLpExponent) (u : W1pFunction (Box lo hi) p.exponent) :

Data of the finite-p even-fold extension.

Instances For