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LeanPool.HighContrastHomogenization.Provider.Regularity.FiniteAffineGradientResidual

High-contrast homogenization: Provider.Regularity.FiniteAffineGradientResidual #

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

Finite affine gradient residuals #

This module realizes the difference between a finite cube solution and a finite affine-boundary solution as an actual harmonic solution on every smaller centered cube. It is the bridge from the gradient-excess definition to the finite Caccioppoli estimates.

theorem HCPolySupport.HighContrast.weightedGradNorm_congr_ae {d : ℕ} (b : CoeffField d) (V : Set (Vec d)) {F G : Vec d → Vec d} (hFG : F =ᵐ[volumeMeasureOn V] G) :

The weighted gradient norm respects almost-everywhere equality on its integration set.

theorem HCPolySupport.HighContrast.normalizedAffineCandidateError_sub_le_add {d : ℕ} (Q : TriadicCube d) (f g : Vec d → ℝ) (c₁ c₂ : ℝ) (e₁ e₂ : Vec d) (h₁ : MeasureTheory.MemLp (fun (x : Vec d) => f x - (c₁ + vecDot e₁ x)) 2 (normalizedCubeMeasure Q)) (h₂ : MeasureTheory.MemLp (fun (x : Vec d) => g x - (c₂ + vecDot e₂ x)) 2 (normalizedCubeMeasure Q)) :
normalizedAffineCandidateError Q (fun (x : Vec d) => f x - g x) (c₁ - c₂) (e₁ - e₂) ≤ normalizedAffineCandidateError Q f c₁ e₁ + normalizedAffineCandidateError Q g c₂ e₂

Subtracting two fields and their affine candidates costs at most the sum of the two candidate errors.

The harmonic residual u - w_m(e) on the centered cube Q_n.

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    @[simp]

    The residual has the literal value representative u - w_m(e).

    @[simp]

    The residual has the literal gradient representative ∇u - ∇w_m(e).

    A gradient-excess candidate is exactly the ENNReal realization of the cube energy of its harmonic residual.

    The canonical excess is bounded by the energy of every harmonic affine residual.

    The residual u - w_m(e) - w_m(p) realized as a harmonic solution on Q_k. Both affine solutions retain the original outer scale m.

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      @[simp]

      The updated residual has the literal value representative u - w_m(e) - w_m(p).

      @[simp]

      The updated residual has gradient ∇u - ∇w_m(e) - ∇w_m(p).

      Updating an outer affine residual is, in weighted gradient norm, the same as updating its outer boundary slope by addition.

      Every updated outer residual gives a candidate upper bound for the original solution's gradient excess.

      A pointwise contraction for every affine residual descends to the canonical infimum without assuming that the infimum is attained.