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LeanPool.HighContrastHomogenization.Support.Sobolev.Foundations.CoerciveH1

Coarse-graining support: Support.Sobolev.Foundations.CoerciveH1 #

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

Coercive H¹ Scaffolding #

This file packages the first reusable coercive layer above the witness-based H1Function API.

The key objects are:

The future bounded-open-convex Poincare theorem should produce H1CoerciveEstimate U data, and the future Hodge proof should consume that coercive layer rather than the raw witness structures directly.

structure HCPolySupport.H1MeanZeroFunction {d : ℕ} (U : Set (Vec d)) :

Mean-zero H¹(U) functions, represented by a chosen H¹ witness together with the zero-average condition.

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    @[simp]
    theorem HCPolySupport.H1MeanZeroFunction.coe_mk {d : ℕ} {U : Set (Vec d)} (u : H1Function U) (hmean : MeanZeroOn U u.toFun) :
    { toH1Function := u, meanZero := hmean }.toH1Function = u
    @[instance_reducible]
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    The additive homomorphism forgetting the zero-mean condition on an H¹ function.

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      noncomputable def HCPolySupport.H1Function.toScalarL2 {d : ℕ} {U : Set (Vec d)} (u : H1Function U) :
      ↥(ScalarL2 U)

      The scalar L²(U) realization of an H¹ function.

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        noncomputable def HCPolySupport.H1Function.gradToVectorL2 {d : ℕ} {U : Set (Vec d)} (u : H1Function U) :
        ↥(VectorL2 U)

        The vector L²(U; ℝ^d) realization of the weak gradient.

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          noncomputable def HCPolySupport.H1Function.gradToHilbertVectorL2 {d : ℕ} {U : Set (Vec d)} (u : H1Function U) :

          The Hilbert-vector L²(U; ℝ^d) realization of the weak gradient.

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            noncomputable def HCPolySupport.H1Function.gradCoordToScalarL2 {d : ℕ} {U : Set (Vec d)} (u : H1Function U) (i : Fin d) :
            ↥(ScalarL2 U)

            The ith scalar L²(U) realization of the weak gradient.

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              noncomputable def HCPolySupport.H1Function.gradientCoordL2NormSum {d : ℕ} {U : Set (Vec d)} (u : H1Function U) :

              The sum of the scalar L² norms of the gradient coordinates.

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                theorem HCPolySupport.H1Function.coeFn_gradCoordToScalarL2 {d : ℕ} {U : Set (Vec d)} (u : H1Function U) (i : Fin d) :
                ↑↑(u.gradCoordToScalarL2 i) =ᵐ[volumeMeasureOn U] fun (x : Vec d) => u.grad x i

                Normalize an H¹ function to its mean-zero representative by subtracting the average.

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                  Alias for toMeanZero, matching the existing harmonic normalization API.

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                    noncomputable def HCPolySupport.H1Function.gradientHilbertPairing {d : ℕ} {U : Set (Vec d)} {f : Vec d → Vec d} (hf : MemVectorL2 U f) (u : H1Function U) :

                    Pair a vector L² field with the weak gradient in the Hilbert L² ambient space.

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                      theorem HCPolySupport.H1Function.gradientHilbertPairing_eq_integral {d : ℕ} {U : Set (Vec d)} {f : Vec d → Vec d} (hf : MemVectorL2 U f) (u : H1Function U) :
                      gradientHilbertPairing hf u = ∫ (x : Vec d) in U, vecDot (f x) (u.grad x)
                      noncomputable def HCPolySupport.H1MeanZeroFunction.toScalarL2 {d : ℕ} {U : Set (Vec d)} (u : H1MeanZeroFunction U) :
                      ↥(ScalarL2 U)

                      The scalar L²(U) realization of a mean-zero H¹ function.

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                        noncomputable def HCPolySupport.H1MeanZeroFunction.gradToVectorL2 {d : ℕ} {U : Set (Vec d)} (u : H1MeanZeroFunction U) :
                        ↥(VectorL2 U)

                        The vector L²(U; ℝ^d) realization of the weak gradient.

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                          The Hilbert-vector L²(U; ℝ^d) realization of a mean-zero H¹ function's weak gradient.

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                            The scalar L² norm of a mean-zero H¹ function.

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                              The gradient-only L² norm which is the future coercive norm on the mean-zero layer.

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                                The gradient realization as a linear map into the Hilbert L² ambient space.

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                                  The gradient realization as a continuous linear map for the gradient-only seminorm on the mean-zero coercive layer.

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                                    noncomputable def HCPolySupport.H1MeanZeroFunction.gradientPairing {d : ℕ} {U : Set (Vec d)} {f : Vec d → Vec d} (hf : MemVectorL2 U f) (u : H1MeanZeroFunction U) :

                                    The gradient pairing of a mean-zero H¹ function against an L² vector field, realized through the Hilbert L² ambient space.

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                                      The gradient pairing, packaged as a linear functional on the mean-zero coercive H¹ layer.

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                                        The gradient pairing as a continuous linear functional for the gradient-only seminorm on the mean-zero coercive layer.

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                                          structure HCPolySupport.H1CoerciveEstimate {d : ℕ} (U : Set (Vec d)) :

                                          Bundled coercive estimate on the mean-zero H¹ layer.

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                                            The value realization as a linear map into scalar L²(U).

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                                              The value realization as a continuous linear map once a coercive estimate controls ‖u‖_{L²} by the gradient-only seminorm.

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                                                The mean-zero coercive layer packaged in the Hilbert product L²(U) × L²(U; ℝᵈ).

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                                                  The mean-zero coercive layer as a continuous linear map into L²(U) × L²(U; ℝᵈ) once a coercive estimate is available.

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