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LeanPool.Superdiffusion.Algsuperdiff.StochasticProcess.Common.DivergenceForm.WholeSpace.ExcessiveCubeData

ExcessiveCubeData #

Ported from scottnarmstrong/Superdiffusion at 7f20476385d4af418f110303085ad0740c9eba46. Module imports, support namespace and local option directives adapted for Lean Pool.

The barrier data on an axis cube #

The caller obligation of WholeSpaceBarrierData is the continuous representative of the part solution which vanishes on the geometric boundary of the part domain. On an axis cube it is discharged: the shifted residual of a bounded measurable datum is a bounded scalar source, so the closed-cube boundary representative of the regularity layer applies, and a continuous function on the closed cube vanishing on its geometric boundary extends by zero to a continuous function on the whole space.

The resulting barrier data needs no input beyond the coefficient field and the observable.

A continuous closed-cube function vanishing on the geometric boundary extends by zero to a continuous function on the whole space.

The continuous zero extension of the part solution on an axis cube. The closed-cube boundary representative of the regularity layer applies to the shifted residual of a bounded measurable datum, and its zero extension is continuous on the whole space.

noncomputable def DivergenceFormProcess.Form.axisCubeBarrierData {d : ℕ} [NeZero d] (A : WholeSpaceAnalyticData d) (z : HCPolySupport.Vec d) {L : ℝ} (hL : 0 < L) (lam : ↑MarkovProcess.Semigroup.PositiveShift) {f : HCPolySupport.Vec d → ℝ} (hf : Measurable f) (hf0 : ∀ (x : HCPolySupport.Vec d), 0 ≤ f x) {D : ℝ} (hfD : ∀ (x : HCPolySupport.Vec d), |f x| ≤ D) (hfV : f =ᵐ[MeasureTheory.volume] (HCPolySupport.axisCube z L).indicator f) :

The barrier data of the whole-space comparison on an axis cube. Every field is discharged: the continuous zero extension of the part solution comes from the closed-cube boundary representative.

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Instances For
    @[simp]
    theorem DivergenceFormProcess.Form.axisCubeBarrierData_V {d : ℕ} [NeZero d] (A : WholeSpaceAnalyticData d) (z : HCPolySupport.Vec d) {L : ℝ} (hL : 0 < L) (lam : ↑MarkovProcess.Semigroup.PositiveShift) {f : HCPolySupport.Vec d → ℝ} (hf : Measurable f) (hf0 : ∀ (x : HCPolySupport.Vec d), 0 ≤ f x) {D : ℝ} (hfD : ∀ (x : HCPolySupport.Vec d), |f x| ≤ D) (hfV : f =ᵐ[MeasureTheory.volume] (HCPolySupport.axisCube z L).indicator f) :
    (axisCubeBarrierData A z hL lam hf hf0 hfD hfV).V = HCPolySupport.axisCube z L
    @[simp]
    theorem DivergenceFormProcess.Form.axisCubeBarrierData_lam {d : ℕ} [NeZero d] (A : WholeSpaceAnalyticData d) (z : HCPolySupport.Vec d) {L : ℝ} (hL : 0 < L) (lam : ↑MarkovProcess.Semigroup.PositiveShift) {f : HCPolySupport.Vec d → ℝ} (hf : Measurable f) (hf0 : ∀ (x : HCPolySupport.Vec d), 0 ≤ f x) {D : ℝ} (hfD : ∀ (x : HCPolySupport.Vec d), |f x| ≤ D) (hfV : f =ᵐ[MeasureTheory.volume] (HCPolySupport.axisCube z L).indicator f) :
    (axisCubeBarrierData A z hL lam hf hf0 hfD hfV).lam = lam
    @[simp]
    theorem DivergenceFormProcess.Form.axisCubeBarrierData_f {d : ℕ} [NeZero d] (A : WholeSpaceAnalyticData d) (z : HCPolySupport.Vec d) {L : ℝ} (hL : 0 < L) (lam : ↑MarkovProcess.Semigroup.PositiveShift) {f : HCPolySupport.Vec d → ℝ} (hf : Measurable f) (hf0 : ∀ (x : HCPolySupport.Vec d), 0 ≤ f x) {D : ℝ} (hfD : ∀ (x : HCPolySupport.Vec d), |f x| ≤ D) (hfV : f =ᵐ[MeasureTheory.volume] (HCPolySupport.axisCube z L).indicator f) :
    (axisCubeBarrierData A z hL lam hf hf0 hfD hfV).f = f