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LeanPool.Superdiffusion.Algsuperdiff.StochasticProcess.Common.Regularity.Ported.ZerothOrderIteration

ZerothOrderIteration #

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

Dyadic iteration with a geometrically decaying scalar source #

theorem Algsuperdiff.StochasticProcess.Common.Regularity.Ported.dyadicSmallContrastIteration_zerothOrder {A : ℕ → ℝ} {alpha B C : ℝ} (halpha0 : 0 < alpha) (halpha1 : alpha < 1) (hA : ∀ (n : ℕ), 0 ≤ A n) (hB : 0 ≤ B) (hC : 0 ≤ C) (hrec : ∀ (n : ℕ), A (n + 1) ≤ smallContrastContraction alpha * A n + B + C * (1 / 2) ^ n) (n : ℕ) :
A n ≤ A 0 + 8 * (1 - alpha)⁻¹ * B + 2 * C

A scalar source whose dyadic contribution decays by one half adds only the literal factor 2, while the divergence source retains the printed 8(1-alpha)⁻¹ factor.

theorem Algsuperdiff.StochasticProcess.Common.Regularity.Ported.dyadicGradientScaleBound_zerothOrder_on_interiorBall {d : ℕ} [NeZero d] {U : Set (HCPolySupport.Vec d)} (z : HCPolySupport.Vec d) {R : ℝ} (hR : 0 < R) (hR1 : R ≤ 1) (houter : HCPolySupport.euclideanBall z R ⊆ U) {a : HCPolySupport.CoeffField d} {u : HCPolySupport.H1Function U} {g : HCPolySupport.Vec d → ℝ} {f : HCPolySupport.Vec d → HCPolySupport.Vec d} {delta alpha : ℝ} (hd : 2 ≤ d) (halpha0 : 0 < alpha) (halpha1 : alpha < 1) (hdelta0 : 0 ≤ delta) (hdelta : delta ≤ smallContrastThreshold d alpha) (hUopen : IsOpen U) (hmeas : Measurable a) (ha : CoefficientIdentityDistanceLE U a delta) (hu : IsMatrixDivFormWeakSolutionZerothOrderOn a U u g f) (hg : MemScalarLInfOn U g) (hf : MemVectorLpOn U (schauderSourceExponent d alpha) f) (n : ℕ) :

The concrete dyadic estimate on an interior ball for an equation with both a divergence source and a bounded scalar source. The scalar price is uniform in alpha.