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LeanPool.AnomalousDiffusion.AVenhance.Infra.Section4.IteratesTAnalyticAssembly

Iterates TAnalytic Assembly #

Support for the Armstrong–Vicol anomalous-diffusion formalization.

theorem AVenhance.Infra.Section4.iterate_T_positive_analytic_of_increment_bounds {β : ℝ} (I : Ingredients β) {Φ : ℕ → ℝ → Homogenization.Vec 2 → ℝ} (hΦ : IsStreamSeq I Φ) {m : ℕ} {κm κprev : ℝ} {θ₀ : Homogenization.Vec 2 → ℝ} {θprev : ℝ → Homogenization.Vec 2 → ℝ} {T : ℕ → ℝ → Homogenization.Vec 2 → ℝ} (hT : I.IsTIterates hΦ m κm κprev θ₀ θprev T) (hθ : ContDiffOn ℝ (↑⊤) (fun (z : AmnrSpace) => θprev z.1 z.2) (Set.Ici 0 ×ˢ Set.univ)) {N L η : ℝ} (hκ : 0 < κprev) (hN : 0 ≤ N) (hL : 0 ≤ L) (hη : 0 ≤ η) (hsmall : η ≤ 1 / 4) (hbase : iterateCoordinateEnergyProfile θprev κprev N L 0) (hV : ∀ (i : ℕ), 1 ≤ i → i ≤ Nstar β → ∀ (v w : List (Fin 2)), v.length = w.length → ∀ (s : ℝ), 0 ≤ s → s ≤ 1 → √(l2NormSq (iterateSpatialWord v (iterateIncrement T i s))) + √κprev * √(spaceTimeGradNormSq fun (t : ℝ) => spaceGrad (iterateSpatialWord w (iterateIncrement T i t))) ≤ N * iterateAmplitude η i * iterateAnalyticWeight v.length i L) (v w : List (Fin 2)) (hvw : v.length = w.length) (hv : 1 ≤ v.length) {s : ℝ} (hs : 0 ≤ s) (hs1 : s ≤ 1) :
√(l2NormSq (iterateSpatialWord v (T (Nstar β) s))) + √κprev * √(spaceTimeGradNormSq fun (t : ℝ) => spaceGrad (iterateSpatialWord w (T (Nstar β) t))) ≤ N * 4 ^ Nstar β * ↑(2 * Nstar β).factorial * ↑v.length.factorial * (4 * L) ^ v.length

The analytic T upgrade at positive scalar order, with abstract amplitude. This is a finite-sum helper; actual PDE l.V supplies its increment estimates.

theorem AVenhance.Infra.Section4.iterate_T_zero_gradient_relative_of_increment_bounds {β : ℝ} (I : Ingredients β) {Φ : ℕ → ℝ → Homogenization.Vec 2 → ℝ} (hΦ : IsStreamSeq I Φ) {m : ℕ} {κm κprev : ℝ} {θ₀ : Homogenization.Vec 2 → ℝ} {θprev : ℝ → Homogenization.Vec 2 → ℝ} {T : ℕ → ℝ → Homogenization.Vec 2 → ℝ} (hT : I.IsTIterates hΦ m κm κprev θ₀ θprev T) (hθ : ContDiffOn ℝ (↑⊤) (fun (z : AmnrSpace) => θprev z.1 z.2) (Set.Ici 0 ×ˢ Set.univ)) {N η : ℝ} (hN : 0 ≤ N) (hη : 0 ≤ η) (hsmall : η ≤ 1) (hzero : √κprev * √(spaceTimeGradNormSq fun (t : ℝ) => spaceGrad (θprev t)) ≤ N) (hV : ∀ (i : ℕ), 1 ≤ i → i ≤ Nstar β → √κprev * √(spaceTimeGradNormSq fun (t : ℝ) => spaceGrad (iterateIncrement T i t)) ≤ N * iterateAmplitude η i * ↑(2 * i).factorial) :
√κprev * √(spaceTimeGradNormSq fun (t : ℝ) => spaceGrad (T (Nstar β) t)) ≤ N * (1 + η * ↑(Nstar β) * ↑(2 * Nstar β).factorial)

Zeroth T order is exclusively a gradient estimate; no scalar supremum is present in either its hypotheses or its conclusion.