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LeanPool.Superdiffusion.Algsuperdiff.Section4.Probability.AnnulusRDependent

AnnulusRDependent #

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

r-dependence of the annular per-scale atoms #

ABK26 applies Proposition p.concentration to the per-scale annular atoms three times, each time through the sentence "since the sequence {X_j} is 2-dependent". The abstract hypothesis is Algsuperdiff.Probability.RDependent; the geometry is AnnulusSeparation.separatedBy_annulusRegion_of_gap; the probability is ShellActiveSigma.iIndepFun_of_local_cutoffSample. This module is the one bridge that joins them, and nothing else.

The statement #

rDependent_of_annulusLocalSigma: if every X n is measurable for the single sigma-field cutoffSampleLocalSigma M (n − c) (annulusRegion d n) — i.e. X n reads only truncations at or below level n − c, and only on the annulus of its own index — then X is r-dependent for every r ≥ 1 with 3 + 2·3^{1−c}·√d ≤ 3^r.

The truncation offset c and the count r are free.

Who supplies the hypothesis #

hX is exactly the hloc slot the proved 𝒢₂ lane already discharges:

Main results #

References #

The bridge #

theorem Algsuperdiff.Section4.Probability.rDependent_of_annulusLocalSigma {d : ℕ} (M : Section3.ABKModel d) (c : ℤ) {r : ℕ} (hr1 : 1 ≤ r) (hr : 3 + 2 * 3 ^ (1 - c) * √↑d ≤ 3 ^ r) {X : ℤ → Section3.Cutoff.CutoffSample d → ℝ} (hX : ∀ (n : ℤ), Measurable (X n)) :

The r-dependence of the annular atoms. A family X : ℤ → Ω → ℝ on the genuine cutoff carrier, each member of which reads only truncations at or below its own level n − c and only on the annulus annulusRegion d n of its own index, is r-dependent for the cutoff law, for every r ≥ 1 with 3 + 2·3^{1−c}·√d ≤ 3^r.

The proof is the composition of the two proved halves: the finite set of pairwise ≥ r-separated indices carried is turned into the pairwise geometric separation separatedBy_annulusRegion_of_gap at the shared-shell threshold √d · 3^{min (n−c) (n'−c)}, which is verbatim the hsep hypothesis of iIndepFun_of_local_cutoffSample at Lidx n = n − c.