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LeanPool.Superdiffusion.Algsuperdiff.Section4.Provider.Proportion.G2RowConversion

G2RowConversion #

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

The 𝒒₂ row: from the manuscript's one-sided ℝβ‰₯0∞ sum to Appendix D's #

two-sided real sum #

ABK26, Β§4.1, l.ratio.of.good.scales.for.mathcal.E Step 4 reconciled with Appendix D's row (e.Yk.def.twosided).

This module supplies the conversion, exactly as RowSumFinite does for the 𝒒₀ lane and by the same device:

  1. lintegral_XcalE_le β€” Tonelli over the inner series defining X_j, with the per-annulus two-term displays of G2AtomTail.isTwoTermBigOWith_errorAnnMax at p = 1. The bound xcalMoment is uniform in j: the Step-1 amplitudes depend on j βˆ’ n, not on j.
  2. lintegral_XrowTwoE_le β€” Tonelli again over the β„€-row, with the geometric weight sum Ξ£_{j ∈ β„€} 3^{βˆ’ΒΌs|mβˆ’j|} ≀ 12/s.
  3. measure_compl_goodRowSetG2 β€” the two finite expectations make the countable families {X_j = ∞} and {row_m = ∞} null.
  4. XrowE_le_XrowTwoE β€” on the good set the one-sided row sits below the two-sided one (the inequality is in the manuscript's favour: the j > m rows are nonnegative).
  5. lt_Yk_of_notMem_eventG2 β€” the deterministic half of the hreduce slot of the Appendix-D concentration interface, entered through G2Score's exact event characterization.

Everything is a first-moment computation; no Borel--Cantelli is used, and the null set is paid for by RowSumFinite.measure_scaleProp_le_of_null_enlargement.

Scope #

Provider material: proved local helpers. hcube is a conditional A obligation, discharged at the caller by G2CubeBound.

References #

1. Two small ℝβ‰₯0∞ devices #

2. Measurability of the 𝒒₂ atom in both readings #

3. The first moment of the 𝒒₂ atom #

The uniform first-moment majorant of the 𝒒₂ atom X_j. The two Step-2 weighted penalty series, weighted by the moment constants of the two Orlicz lanes. It does not depend on j.

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    The p = 1 case of the two-term moment engine. A nonnegative random variable with a two-term weak-Orlicz display has first moment at most the sum of the two lanes' one-term moments.

    4. The two-sided Appendix-D row, formed in ℝβ‰₯0∞ #

    The Appendix-D row of the 𝒒₂ atoms, formed in ℝβ‰₯0∞. Two-sided, matching ScalesConcentration.Yk at the 𝒒₂ lane rate s' = ΒΌs, and total. The manuscript's one-sided row XrowE sits below it.

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      5. The null set of the enlargement #

      The full-measure set on which the 𝒒₂ Appendix-D row is the honest series. Both the inner series defining each X_j and the β„€-row of the X_j are finite there; off it the real tsum carries no information.

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        6. The row conversion and the Appendix-D reduction #

        theorem Algsuperdiff.Section4.Provider.Proportion.XrowE_le_XrowTwoE {d : β„•} (M : Section3.ABKModel d) (s : { s : ℝ // 0 < s }) (m : β„€) {omega : Section3.Cutoff.CutoffSample d} (hfin : βˆ€ (j : β„€), XcalE M s j omega β‰  ⊀) :
        XrowE M s m omega ≀ XrowTwoE M s m omega

        The ℝβ‰₯0∞ one-sided row is below the real two-sided row, on the set where the atoms are finite. This is the reconciliation of the manuscript's Ξ£_{j ≀ m} with Appendix D's Ξ£_{j ∈ β„€}, the inequality being in the manuscript's favour: the j > m rows are nonnegative.

        theorem Algsuperdiff.Section4.Provider.Proportion.lt_Yk_of_notMem_eventG2 {d : β„•} (M : Section3.ABKModel d) (s : { s : ℝ // 0 < s }) {ep D : ℝ} (hD : 0 < D) (m : β„€) {omega : Section3.Cutoff.CutoffSample d} (hgood : omega ∈ goodRowSetG2 M s) (hnot : omega βˆ‰ Support.eventG2 M m s ep) :
        D⁻¹ * (ep ^ 2 / ↑s) < Probability.ScalesConcentration.Yk (xcalArray M s D) (↑s / 4) m omega

        The Appendix-D reduction of 𝒒₂, off the null set. Off 𝒒₂(m;s,Ξ΅) β€” and off the null set of goodRowSetG2 β€” the Appendix-D row sum of the normalized atoms exceeds D^{-1}Ρ²s^{-1}. The entry point is G2Score.notMem_eventG2_iff, which is an exact characterization, so nothing is lost here beyond the j > m rows.