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LeanPool.Superdiffusion.Algsuperdiff.Section4.Provider.Proportion.G2Score

G2Score #

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

The 𝒒₂ score layer: the squared annular maximum, the atom X_j, and the #

exact interchange identity #

ABK26, Β§4.1, the proof of l.ratio.of.good.scales.for.mathcal.E, Steps 1, 2 and 4.

The 𝒒₂ lane is structurally the cleanest of the three: where the 𝒒₀ reduction is a chain of inequalities, the 𝒒₂ reduction is an equality:

s Ξ£_{j ≀ m} Ξ£_{n ≀ jβˆ’1} 3^{βˆ’ΒΌs(mβˆ’n)} max_{z ∈ 3ⁿ℀^d ∩ (β–‘_jβˆ–β–‘_{jβˆ’1})} 𝓔_{s,2,2}(z+β–‘_n;Β·)Β²
  = Kβ‚‚^{βˆ’1} s Ρ² Y_m ,        Y_m = Ξ£_{j ≀ m} 3^{βˆ’ΒΌs(mβˆ’j)} X_j ,

whose entire content is the exponent split 3^{βˆ’ΒΌs(mβˆ’n)} = 3^{βˆ’ΒΌs(mβˆ’j)}Β·3^{βˆ’ΒΌs(jβˆ’n)} (annularWeight_split). Everything below is proved as an identity of ℝβ‰₯0∞, so no convergence, no a.s. qualifier and no null set enters: the convergence caveat that the printed Y_m identity leaves implicit is therefore never needed.

Main definitions #

Main results #

Deviations from the printed text #

Scope #

Provider material: proved local helpers.

References #

1. The geometric weight of the 𝒒₂ lane #

The 𝒒₂ weight 3^{βˆ’ΒΌsk}, in ℝβ‰₯0∞. Written exactly as the frozen Support.eventG2 writes it, so the identifications below are definitional on the weight.

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    The exponent split. 3^{βˆ’ΒΌs(mβˆ’n)} = 3^{βˆ’ΒΌs(mβˆ’j)}Β·3^{βˆ’ΒΌs(jβˆ’n)}: the single computation behind's "by interchanging summation".

    The weight at a nonnegative offset is the 𝒒₀ lane's weightThird at rate ΒΌs; this is what lets the β„•-indexed series apparatus of SeriesTail be reused verbatim.

    2. The squared per-cube atom and its lattice maximum #

    The 𝒒₂ per-cube atom 𝓔_{s,2,2}(z+β–‘_n; 𝐚_{nβˆ’2}, Οƒ_{nβˆ’2})Β², rendered by translating the sample, at the measurable (2,2) observable.

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      The left side of Step 1: max_{z ∈ 3^nβ„€^d ∩ (β–‘_jβˆ–β–‘_{jβˆ’1})} 𝓔_{s,2,2}(z+β–‘_n; 𝐚_{nβˆ’2}, Οƒ_{nβˆ’2})Β², 0-floored so that it is total (the annulus enumeration may be empty).

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        The same maximum in the ℝβ‰₯0∞ supremum shape of the frozen event.

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          The Finset maximum and the set supremum agree #

          theorem Algsuperdiff.Section4.Provider.Proportion.exists_mem_eq_fmax {iota : Type u_1} {S : Finset iota} {f : iota β†’ ℝ} (hS : S.Nonempty) (hf : βˆ€ i ∈ S, 0 ≀ f i) :
          βˆƒ i ∈ S, fmax S f = f i

          A nonempty Finset attains its 0-floored maximum at a member, provided the values there are nonnegative.

          The two renderings of the lattice maximum coincide. The Finset enumeration latticeAnnulusFinset and the proved set latticeAnnulusSet have the same members at n ≀ j, and all entries are squares, hence nonnegative, so the 0-floor is not felt.

          3. The atom X_j and the row sum #

          The atom X_j, formed in ℝβ‰₯0∞ and WITHOUT the manuscript's lane prefactor Kβ‚‚Ξ΅^{βˆ’2}: Ξ£_{n ≀ jβˆ’1} 3^{βˆ’ΒΌs(jβˆ’n)} max_{z ∈ 3^nβ„€^d ∩ (β–‘_jβˆ–β–‘_{jβˆ’1})} 𝓔_{s,2,2}(z+β–‘_n;Β·)Β².

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            The one-sided row sum Y_m, before the Kβ‚‚Ξ΅^{βˆ’2} normalization.

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              The β„•-enumeration of the inner scales #

              The inner scales n ≀ j βˆ’ 1 enumerated by the offset j βˆ’ n βˆ’ 1 ∈ β„•.

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                theorem Algsuperdiff.Section4.Provider.Proportion.XcalE_eq_wsumE {d : β„•} (M : Section3.ABKModel d) (s : { s : ℝ // 0 < s }) (j : β„€) (omega : Section3.Cutoff.CutoffSample d) :
                XcalE M s j omega = wsumE (fun (i : β„•) => errorAnnMax M s j (j - 1 - ↑i)) (fun (i : β„•) => weightThird (↑s / 4) (i + 1)) omega

                The atom is the SeriesTail weighted series at the 𝒒₀ lane's weight weightThird (ΒΌs) shifted by one (the inner offset j βˆ’ n starts at 1). This is the bridge that lets the countable generalized triangle inequality isBigOWith_wsum and the moment engine be reused verbatim on the 𝒒₂ lane.

                4. The identity #

                theorem Algsuperdiff.Section4.Provider.Proportion.inner_eq_annularWeight_mul_XcalE {d : β„•} (M : Section3.ABKModel d) (s : { s : ℝ // 0 < s }) (m j : β„€) (omega : Section3.Cutoff.CutoffSample d) :
                βˆ‘' (n : { n : β„€ // n ≀ j - 1 }), annularWeight (↑s) (m - ↑n) * errorAnnSup M s j (↑n) omega = annularWeight (↑s) (m - j) * XcalE M s j omega

                The identity. For every row index m and every annulus index j, the inner block of the 𝒒₂ display is exactly the discounted atom. This is an equality of ℝβ‰₯0∞: nothing is dropped, no convergence is used, and the entire content is annularWeight_split.

                5. The frozen event, in row-sum form #

                The frozen 𝒒₂ event IS {sΒ·XrowE ≀ Ρ²}. A set equality, obtained by applying the identity inside the outer sum.

                The complement of the frozen 𝒒₂ event, in row form.