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LeanPool.Superdiffusion.Algsuperdiff.Section3.Provider.Stream.LargeCubeLinfty

LargeCubeLinfty #

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

The large-cube L∞ bound: ABK26's e.km.kn.Linfty #

ABK26 upgrades the small-cube estimate e.km.kn.Linfty.smallcube to the large cube cu_l: for n < m ≤ l,

‖k_m - k_n‖²_{L∞(cu_l)} ≤ O_{Γ₁}(C (l-n) min{γ^{-1}, m-n} 3^{2γm}),

by covering cu_l with translated copies of the small cube and applying the maximum lemma l.maximums.Gamma.s, which costs the amplitude factor (log N)^{1/2} with N the number of copies.

As in the small-cube layer, the statement is split into a deterministic part and a probabilistic part, because the finite increment k_m - k_n = ∑_{k ∈ (n,m]} j_k is not itself a shell and so carries no localCubeControl gauge.

Composing the two gives the source display for every realization: the left-hand side of e.km.kn.Linfty is the essential supremum over cu_l of the squared matrix norm of the increment, which is at most largeCubeSupBound l n m ^ 2 pointwise on cu_l.

The covering family is explicit: the shifts are the lattice points of 3^{n-1} ℤ^d with coordinates bounded by 3^{(l-n+1)^+}, and each translated open cube has scale n. Rounding each coordinate to the nearest lattice point moves it by at most 3^{n-1}/2 < 3^n/2, so the translated open cubes really do cover the whole of cu_l, with no boundary exception. The count is N = (2·3^{l-n+1} + 1)^d, so log N ≤ 3 d (l-n) log 3, which is the source's (l-n) factor with an explicit dimensional constant.

Deviations from the source, all absorbed by its C(d):

Main definitions #

Main results #

Algsuperdiff.Section3.Provider.Stream.matrixOperatorNorm_finiteShellIncrement_le_largeCubeSupBound

References #

The stream increment at an arbitrary base point #

theorem Algsuperdiff.Section3.Provider.Stream.isBigO_gammaSigma_incrementAt_entry {d : ℕ} (M : ABKModel d) {n m : ℤ} (hnm : n < m) (z : HCPolySupport.Vec d) (i l : Fin d) :
HCPolySupport.IndependentSums.IsBigO (↑M.P) (HCPolySupport.IndependentSums.gammaSigma 2) (fun (omega : Cutoff.ShellSeq d) => ∑ k ∈ Finset.Ioc n m, (↑(omega k)).1 z i l) (geometricConcentrationConst * min √M.gamma⁻¹ √(↑m - ↑n) * 3 ^ (M.gamma * ↑m))

ABK26's e.k.ell.upscales, entrywise at an arbitrary base point z: for n < m and every matrix entry,

∑_{k = n+1}^m j_k(z)_{il} = O_{Γ₂}(C min{γ^{-1/2}, (m-n)^{1/2}} 3^{γm}),

with an amplitude that does not depend on z.

ABK26's e.k.ell.upscales at an arbitrary base point z:

|(k_m - k_n)(z)| ≤ O_{Γ₂}(C min{γ^{-1/2}, (m-n)^{1/2}} 3^{γm}),

with |·| the exact Euclidean matrix operator norm. This is the translated form of isBigOWith_gammaSigma_originIncrement; the amplitude is the same, which is where the stationarity half of (J1) enters through isBigO_gammaSigma_shell_entry.

The small-cube bound on a translated cube #

The random variable dominating ‖k_m - k_n‖_{L∞(z + cu_n)}: the small-cube bound incrementSupBound of the translated shell sequence.

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    Translating the shell sequence translates the finite stream increment.

    The explicit form of the translated small-cube bound: the increment value at the base point z plus the geometric factor times the summed first-derivative gauges on the translated cube.

    The small-cube bound is nonnegative.

    The deterministic half of ABK26's e.k.ell.upscales.infty on a translated cube: at every point of z + cu_n the finite stream increment is dominated by translatedIncrementSupBound z n m.

    The value of the finite stream increment at a fixed point is a measurable random variable.

    The probabilistic half of ABK26's e.k.ell.upscales.infty on a translated cube, at the same amplitude as at the origin.

    A finite cover of the large cube by translated small cubes #

    The per-coordinate lattice radius of the covering family: the shifts range over the lattice 3^{n-1} ℤ^d with integer coordinates bounded by 3^{(l-n+1)^+}.

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      The finite index set of lattice shifts covering cu_l by translates of cu_n.

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        The lattice point of 3^{n-1} ℤ^d attached to an index.

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          The covering property: every point of the open cube cu_l lies in one of the translated open cubes z + cu_n of the family. Rounding each coordinate to the nearest point of the lattice 3^{n-1} ℤ^d moves it by at most 3^{n-1}/2, which is strictly less than the half-side 3^n/2, so the open cubes already cover cu_l.

          The maximum over the cover #

          The single random variable dominating ‖k_m - k_n‖_{L∞(cu_l)}: the maximum of the translated small-cube bounds over the covering family.

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            The deterministic half of ABK26's e.km.kn.Linfty: at every point of cu_l the finite stream increment is dominated by largeCubeSupBound l n m.

            The maximum over the cover, with the amplitude factor supplied by the proved cardinality-free maximum lemma.

            The source display #

            The universal factor produced by the maximum over the cover.

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              The count of the covering family is (2·3^{l-n+1} + 1)^d, so the amplitude factor of the maximum lemma is at most C(d) (l-n). This is the source's (l-n) factor, with an explicit dimensional constant.

              ABK26's e.km.kn.Linfty:

              ‖k_m - k_n‖²_{L∞(cu_l)} ≤ O_{Γ₁}(C (l-n) min{γ^{-1}, m-n} 3^{2γm}).

              The left-hand side is represented, as in the proved small-cube layer, by the random variable largeCubeSupBound l n m, which dominates the matrix operator norm of k_m - k_n at every point of cu_l by matrixOperatorNorm_finiteShellIncrement_le_largeCubeSupBound. The tail exponent moves from σ = 2 to σ = 1 through the proved power rule e.powerofGammasigma at p = 2, exactly as in the small-cube display.