Documentation

LeanPool.Superdiffusion.Algsuperdiff.Section3.Provider.Stream.LargeCubeW1Inf

LargeCubeW1Inf #

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

The summed derivative-stream bound: ABK26's e.W.1.inf.bound #

ABK26 states, for l, m, n ∈ ℤ with n ≤ min{m, l},

∑_{k = n+1}^m (3^k ‖∇j_k‖_{L∞(cu_l)} + 3^{2k} ‖∇²j_k‖_{L∞(cu_l)}) ≤ O_{Γ₂}(C (l-n)^{1/2} min{γ^{-1}, m-n} 3^{γm}).

The source proof has two regimes. For k < l the display e.W1inf.jL.bound.smaller covers cu_l by translates of cu_k and applies the maximum lemma l.maximums.Gamma.s to the single-shell derivative display e.nabla.jk.O, which costs the amplitude factor (log N)^{1/2} ≃ (l-k)^{1/2}. For k ≥ l the cube cu_l is contained in the own scale cube cu_k, so e.nabla.jk.O applies with no covering loss. The two regimes are then summed with the Γ₂ triangle inequality against the geometric series ∑_{k ∈ (n,m]} 3^{γk} ≤ C min{γ^{-1}, m-n} 3^{γm} (e.geo.part.sum).

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

Main definitions #

Main results #

References #

Elementary rewrites #

The source summand #

The summand of ABK26's e.W.1.inf.bound: 3^k ‖∇j_k‖_{L∞(cu_l)} + 3^{2k} ‖∇²j_k‖_{L∞(cu_l)}, read on the observation cube cu_l and at the shell index k.

Equations
  • One or more equations did not get rendered due to their size.
Instances For

    The exact factorization of the summand through the own-scale gauge weight.

    The covering maximum #

    The maximum, over the proved covering family of cu_l by translates of cu_k, of the translated own-scale derivative gauge ‖∇j‖_{L∞(z + cu_k)} + 3^k ‖∇²j‖_{L∞(z + cu_k)}.

    Equations
    • One or more equations did not get rendered due to their size.
    Instances For

      The covering bound for the first-derivative norm: every point of cu_l lies in one of the translated cubes z + cu_k, and the translated shell has the same derivative there.

      The deterministic half of e.W1inf.jL.bound.smaller: the source summand on cu_l is dominated by twice the weighted covering maximum.

      The probabilistic half of e.W1inf.jL.bound.smaller: the covering maximum obeys the single-shell Γ₂ estimate e.nabla.jk.O with the amplitude factor supplied by the proved cardinality-free maximum lemma.

      e.W1inf.jL.bound.smaller #

      ABK26's e.W1inf.jL.bound.smaller: for k < l,

      3^k ‖∇j_k‖_{L∞(cu_l)} + 3^{2k} ‖∇²j_k‖_{L∞(cu_l)} ≤ O_{Γ₂}(C (l-k)^{1/2} 3^{γk}),

      with the explicit dimensional constant 2 √(largeCubeLogConst · d).

      The uniform per-shell estimate #

      The dimensional constant covering both regimes of the source proof.

      Equations
      Instances For

        The per-shell estimate uniform in the two regimes of the source proof: for n < k the source summand on cu_l is O_{Γ₂}(C (1 ∨ (l-n))^{1/2} 3^{γk}).

        For k < l this is e.W1inf.jL.bound.smaller together with l - k ≤ l - n; for l ≤ k it is e.nabla.jk.O on the smaller cube cu_l ⊆ cu_k, whose amplitude carries no covering factor at all.

        e.W.1.inf.bound #

        theorem Algsuperdiff.Section3.Provider.Stream.sum_Ioc_rpow_gamma_le {d : ℕ} (M : ABKModel d) {n m : ℤ} (hnm : n ≤ m) :
        ∑ k ∈ Finset.Ioc n m, 3 ^ (M.gamma * ↑k) ≤ 7 / Real.log 3 * min M.gamma⁻¹ (↑m - ↑n) * 3 ^ (M.gamma * ↑m)

        The geometric series of the source amplitudes: ∑_{k ∈ (n,m]} 3^{γk} ≤ (7 / log 3) min{γ^{-1}, m-n} 3^{γm}. This is e.geo.part.sum at the halved exponent.

        ABK26's e.W.1.inf.bound, in its corrected form: for every n ≤ m,

        ∑_{k ∈ (n,m]} (3^k ‖∇j_k‖_{L∞(cu_l)} + 3^{2k} ‖∇²j_k‖_{L∞(cu_l)}) ≤ O_{Γ₂}(C (1 ∨ (l-n))^{1/2} min{γ^{-1}, m-n} 3^{γm}).

        The source hypothesis n ≤ l is dropped: it is not needed, since for l < n every shell of the range is estimated on the cube cu_l ⊆ cu_k at its own scale.