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LeanPool.Superdiffusion.Algsuperdiff.Section4.Provider.Schauder.CubeSchauderPointwise

CubeSchauderPointwise #

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

Cube Schauder: from the Campanato bound to a pointwise C^{0,1/2} slope field #

  E(u, (z+□_j) ∩ □_m) ≤ K · √(3^j)      for every z ∈ S and every j ≤ m+1 .

From it we build the continuous slope field

  Ψ(z) := lim_{j → -∞} ∇ℓ(u, (z+□_j) ∩ □_m)

and prove the two displays the cube Schauder core needs about it: a C^{0,1/2} seminorm bound with a d-constant times K, and a sup bound at the top scale.

Why the family is Cauchy, and why no chaining lemma is needed #

CubeSchauderSlope.slopeMagnitude_windowSlope_sub_le bounds the slope increment by the two excesses, so consecutive slopes differ by at most 2·C_stab·K·√(3^j) — a geometric sequence of ratio √(1/3), whence mathlib's cauchySeq_of_le_geometric and dist_le_of_le_geometric_of_tendsto give the limit and its tail estimate in two lines each.

For the two-point estimate the usual Campanato argument runs a local Hölder bound (valid only for nearby points) and then chains it along segments of a convex set. That chaining step is not needed here: at the top scale j = m+1 every window (z+□_{m+1}) ∩ □_m is the same set □_m, so all the slopes coincide there and the far-apart case is closed by two tail estimates alone. This is what makes the module short.

Main results #

References #

1. Two window identities #

A window at a nearby centre and one scale down sits inside the window at x: if ‖x − y‖ < 3^k then (y+□_k) ∩ □_m ⊆ (x+□_{k+1}) ∩ □_m.

Two points of □_m are less than 3^m apart in the ambient sup norm.

2. The Campanato constants #

The geometric ratio of the slope telescope: √(1/3).

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    The slope-stability constant of the truncated window family.

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      3. The one-step slope increment #

      The scale factorization used by the geometric telescope.

      The slope increment at one triadic step.

      Under the Campanato datum the slopes on consecutive windows about the same centre differ by at most 2·C_stab(d)·K·√(3^j).

      4. The limit field #

      The Campanato slope field. Ψ(z) is the limit of the affine-minimizer slopes of u on the windows (z+□_{T-n}) ∩ □_m as n → ∞. The top index T is a parameter: the interior regime runs it at T = m (the range of CubeSchauderCampanato.affineExcess_le_campanato), the full-cube regime at T = m+1, where every window degenerates to □_m.

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        The geometric step bound of the reindexed slope sequence.

        The reindexed slope sequence is Cauchy.

        The tail estimate. At every scale j ≤ T the slope of the window at scale j is within C_tail(d)·K·√(3^j) of the limit.

        5. The top scale #

        6. The two-point estimate #

        The Hölder constant of the slope field: √3·(2·C_tail + 2·C_stab·(1 + √3)).

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          theorem Algsuperdiff.Section4.Provider.Schauder.holderSeminormBoundOn_campanatoSlopeLimit {d : ℕ} (hd : 0 < d) {m T : ℤ} {S : Set (HCPolySupport.Vec d)} (hS : S ⊆ HCPolySupport.openCubeSet (HCPolySupport.originCube d m)) (hTm : T ≤ m + 1) {u : HCPolySupport.Vec d → ℝ} (hu : MeasureTheory.MemLp u 2 (MeasureTheory.volume.restrict (HCPolySupport.openCubeSet (HCPolySupport.originCube d m)))) {K : ℝ} (hK : 0 ≤ K) (hdiamS : ∀ x ∈ S, ∀ y ∈ S, ‖x - y‖ < 3 ^ (T - 1)) (hE : ∀ z ∈ S, ∀ i ≤ T, Support.affineExcess (ExcessDecay.truncatedWindow z m i) u ≤ K * √(3 ^ i)) :

          The C^{0,1/2} bound of the slope field.

          If the Campanato datum holds at every point of S ⊆ □_m up to the top scale T with constant K, and S has diameter below 3^{T-1}, then

            ‖Ψ(x) − Ψ(y)‖ ≤ campanatoHolderConst d · K · ‖x − y‖^{1/2}
          

          for all x, y ∈ S. No convexity of S and no chaining are needed: for far apart points the two windows at scale T-1 sit inside the common window (x+□_T) ∩ □_m, which closes the case with two tails and two slope comparisons.