Documentation

LeanPool.Superdiffusion.Algsuperdiff.Section3.Provider.Multiscale.ConclusionAssembly

ConclusionAssembly #

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

The layer series of p.bfA.multiscalebound, Step 3, at the corrected density #

ABK26, proof of Proposition p.bfA.multiscalebound, Step 3. After the per-layer estimates are in place the manuscript sums over the Whitney layer index k,

  sum_k 3^{-k} ( C 3^{gamma (k + h_k)}
                 + C 3^{2 b (k + h_k)} ( bad density of layer k ) )
    <=  C 3^{gamma (hsep + k_0)} ( 1 + 3^{2 b (hsep + k_0)}
              ( exp(-c E^{-2} gamma^{-1}) + 3^{-k_0/2} ) ) ,

and then collapses the k_0-dependent factor.

What changes against the printed Step 3 #

l.bad.cubes.density is available here only in its mass form, Provider.Whitney.sum_cubeMassRatio_badFamilyLayer_le: the bad mass of layer k relative to cu_m. The printed Step 3 weights that quantity by the layer's own mass fraction 3^{-k} a second time, and with only the mass form the resulting k-sum of the exp(-c E^{-2} gamma^{-1}) leg diverges. Concretely, layerContrib below weights

The 3^{-k/2} that survives degrades the series ratio from the printed 3^{-3/4} to 3^{-1/4} (three_rpow_layerQuantity_collar_decay) and forces the square-root collapse k0_sqrt_collapse with its exponent 1/36 in place of the printed 1/4. Both are in Provider.Multiscale.ConclusionArithmetic.

The layer-mass A input and its downstream producer #

LayerMassBound m hn Cmass -- "the Whitney layer k carries mass at most Cmass 3^{-k} inside cu_m" -- is not proved in this file and is carried as an explicit A hypothesis wherever it is needed. It is a purely combinatorial statement about Provider.Whitney.whitneyLayer: the layer-k cubes sit under the depth-(k-1) descendants of cu_m that touch ∂cu_m, of which there are at most 2 d 3^{(k-1)(d-1)} out of 3^{d(k-1)}, so the expected constant is Cmass = 6 d. The downstream file LayerMass.lean now proves and applies this bound at that constant. The declarations here retain the abstract input and therefore remain conditional; the downstream discharge is not a premise of the source statement and does not turn this file into a node closure.

What is not here #

In this file, the 3^{gamma hsep} prefactor reduction stops after its deterministic half's display three_rpow_le_two_add_indicator (in ConclusionArithmetic), and the bridge from the manuscript's 3^{gamma hsep} to the proved tail Provider.Percolation.isBigOWith_gammaSigma_three_rpow_hsep (which is stated at 3^{b hsep}, at the amplitude hsepAmplitude sigma b rather than the printed 1) is three_rpow_gamma_hsep_le_three_rpow_b_hsep. The remaining Orlicz half -- e.indc.O.sigma for the indicator and e.multGammasig for the product -- is assembled only in later multiscale providers.

References #

The Whitney layer quantity k + h_k #

ABK26's layer quantity k + h_k as a real, at the proved scale profile Provider.Whitney.whitneyScaleSeq (`h_k = ceil(b (1-b)^{-1} k) + hsep

  • k_0`).
Equations
Instances For

    Every Whitney layer sits above the tuning scale: k + h_k >= k_0.

    theorem Algsuperdiff.Section3.Provider.Multiscale.layerQuantity_le {b : ℝ} (hb0 : 0 < b) (hb1 : b < 1) (hs k₀ k : ℕ) :
    layerQuantity b hs k₀ k ≤ (1 - b)⁻¹ * ↑k + (↑hs + ↑k₀ + 1)

    Slow growth of the layer quantity (e.hn.def summed): from h_k = ceil(b (1-b)^{-1} k) + hsep + k_0 and ceil t < t + 1, k + h_k <= (1-b)^{-1} k + (hsep + k_0 + 1).

    The two layer decays #

    theorem Algsuperdiff.Section3.Provider.Multiscale.three_rpow_layerQuantity_decay {b α : ℝ} (hb0 : 0 < b) (hb1 : b < 1) (hα0 : 0 ≤ α) (hα : 4 * α ≤ 1 - b) (hs k₀ k : ℕ) :
    3 ^ (-↑k) * 3 ^ (α * layerQuantity b hs k₀ k) ≤ 3 ^ (α * (↑hs + ↑k₀ + 1)) * (3 ^ (-(3 / 4))) ^ k

    The printed layer decay. For alpha >= 0 with 4 alpha <= 1 - b, the layer mass 3^{-k} beats the growth 3^{alpha (k+h_k)} at the printed rate 3^{-3k/4}. Applied at alpha = gamma (the good leg of e.good.simplex.consequence) and at alpha = 2 b (the collar amplification of e.bounds.on.slopes.when.bad).

    theorem Algsuperdiff.Section3.Provider.Multiscale.three_rpow_layerQuantity_collar_decay {b : ℝ} (hb0 : 0 < b) (hb9 : 9 * b ≤ 1) (hs k₀ k : ℕ) :
    3 ^ (-↑k / 2) * 3 ^ (2 * b * layerQuantity b hs k₀ k) ≤ 3 ^ (2 * b * (↑hs + ↑k₀ + 1)) * (3 ^ (-(1 / 4))) ^ k

    The corrected collar decay. After the Cauchy-Schwarz step only half of the layer mass, 3^{-k/2}, is available against the collar amplification 3^{2 b (k+h_k)}, and the surviving ratio is 3^{-1/4} rather than the printed 3^{-3/4}. The hypothesis 9 b <= 1 is exactly what 4 (2 b) <= 1 - b demands -- the same gate as k0_sqrt_collapse.

    The per-layer contribution #

    noncomputable def Algsuperdiff.Section3.Provider.Multiscale.layerContrib (b γ : ℝ) (hs k₀ : ℕ) (Ktot Ccol : ℝ) (Mass Bad : ℕ → ℝ) (k : ℕ) :

    The printed Step 3 puts an extra 3^{-k} in front of the collar leg shows it is not available.

    Equations
    • One or more equations did not get rendered due to their size.
    Instances For
      theorem Algsuperdiff.Section3.Provider.Multiscale.layerContrib_nonneg {b γ Ktot Ccol : ℝ} {hs k₀ : ℕ} {Mass Bad : ℕ → ℝ} (hK : 0 ≤ Ktot) (hC : 0 ≤ Ccol) (hMass0 : ∀ (j : ℕ), 0 ≤ Mass j) (hBad0 : ∀ (j : ℕ), 0 ≤ Bad j) (k : ℕ) :
      0 ≤ layerContrib b γ hs k₀ Ktot Ccol Mass Bad k
      theorem Algsuperdiff.Section3.Provider.Multiscale.layerContrib_le {b γ ε Cmass Ktot Ccol : ℝ} {hs k₀ : ℕ} {Mass Bad : ℕ → ℝ} (hb0 : 0 < b) (hb9 : 9 * b ≤ 1) (hγ0 : 0 ≤ γ) (hγ : 4 * γ ≤ 1 - b) (hK : 0 ≤ Ktot) (hC : 0 ≤ Ccol) (hCmass : 0 ≤ Cmass) (hε0 : 0 ≤ ε) (hMass : ∀ (j : ℕ), Mass j ≤ Cmass * 3 ^ (-↑j)) (hBadMass : ∀ (j : ℕ), Bad j ≤ Cmass * 3 ^ (-↑j)) (hBadDens : ∀ (j : ℕ), Bad j ≤ ε + 3 ^ (-(layerQuantity b hs k₀ j / 2))) (k : ℕ) :
      layerContrib b γ hs k₀ Ktot Ccol Mass Bad k ≤ (Ktot * Cmass * 3 ^ (γ * (↑hs + ↑k₀ + 1)) + Ccol * (√Cmass * (3 ^ (2 * b * (↑hs + ↑k₀ + 1)) * √(ε + 3 ^ (-(↑k₀ / 2)))))) * (3 ^ (-(1 / 4))) ^ k

      The termwise bound at the density. Each layer contributes at most an explicit constant times (3^{-1/4})^k; the collar constant carries (eps + 3^{-k_0/2})^{1/2}, exponentially small in k_0.

      theorem Algsuperdiff.Section3.Provider.Multiscale.summable_layerContrib {b γ ε Cmass Ktot Ccol : ℝ} {hs k₀ : ℕ} {Mass Bad : ℕ → ℝ} (hb0 : 0 < b) (hb9 : 9 * b ≤ 1) (hγ0 : 0 ≤ γ) (hγ : 4 * γ ≤ 1 - b) (hK : 0 ≤ Ktot) (hC : 0 ≤ Ccol) (hCmass : 0 ≤ Cmass) (hε0 : 0 ≤ ε) (hMass0 : ∀ (j : ℕ), 0 ≤ Mass j) (hBad0 : ∀ (j : ℕ), 0 ≤ Bad j) (hMass : ∀ (j : ℕ), Mass j ≤ Cmass * 3 ^ (-↑j)) (hBadMass : ∀ (j : ℕ), Bad j ≤ Cmass * 3 ^ (-↑j)) (hBadDens : ∀ (j : ℕ), Bad j ≤ ε + 3 ^ (-(layerQuantity b hs k₀ j / 2))) :
      Summable fun (k : ℕ) => layerContrib b γ hs k₀ Ktot Ccol Mass Bad k

      The layer series converges at the ratio 3^{-1/4}.

      The Step-3 payload #

      noncomputable def Algsuperdiff.Section3.Provider.Multiscale.layerSumConst (b γ : ℝ) (k₀ : ℕ) (Ktot Ccol Cmass : ℝ) :

      Crucially it carries no 3^{2 b k_0} — the load-bearing property of this constant.

      Equations
      Instances For
        theorem Algsuperdiff.Section3.Provider.Multiscale.tsum_layerContrib_le_payload {b γ ε Cmass Ktot Ccol : ℝ} {hs k₀ : ℕ} {Mass Bad : ℕ → ℝ} (hb0 : 0 < b) (hb9 : 9 * b ≤ 1) (hγ0 : 0 ≤ γ) (hγ : 4 * γ ≤ 1 - b) (hK : 0 ≤ Ktot) (hC : 0 ≤ Ccol) (hCmass : 0 ≤ Cmass) (hε0 : 0 ≤ ε) (hεk0 : ε ≤ Real.exp (-↑k₀)) (hMass0 : ∀ (j : ℕ), 0 ≤ Mass j) (hBad0 : ∀ (j : ℕ), 0 ≤ Bad j) (hMass : ∀ (j : ℕ), Mass j ≤ Cmass * 3 ^ (-↑j)) (hBadMass : ∀ (j : ℕ), Bad j ≤ Cmass * 3 ^ (-↑j)) (hBadDens : ∀ (j : ℕ), Bad j ≤ ε + 3 ^ (-(layerQuantity b hs k₀ j / 2))) :
        ∑' (k : ℕ), layerContrib b γ hs k₀ Ktot Ccol Mass Bad k ≤ layerSumConst b γ k₀ Ktot Ccol Cmass * (3 ^ (γ * ↑hs) * (1 + 3 ^ (2 * b * ↑hs) * Real.exp (-(↑k₀ / 36))))
          sum_k (layer k)  <=  C ( 3^{gamma hsep} ( 1 + 3^{2 b hsep} exp(-k_0/36) ) ) ,
        

        with C = layerSumConst free of k_0 in its 3^{2b(.)} factor. Against the printed display the only differences are the two recorded: the collapse exponent 1/36 in place of 1/4 (absorbed by relabelling c in the manuscript's own k_0 := c E^{-2} gamma^{-1}) and the absolute constant inflation geomSeriesInflation from the ratio change 3^{-3/4} |-> 3^{-1/4}.

        The hypothesis hεk0 : eps <= exp(-k_0) is the manuscript's selection k_0 := c E^{-2} gamma^{-1} read against the density constant.

        Instantiation at the proved Whitney carriers #

        l.bad.cubes.density at the layer quantity. The proved mass form Provider.Whitney.sum_cubeMassRatio_badFamilyLayer_le, with its threshold rewritten at k + h_k = layerQuantity and in the exponent convention that layerContrib_le consumes.

        The bridge to the proved e.hsep.tails #

        theorem Algsuperdiff.Section3.Provider.Multiscale.three_rpow_gamma_hsep_le_three_rpow_b_hsep {d : ℕ} {M : ABKModel d} {m : ℤ} {E b γ : ℝ} (hγb : γ ≤ b) (omega : Cutoff.CutoffSample d) :
        3 ^ (γ * ↑(Percolation.hsep M m E b omega)) ≤ 3 ^ (b * ↑(Percolation.hsep M m E b omega))

        This is the gamma <= b step.