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LeanPool.Superdiffusion.Algsuperdiff.Section3.Provider.Multiscale.BfaLocalLane

BfaLocalLane #

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

The local-descendant lane for p.bfA.multiscalebound #

ABK26 applies p.bfA.multiscalebound separately on every translated cube R = z + cu_n before invoking e.maxy.bound over the finite grid (especially). Consequently the random separation scale at R is not the root observable hsep M m E b omega: it is the origin observable at scale R.scale, read at the translated sample

hsep M R.scale E b
  (Cutoff.translateCutoffSample (triadicCubeShift R) omega).

This file records exactly that local lane. Stationarity transports the proved local Gamma_(bfaTau sigma gam b) bound from BfaPerCube without changing its amplitude. The subsequent finite-grid maximum is deliberately priced by the existing BlockPayload.isBigOWith_gammaSigma_blockGridSup; thus the e.maxy.bound cost gridBlockAmp ... k remains visible and is not replaced by an unsupported same-sample domination by the root hsep.

Scope of the payoff interface #

ConclusionRoot.abs_blockVecDot_coarseBlockMatrix_originCube_le_payload_ae is almost-everywhere and retains, as antecedents, nonemptiness of hsepSet, the wave envelope, and the potential/solenoidal competitor clauses. The final theorem here therefore only converts an already supplied a.e. conditional local Step-3 payoff into the constant-plus-lane form, preserving an explicit gate unchanged on both sides. It does not assert that the gate or payoff is satisfied, and it does not turn an a.e. conclusion into a pointwise one.

A producer from ConclusionRoot still requires the analytic competitor clauses, a uniform envelope, the quadratic-form-to-operator-norm bridge, and a simultaneous a.e. argument over the loadings (the cutoff indices are countable, but the unit sphere is not). None of those obligations is moved into a hypothesis of an unconditional theorem here.

Source #

The local lane and its deterministic hygiene #

noncomputable def Algsuperdiff.Section3.Provider.Multiscale.bfaLocalLane {d : ℕ} (M : ABKModel d) (R : HCPolySupport.TriadicCube d) (E b gam Cpre eps : ℝ) (omega : Cutoff.CutoffSample d) :

The p.bfA.multiscalebound random lane at a triadic cube R: the origin lane at scale R.scale, evaluated on the sample translated by the base point of R.

Equations
  • One or more equations did not get rendered due to their size.
Instances For
    theorem Algsuperdiff.Section3.Provider.Multiscale.bfaLocalLane_nonneg {d : ℕ} (M : ABKModel d) (R : HCPolySupport.TriadicCube d) {E b gam Cpre eps : ℝ} (hCpre : 0 ≤ Cpre) (heps : 0 ≤ eps) (omega : Cutoff.CutoffSample d) :
    0 ≤ bfaLocalLane M R E b gam Cpre eps omega

    Stationarity transport of the proved local BfaPerCube bound #

    Restrict the induction state to an earlier terminal scale. This is only the monotonicity already present in the frozen definition's two forall m <= m0 clauses.

    theorem Algsuperdiff.Section3.Provider.Multiscale.isBigOWith_gammaSigma_bfaLocalLane_of_localInduction_of_gates {d : ℕ} (M : ABKModel d) (R : HCPolySupport.TriadicCube d) {E sigma b gam Cpre eps : ℝ} (hd : 2 ≤ d) (hE : 1 ≤ E) (hS : Frozen.Section3.inductionState M (R.scale - 1) ⟨E, hE⟩) (hsigma0 : 0 < sigma) (hsigma : sigma ≤ 1 / 2) (hb0 : 0 < b) (hb1 : b ≤ 1 / 8) (hEexp : Real.exp (Percolation.badClustersConst d / sigma) ≤ E) (hE4 : 4 ≤ E) (hunit : BadEvents.unitGate M) (hgamma20 : M.gamma ≤ 1 / 20) (hinvSq : E⁻¹ ^ 2 ≤ Disorder.cstar M) (hEb : Percolation.badClustersConst d / b ≤ E) (hgammaE : M.gamma ≤ E ^ (-5)) (hgam : 0 < gam) (hgammab : gam ≤ b) (hCpre : 0 < Cpre) (heps : 0 < eps) :

    The same stationarity transport from the raw bad-event gates.

    theorem Algsuperdiff.Section3.Provider.Multiscale.isBigOWith_gammaSigma_bfaLocalLane_of_mem_descendantsAtScale_of_gates {d : ℕ} (M : ABKModel d) {m : ℤ} {k : ℕ} {R : HCPolySupport.TriadicCube d} (hR : R ∈ HCPolySupport.descendantsAtScale (HCPolySupport.originCube d m) (m - 1 - ↑k)) {E sigma b gam Cpre eps : ℝ} (hd : 2 ≤ d) (hE : 1 ≤ E) (hS : Frozen.Section3.inductionState M (m - 1) ⟨E, hE⟩) (hsigma0 : 0 < sigma) (hsigma : sigma ≤ 1 / 2) (hb0 : 0 < b) (hb1 : b ≤ 1 / 8) (hEexp : Real.exp (Percolation.badClustersConst d / sigma) ≤ E) (hE4 : 4 ≤ E) (hunit : BadEvents.unitGate M) (hgamma20 : M.gamma ≤ 1 / 20) (hinvSq : E⁻¹ ^ 2 ≤ Disorder.cstar M) (hEb : Percolation.badClustersConst d / b ≤ E) (hgammaE : M.gamma ≤ E ^ (-5)) (hgam : 0 < gam) (hgammab : gam ≤ b) (hCpre : 0 < Cpre) (heps : 0 < eps) :

    The descendant-grid local bound from the raw bad-event gates.

    The honest e.maxy.bound lift #

    noncomputable def Algsuperdiff.Section3.Provider.Multiscale.bfaLocalGridSup {d : ℕ} (M : ABKModel d) (m : ℤ) (k : ℕ) (E b gam Cpre eps : ℝ) (omega : Cutoff.CutoffSample d) :

    The finite descendant-grid maximum of the local lane.

    Equations
    • One or more equations did not get rendered due to their size.
    Instances For
      theorem Algsuperdiff.Section3.Provider.Multiscale.bfaLocalGridSup_nonneg {d : ℕ} (M : ABKModel d) (m : ℤ) (k : ℕ) (E b gam Cpre eps : ℝ) (omega : Cutoff.CutoffSample d) :
      0 ≤ bfaLocalGridSup M m k E b gam Cpre eps omega
      theorem Algsuperdiff.Section3.Provider.Multiscale.isBigOWith_gammaSigma_bfaLocalGridSup_of_gates {d : ℕ} (M : ABKModel d) {m : ℤ} (k : ℕ) {E sigma b gam Cpre eps : ℝ} (hd : 2 ≤ d) (hE : 1 ≤ E) (hS : Frozen.Section3.inductionState M (m - 1) ⟨E, hE⟩) (hsigma0 : 0 < sigma) (hsigma : sigma ≤ 1 / 2) (hb0 : 0 < b) (hb1 : b ≤ 1 / 8) (hEexp : Real.exp (Percolation.badClustersConst d / sigma) ≤ E) (hE4 : 4 ≤ E) (hunit : BadEvents.unitGate M) (hgamma20 : M.gamma ≤ 1 / 20) (hinvSq : E⁻¹ ^ 2 ≤ Disorder.cstar M) (hEb : Percolation.badClustersConst d / b ≤ E) (hgammaE : M.gamma ≤ E ^ (-5)) (hgam : 0 < gam) (hgammab : gam ≤ b) (hCpre : 0 < Cpre) (heps : 0 < eps) :

      The finite-grid maximum priced from the raw bad-event gates.

      A.e. conditional conversion of a local Step-3 payoff #