Coarse-graining support: Support.Book.Ch05.Theorems.Section57.UniformEllipticityEndpoint #
Imported from the Apache-2.0 CoarseGraining development at commit
c7ddd76c08ade64fed1b8d2ca51be14dfee8deb4.
The uniform ellipticity endpoint in Section 5.7 #
This file records the σ = ∞ endpoint of the quenched coarse-grained
ellipticity assumption. The endpoint is deliberately kept as a separate API:
it gives an a.s. unit-scale bound, and from that bound we may recover every
finite Γσ input needed by the existing concentration arguments.
The σ = ∞ endpoint of the quenched coarse-grained ellipticity
assumption.
The field bound is the Lean version of the uniform estimate
Γ_∞: the unit-cube ellipticity observable is bounded by thetaHat
almost surely.
- params : QuantitativeCoarseGrainedEllipticityParams d
Parameters specifying the coarse-grained upper and lower ellipticity observables.
- thetaHat : ℝ
Uniform almost-sure bound for the unit-cube coarse-grained ellipticity observable.
- bound : gammaSigmaUnitEllipticityObservable hP hStruct self.params.sUpper self.params.sLower ≤ᵐ[P] fun (x : RegCoeffField d) => self.thetaHat
Instances For
Manuscript-facing σ = ∞ endpoint of (P5), with no exposed moment
exponent xi.
- params : GammaCoarseGrainedEllipticityParams d
Parameters specifying the coarse-grained upper and lower ellipticity observables.
- thetaHat : ℝ
Uniform almost-sure bound for the unit-cube coarse-grained ellipticity observable.
- bound : gammaSigmaUnitEllipticityObservable hP hStruct self.params.sUpper self.params.sLower ≤ᵐ[P] fun (x : RegCoeffField d) => self.thetaHat
Instances For
Add the internal finite moment exponent used by the existing endpoint proof infrastructure.
Equations
- hInf.withInternalXi = { params := hInf.params.toQuantitativeParams, thetaHat := hInf.thetaHat, thetaHat_pos := ⋯, bound := ⋯ }
Instances For
Transfer an a.s. upper bound across equality in law.
A deterministic counterpart of the finite-Γσ scale-zero propagation:
an a.s. bound at the unit origin cube propagates to every larger origin cube.
Transfer an a.s. bound from the origin cube at scale n to a descendant
cube at the same scale, using stationarity.
An a.s. origin-cube bound controls the localized maximum over descendants.
The guarded unit-cube observable is nonnegative even before proving that
the normalizing scalar barσ_0 is positive.
A uniform unit-scale bound is, in particular, a finite Γσ tail for every
positive finite exponent σ.
Forget the endpoint input to any finite positive Γσ input.
Equations
Instances For
The endpoint implies the Chapter 5 quantitative coarse-grained ellipticity package, via any finite exponent.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The deterministic unit-scale constant for the endpoint normalized
J bound.
Equations
- One or more equations did not get rendered due to their size.
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Under the endpoint assumption, the limiting-normalized unit-cube J
observable is almost surely bounded by a deterministic multiple of
thetaHat^2.
The endpoint unit J bound propagates to every origin scale.
The endpoint controls every localized normalized finite-probe maximum by a
deterministic multiple of thetaHat^2.
The endpoint controls the localized scale-zero unit-ellipticity supremum
by a deterministic multiple of thetaHat^2.
Forget the endpoint input to any finite positive Γσ input, in the
manuscript-facing parameter package with no exposed moment exponent.
Equations
Instances For
Endpoint (σ = ∞) version of Corollary c.first.quenched.estimate.
In Lean the endpoint assumption is a separate structure. The conclusion is
obtained by applying the finite-σ corollary at σ = 2, which is exactly the
Γ_{σ ∧ 2} exponent when σ = ∞.