Documentation

LeanPool.AnomalousDiffusion.AVenhance.Infra.Section5.Integration.BigBound.Centered

Centering on the unit cube #

centerCell h = h - ⨍_{(0,1)²} h is the mean-zero part of an L² function on the unit cube. This generic API is used by the grouped mean-zero assembly of BigBoundInputs (the grouped mean-zero decomposition (12)–(18)): three terms (twistie4, twistie5, normie3) need not be individually mean zero, only their sum is; their centered versions are mean zero, are bounded in HDot⁻¹ through the L² estimate, and the centered family has the same pointwise sum as the original one.

h minus its mean over the unit cube.

Equations
Instances For

    The mean of a function over the unit cube is the integral (volume one).

    Centering is L²-nonexpansive: ‖h - ⨍ h‖² = ‖h‖² - (⨍ h)² ≤ ‖h‖².

    theorem AVenhance.Infra.Section5.Integration.sum_centerCell_eq_of_meanZero {ι : Type u_1} (s : Finset ι) (h : ι → Homogenization.Vec 2 → ℝ) (hint : ∀ i ∈ s, MeasureTheory.IntegrableOn (h i) unitCube MeasureTheory.volume) (hsum : Homogenization.MeanZeroOn unitCube fun (x : Homogenization.Vec 2) => ∑ i ∈ s, h i x) (x : Homogenization.Vec 2) :
    ∑ i ∈ s, centerCell (h i) x = ∑ i ∈ s, h i x

    Centering a finite family whose sum has mean zero does not change the sum.

    Centering preserves joint continuity on (0,1) × ℝ².