lemmaroutine
Square function bound for dilated vector kernels
Bounds square function of dilated vector kernels with only loss
handles different dilates in the square function proof
Lemma·
lem:square-dilates·§11 Stein's square functionStatement (paper)
Let be a Hilbert space, , , and
. Suppose is continuously differentiable and
Write , and let bound the norm
of from to , . For every finite
sequence of Schwartz functions ,
In plain English
For a Hilbert-space-valued kernel with decay and gradient bounds of size , , the vector-valued square function for dilates is bounded by a constant times . The constant is , where are the norms of , valid for and .
Why it's here
This lemma lets one apply a different dilate of the same operator to each and still control the result by the square function of the , with only a logarithmic loss in at . It is the tool in Stein's square function argument that handles shell pieces at scale and the smooth part away from the boundary, with explicit dependence on tracked through the term.
Classified routine:
A standard vector-valued Calderón–Zygmund / sharp-function interpolation argument for square functions of dilates, as in Seeger's and Carbery's work on Bochner–Riesz maximal functions. The explicit tracking of the log(1/δ) factor is bookkeeping on that known technique.
Uses
Nothing else in the paper
Used by
Sources
PaperOpen
- Section
- §11 Stein's square function
- Page
- —
- Label
lem:square-dilates- Line
sections/stein_square.tex:103
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