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For $f\in L^1(\mathbb R^n),$ let $Mf$ be the (Edited: changed the type of maximal function) Stein spherical maximal function. Let $\varphi\in C_c^\infty.$ Then, can we have a pointwise estimate of the form

$$ |(\varphi \ast f)(x)| \leq C\|\varphi\|_{L^1} |Mf(x)|? $$

This is obviously true when $\varphi$ is symmetric decreasing. However, the general case is very hard.

Can we prove a general inequality of this form? We can, if necessary, replace $Mf$ with a different maximal function, or change the form of the inequality slightly.

Motivation: there are some related ideas in this post by Terry Tao: https://terrytao.wordpress.com/2011/05/21/steins-spherical-maximal-theorem/

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    $\begingroup$ No. If $\varphi(x)=f(-x)=\chi_{(n,n+1)}(x)$, then $(\varphi *f)(0)=\|\varphi\|_1=1$, but $(Mf)(0)\simeq 1/n$. $\endgroup$ Commented Jan 28 at 23:46
  • $\begingroup$ @ChristianRemling Thank you. Does spherical maximal function work, though? $\endgroup$
    – Ma Joad
    Commented Jan 29 at 10:39
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    $\begingroup$ The spherical (= symmetric) maximal function is what I had in mind. $\endgroup$ Commented Jan 29 at 18:06
  • $\begingroup$ When $n = 1$ what you are looking at holds essentially by accident. When $n \geq 2$ take $\varphi(x) = f(-x)$ to be the characteristic function of the ball of radius 1 centered at then point $(n,0,0,0,\ldots,0)$. Then even with the "spherical" maximal function this extension of Christian's counterexample works. $\endgroup$ Commented Jan 30 at 1:26
  • $\begingroup$ Incidentally, you probably don't want to consider the spherical maximal function anyway on $L^1(\mathbb{R})$, as it isn't even well-defined. (Take a random $L^1(\mathbb{R})$ function $f$, modify it so that $f(n) = |n|$; this new function differs only on a measure zero set from the original, so is still $L^1$. But at every point you find $Mf(x) = +\infty$.) $\endgroup$ Commented Jan 30 at 1:33

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For simplicity consider $f \in \mathcal{S}$. Fix $\psi\in C^\infty_c(\mathbb{R}^n,[0,\infty))$ with $\int \psi = 1$. Define $$ \varphi_{\epsilon,y}(x) = \epsilon^{-n}\psi( \epsilon^{-1}(x-y)) $$ so we have $\int\varphi_{\epsilon,y} = 1$ for every $y\in \mathbb{R}^n$ and $\epsilon > 0$.

If the desired inequality were to hold, you must have $$ |\varphi_{\epsilon,y}* f(x)| \lesssim |Mf(x)| $$ for your choice of maximal function $M$. Taking $\epsilon \searrow 0$ the LHS converges (as we are using an approximation to identity), and so we must have $$ |f(x+y)| \lesssim |Mf(x)| $$ uniformly for $y\in \mathbb{R}^n$. Taking the supremum in $y$ we find necessarily $$ \|f\|_\infty \lesssim |Mf(x)|. $$ In particular, we have that for any non-trivial function, $|Mf|$ is bounded below away from zero. As consequence, we can conclude that

  1. If $M$ is any maximal function that maps $L^p$ to itself boundedly, for some $1 \leq p < \infty$, then the desired inequality cannot hold.
  2. In fact, if there is some $p\in [1,\infty]$ and $q\in [1,\infty)$ such that $M$ sends all $L^p$ functions to $L^{q}_w$ (weak $L^q$) functions, then the desired inequality cannot hold.
  3. In a slightly different direction: if $M$ is any maximal function that maps $L^p$ to $L^\infty$ for some $1\leq p < \infty$, then the desired inequality cannot hold.

The astute reader will notice that the properties that appear in the hypotheses of the above three statements are the three quintessential properties of the Hardy-Littlewood Maximal function, and some subset thereof are often shared by what one consider to be "maximal functions".

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