[Math] Hardy-Littlewood Maximal Function and Characteristic Functions

harmonic-analysisintegrationlebesgue-integralmeasure-theoryreal-analysis

For $f\in L^{1}_{\textrm{loc}}(\mathbb R),$ define the (centered) Hardy-Littlewood maximal function
$$
Mf(x)=\sup\limits_{r>0}\frac{1}{2r}\int_{-r}^{r}\vert f(x-t)\vert\,dt$$

for $x\in\mathbb R.
$

Fix real numbers $a<b$. Compute $M\text{$\bf1$}_{[a,b]}$ explicitly.

$\textbf{My Attempt & Ideas:}$ Writing down the definition, I have
$$
\begin{align*}M\text{$\bf1$}_{[a,b]}(x)
&=\sup\limits_{r>0}\frac{1}{2r}\int^{r}_{-r}\text{$\bf1$}_{[a,b]}(x-t)dt
=\sup\limits_{r>0}\frac{1}{2r}\int_{x-r}^{x+r}\text{$\bf1$}_{[a,b]}(t)dt\\&=\begin{cases}1&\text{if }x\in(a,b)\\\frac{b-a}{2(b-x)}&\text{if }x\leq a\\\frac{b-a}{2(x-a)}&\text{if }x\geq b\end{cases}\;.
\end{align*}$$

My reasoning for this is that if $x\in(a,b)$ I can choose $r$ such that $(x-r,x+r)\subset[a,b]$.

However, if $x<a$ then $(x-r,x+r)\not\subset(a,b)$ implies that $\int_{x-r}^{x+r}\text{$\bf1$}_{[a,b]}(t)dt=0,$ and if $(x-r,x+r)\subset(a,b)$, then the value of $r$ that gives the expression of the supremum is $r=b-x$ and similarly if $x>b$, the value that gives the supremum above is $r=x-a$.


I am not confident about my reasoning, as I am sure it is not rigorous enough. Any hints on how to proceed in a more precise manner or is the calculation above actually on the right track?

Any feedback is much appreciated.

Thank you for your time.

Best Answer

One may gain more insights by writing the maximal operator in a different way. By change of variable, $$ Mf(x)=\sup\limits_{r>0}A_r(f) $$ where $A_r(f)$ is the average of the function $|f|$ over the interval $B_x(r)=(x-r,x+r)$: $$ A_r(f)=\frac{1}{2r}\int_{x-r}^{x+r}\vert f(t)\vert\;dt\;. $$

One can then focus on the case $[a,b]=[0,1]$ since the general one is not very different.

When $f=1_{[0,1]}$, the average is given by $$ A_r(f)=\frac{|B_x(r)\cap (0,1)|}{|B_x(r)|}\tag{1} $$ namely, the ratio of the length of the intersection $B_x(r)\cap (0,1)$ and the length of $B_x(r)$. One can immediately see that this quantity is at most $1$.

To find the maximal value (1), it is helpful to draw a picture. There are several cases.

  • When $x\in(0,1)$, the average $A_r(f)$ achieves its maximal value $1$ whenever $B_x(r)\subset (0,1)$.

  • When $x=0$ or $x=1$, the length of $B_x(r)\cap (0,1)$ is at most a half of $B_x(r)$, which gives the maximal value of $A_r(f)$ as $\dfrac12$ in this case.

  • The cases when $x<0$ and $x>1$ are similar. Let us consider $x>1$. Again, drawing a picture will be very helpful.

    • If $r< x-1$, then the numerator in (1) is zero. So to achieve the maximum, we must have $r\ge x-1$.
    • On the other hand, if $r> x-0$, the numerator of (1) remains the same and the denominator will increase if one raises the value of $r$. So the maximal of $A_r(f)$ must be achieved for $x-1\leq r\leq x-0$. Explicitly, one can write $$ A_r(f) = \frac{r-(x-1)}{2r} = \frac{1}{2}-\frac{x-1}{2r},\quad r\in[x-0,x-1]\;, $$ which implies that the maximal is at $r=x-0$.
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