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The Mean Value of Locally Integrable Functions Converges to the Value of the Function at the Center. 📂Measure Theory

The Mean Value of Locally Integrable Functions Converges to the Value of the Function at the Center.

Theorem1

Let’s say fLloc1f \in L^1_{\mathrm{loc}}. Then, the following is true.

limr0Arf(x)=f(x) a.e. xRn \lim \limits_{r \rightarrow 0} A_{r} f(x)=f(x) \text{ a.e. } x\in \mathbb{R}^n

Here,  a.e. \text{ a.e. } is almost everywhere.

Description

The message here is that the limit of the average value of a locally integrable function’s value over the volume B(r,x)B(r,x) as the radius goes to 00 equals the function value at the center of the volume.

Proof

Since we take the limit as the radius of the volume goes to 00, it suffices to show the following equation for some NNN \in \mathbb{N}.

Arf(x)f(x) a.e. xN A_{r}f(x) \rightarrow f(x) \text{ a.e. } |x|\le N

For the same reason, we only need to consider the case when r<1r<1. Then, as shown in the figure below, xN|x| \le N and when r<1r<1, Arf(x)=1m(Br(x))Br(x)f(y)dyA_{r} f(x)=\frac{1}{m\big( B_{r}(x) \big)}{\displaystyle \int_{B_{r}(x)}} f(y)dy is determined only by yN+1|y|\le N+1, which are f(y)f(y). Therefore, it is harmless to replace ff with fχB(N+1,x)f\chi_{B(N+1,x)} and assume fL1f\in L^1.

5DAEB3081.png

Lemma

Let’s say fL1(m)f \in L^1(m) and ϵ>0\epsilon>0. Then, there exists a simple function ϕ=1NajχRj\phi=\sum\nolimits_{1}^Na_{j}\chi_{R_{j}} that satisfies the following condition.

fϕ<ϵ \int |f-\phi| <\epsilon

Moreover, there exists a continuous function gg whose function values are 00 outside a bounded set that satisfies the following condition.

fg<ϵ \int |f-g| <\epsilon

mm is Lebesgue measure.

Now, assume that ϵ>0\epsilon>0 is given. Then, since fL1f \in L^1, according to the lemma, a continuous integrable function gg exists that satisfies the following condition.

g(y)f(y)dy<ϵ \int |g(y)-f(y)|dy < \epsilon

Moreover, since gg is continuous, there exists r>0r>0 that satisfies the following condition for all xRnx\in \mathbb{R}^n, δ>0\delta >0.

yx<r    g(y)g(x)<δ |y-x|<r \implies |g(y)-g(x)| < \delta

Moreover, since 1m(B(r,x))B(r,x)dy=1\frac{1}{m \big( B(r,x)\big)} {\displaystyle \int_{B(r,x)} }dy=1, whenever yx<r|y-x|<r, the following holds.

Arg(x)g(x)=1m(B(r,x))B(r,x)g(y)dyg(x)=1m(B(r,x))B(r,x)g(y)dy1m(B(r,x))B(r,x)g(x)dy1m(B(r,x))B(r,x)g(y)g(x)dy1m(B(r,x))B(r,x)δdy=δ1m(B(r,x))B(r,x)dy=δ \begin{align*} |A_{r} g(x)-g(x)| &= \left| \frac{1}{m\big( B(r,x)\big)}\int_{B(r,x)}g(y)dy -g(x) \right| \\ &= \left| \frac{1}{m\big( B(r,x)\big)}\int_{B(r,x)}g(y)dy -\frac{1}{m\big( B(r,x)\big)}\int_{B(r,x)}g(x)dy \right| \\ &\le \frac{1}{m\big( B(r,x)\big)}\int_{B(r,x)}|g(y)-g(x)|dy \\ &\le \frac{1}{m\big( B(r,x)\big)}\int_{B(r,x)} \delta dy \\ &= \delta\frac{1}{m\big( B(r,x)\big)}\int_{B(r,x)} dy \\ &= \delta \end{align*}

Therefore, limr0Arg(x)g(x)=0\lim \limits_{r \rightarrow 0} |A_{r} g(x) -g(x)|=0. By the triangle inequality, the following is true.

lim supr0Arf(x)f(x)lim supr0(Arf(x)Arg(x)+Arg(x)g(x)+g(x)f(x))= lim supr0H(fg)(x)+g(x)f(x) \begin{equation} \begin{aligned} & \limsup \limits_{r\rightarrow 0} |A_{r}f(x)-f(x)| \\ \le& \limsup \limits_{r\rightarrow 0} \Big( |A_{r}f(x)-A_{r} g(x)|+|A_{r}g(x)-g(x)|+|g(x)-f(x)| \Big) \\ =&\ \limsup \limits_{r\rightarrow 0} H(f-g)(x)+ |g(x)-f(x)| \end{aligned} \end{equation}

Now, let’s consider EαE_\alpha, FαF_\alpha as follows.

Eα={x : lim supr0Arf(x)f(x)>α}Fα={x : gf(x)>α} E_\alpha =\left\{ x\ :\ \limsup\limits_{r \rightarrow 0} |A_{r} f(x)-f(x) | > \alpha \right\} \\ F_\alpha =\left\{ x\ :\ |g-f |(x) > \alpha \right\}

Then, by (1)(1), the following is true.

Eα(Fα/2{x : H(fg)(x)>α/2}) E_\alpha \subset \Big( F_{\alpha /2} \cup \left\{ x\ :\ H(f-g)(x) >\alpha /2\right\} \Big)

If an element belongs to EαE_\alpha, it must belong to either Fα/2F_{\alpha/2} or {x : H(fg)(x)>α/2}\left\{x\ :\ H(f-g)(x)>\alpha/2 \right\}. Therefore, the following holds.

m(Eα)m(Fα/2)+m({x : H(fg)(x)>α/2}) m(E_\alpha) \le m(F_{\alpha/2}) + m\Big( \left\{ x\ :\ H(f-g)(x)>\alpha/2\right\}\Big)

Moreover, by the definition of Fα/2F_{\alpha /2}, the following is true.

m(Fα/2)α2Fα/2gf(x)dx<ϵ    m(Fα/2)<2ϵα \begin{align*} && m(F_{\alpha /2}) \frac{\alpha}{2} & \le \int_{F_{\alpha /2}}|g-f|(x)dx < \epsilon \\ \implies && m(F_{\alpha/2}) &< \frac{2\epsilon}{\alpha} \end{align*}

Moreover, according to the Maximal Theorem, the following is true.

m({x : H(fg)(x)>α/2})2Cαgf(x)dx2Cϵα m\Big( \left\{ x\ :\ H(f-g)(x) > \alpha/2 \right\} \Big) \le \frac{2C}{\alpha} \int|g-f|(x)dx \le \frac{2C\epsilon}{\alpha}

Therefore, we obtain the following result.

m(Eα)2ϵα+2Cϵα=(2(1+C)α)ϵ m(E_\alpha) \le \frac{2\epsilon}{\alpha}+\frac{2C\epsilon}{\alpha}=\left( \frac{2(1+C)}{\alpha}\right)\epsilon

Since this holds for every ϵ>0\epsilon>0, we obtain the following.

m(Eα)=0 m( E_\alpha)=0

limrRϕ(r)=c    lim suprRϕ(r)c=0 \lim \limits_{r\rightarrow R}\phi (r)=c \iff \limsup \limits_{r\rightarrow R}|\phi (r)-c|=0

Therefore, for a.e.\mathrm{a.e.} xRnx\in\mathbb{R}^n, we obtain the following.

lim supr0Arf(x)f(x)=0    limr0Arf(x)=f(x) \begin{align*} && \limsup \limits_{r\rightarrow 0} |A_{r} f(x)-f(x)| &= 0 \\ \implies && \lim \limits_{r \rightarrow 0}A_{r}f(x) &= f(x) \end{align*}


  1. Gerald B. Folland, Real Analysis: Modern Techniques and Their Applications (2nd Edition, 1999), p97 ↩︎