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. Theorem Let’s say f ∈ L l o c 1 f \in L^1_{\mathrm{loc}} f ∈ L loc 1 . Then, the following is true.
lim r → 0 A r f ( x ) = f ( x ) a.e. x ∈ R n
\lim \limits_{r \rightarrow 0} A_{r} f(x)=f(x) \text{ a.e. } x\in \mathbb{R}^n
r → 0 lim A r f ( x ) = f ( x ) a.e. x ∈ R n
Here, a.e. \text{ a.e. } 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) B ( r , x ) as the radius goes to 0 0 0 equals the function value at the center of the volume.
Proof Since we take the limit as the radius of the volume goes to 0 0 0 , it suffices to show the following equation for some N ∈ N N \in \mathbb{N} N ∈ N .
A r f ( x ) → f ( x ) a.e. ∣ x ∣ ≤ N
A_{r}f(x) \rightarrow f(x) \text{ a.e. } |x|\le N
A r f ( x ) → f ( x ) a.e. ∣ x ∣ ≤ N
For the same reason, we only need to consider the case when r < 1 r<1 r < 1 . Then, as shown in the figure below, ∣ x ∣ ≤ N |x| \le N ∣ x ∣ ≤ N and when r < 1 r<1 r < 1 , A r f ( x ) = 1 m ( B r ( x ) ) ∫ B r ( x ) f ( y ) d y A_{r} f(x)=\frac{1}{m\big( B_{r}(x) \big)}{\displaystyle \int_{B_{r}(x)}} f(y)dy A r f ( x ) = m ( B r ( x ) ) 1 ∫ B r ( x ) f ( y ) d y is determined only by ∣ y ∣ ≤ N + 1 |y|\le N+1 ∣ y ∣ ≤ N + 1 , which are f ( y ) f(y) f ( y ) . Therefore, it is harmless to replace f f f with f χ B ( N + 1 , x ) f\chi_{B(N+1,x)} f χ B ( N + 1 , x ) and assume f ∈ L 1 f\in L^1 f ∈ L 1 .
Lemma
Let’s say f ∈ L 1 ( m ) f \in L^1(m) f ∈ L 1 ( m ) and ϵ > 0 \epsilon>0 ϵ > 0 . Then, there exists a simple function ϕ = ∑ 1 N a j χ R j \phi=\sum\nolimits_{1}^Na_{j}\chi_{R_{j}} ϕ = ∑ 1 N a j χ R j that satisfies the following condition.
∫ ∣ f − ϕ ∣ < ϵ
\int |f-\phi| <\epsilon
∫ ∣ f − ϕ ∣ < ϵ
Moreover, there exists a continuous function g g g whose function values are 0 0 0 outside a bounded set that satisfies the following condition.
∫ ∣ f − g ∣ < ϵ
\int |f-g| <\epsilon
∫ ∣ f − g ∣ < ϵ
m m m is Lebesgue measure .
Now, assume that ϵ > 0 \epsilon>0 ϵ > 0 is given. Then, since f ∈ L 1 f \in L^1 f ∈ L 1 , according to the lemma, a continuous integrable function g g g exists that satisfies the following condition.
∫ ∣ g ( y ) − f ( y ) ∣ d y < ϵ
\int |g(y)-f(y)|dy < \epsilon
∫ ∣ g ( y ) − f ( y ) ∣ d y < ϵ
Moreover, since g g g is continuous, there exists r > 0 r>0 r > 0 that satisfies the following condition for all x ∈ R n x\in \mathbb{R}^n x ∈ R n , δ > 0 \delta >0 δ > 0 .
∣ y − x ∣ < r ⟹ ∣ g ( y ) − g ( x ) ∣ < δ
|y-x|<r \implies |g(y)-g(x)| < \delta
∣ y − x ∣ < r ⟹ ∣ g ( y ) − g ( x ) ∣ < δ
Moreover, since 1 m ( B ( r , x ) ) ∫ B ( r , x ) d y = 1 \frac{1}{m \big( B(r,x)\big)} {\displaystyle \int_{B(r,x)} }dy=1 m ( B ( r , x ) ) 1 ∫ B ( r , x ) d y = 1 , whenever ∣ y − x ∣ < r |y-x|<r ∣ y − x ∣ < r , the following holds.
∣ A r g ( x ) − g ( x ) ∣ = ∣ 1 m ( B ( r , x ) ) ∫ B ( r , x ) g ( y ) d y − g ( x ) ∣ = ∣ 1 m ( B ( r , x ) ) ∫ B ( r , x ) g ( y ) d y − 1 m ( B ( r , x ) ) ∫ B ( r , x ) g ( x ) d y ∣ ≤ 1 m ( B ( r , x ) ) ∫ B ( r , x ) ∣ g ( y ) − g ( x ) ∣ d y ≤ 1 m ( B ( r , x ) ) ∫ B ( r , x ) δ d y = δ 1 m ( B ( r , x ) ) ∫ B ( r , x ) d y = 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*}
∣ A r g ( x ) − g ( x ) ∣ = m ( B ( r , x ) ) 1 ∫ B ( r , x ) g ( y ) d y − g ( x ) = m ( B ( r , x ) ) 1 ∫ B ( r , x ) g ( y ) d y − m ( B ( r , x ) ) 1 ∫ B ( r , x ) g ( x ) d y ≤ m ( B ( r , x ) ) 1 ∫ B ( r , x ) ∣ g ( y ) − g ( x ) ∣ d y ≤ m ( B ( r , x ) ) 1 ∫ B ( r , x ) δ d y = δ m ( B ( r , x ) ) 1 ∫ B ( r , x ) d y = δ
Therefore, lim r → 0 ∣ A r g ( x ) − g ( x ) ∣ = 0 \lim \limits_{r \rightarrow 0} |A_{r} g(x) -g(x)|=0 r → 0 lim ∣ A r g ( x ) − g ( x ) ∣ = 0 . By the triangle inequality, the following is true.
lim sup r → 0 ∣ A r f ( x ) − f ( x ) ∣ ≤ lim sup r → 0 ( ∣ A r f ( x ) − A r g ( x ) ∣ + ∣ A r g ( x ) − g ( x ) ∣ + ∣ g ( x ) − f ( x ) ∣ ) = lim sup r → 0 H ( f − g ) ( 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}
≤ = r → 0 lim sup ∣ A r f ( x ) − f ( x ) ∣ r → 0 lim sup ( ∣ A r f ( x ) − A r g ( x ) ∣ + ∣ A r g ( x ) − g ( x ) ∣ + ∣ g ( x ) − f ( x ) ∣ ) r → 0 lim sup H ( f − g ) ( x ) + ∣ g ( x ) − f ( x ) ∣
Now, let’s consider E α E_\alpha E α , F α F_\alpha F α as follows.
E α = { x : lim sup r → 0 ∣ A r f ( x ) − f ( x ) ∣ > α } F α = { x : ∣ g − f ∣ ( 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\}
E α = { x : r → 0 lim sup ∣ A r f ( x ) − f ( x ) ∣ > α } F α = { x : ∣ g − f ∣ ( x ) > α }
Then, by ( 1 ) (1) ( 1 ) , the following is true.
E α ⊂ ( F α / 2 ∪ { x : H ( f − g ) ( x ) > α / 2 } )
E_\alpha \subset \Big( F_{\alpha /2} \cup \left\{ x\ :\ H(f-g)(x) >\alpha /2\right\} \Big)
E α ⊂ ( F α /2 ∪ { x : H ( f − g ) ( x ) > α /2 } )
If an element belongs to E α E_\alpha E α , it must belong to either F α / 2 F_{\alpha/2} F α /2 or { x : H ( f − g ) ( x ) > α / 2 } \left\{x\ :\ H(f-g)(x)>\alpha/2 \right\} { x : H ( f − g ) ( x ) > α /2 } . Therefore, the following holds.
m ( E α ) ≤ m ( F α / 2 ) + m ( { x : H ( f − g ) ( x ) > α / 2 } )
m(E_\alpha) \le m(F_{\alpha/2}) + m\Big( \left\{ x\ :\ H(f-g)(x)>\alpha/2\right\}\Big)
m ( E α ) ≤ m ( F α /2 ) + m ( { x : H ( f − g ) ( x ) > α /2 } )
Moreover, by the definition of F α / 2 F_{\alpha /2} F α /2 , the following is true.
m ( F α / 2 ) α 2 ≤ ∫ F α / 2 ∣ g − f ∣ ( x ) d x < ϵ ⟹ m ( F α / 2 ) < 2 ϵ α
\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*}
⟹ m ( F α /2 ) 2 α m ( F α /2 ) ≤ ∫ F α /2 ∣ g − f ∣ ( x ) d x < ϵ < α 2 ϵ
Moreover, according to the Maximal Theorem , the following is true.
m ( { x : H ( f − g ) ( x ) > α / 2 } ) ≤ 2 C α ∫ ∣ g − f ∣ ( x ) d x ≤ 2 C ϵ α
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}
m ( { x : H ( f − g ) ( x ) > α /2 } ) ≤ α 2 C ∫ ∣ g − f ∣ ( x ) d x ≤ α 2 C ϵ
Therefore, we obtain the following result.
m ( E α ) ≤ 2 ϵ α + 2 C ϵ α = ( 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
m ( E α ) ≤ α 2 ϵ + α 2 C ϵ = ( α 2 ( 1 + C ) ) ϵ
Since this holds for every ϵ > 0 \epsilon>0 ϵ > 0 , we obtain the following.
m ( E α ) = 0
m( E_\alpha)=0
m ( E α ) = 0
lim r → R ϕ ( r ) = c ⟺ lim sup r → R ∣ ϕ ( r ) − c ∣ = 0
\lim \limits_{r\rightarrow R}\phi (r)=c \iff \limsup \limits_{r\rightarrow R}|\phi (r)-c|=0
r → R lim ϕ ( r ) = c ⟺ r → R lim sup ∣ ϕ ( r ) − c ∣ = 0
Therefore, for a . e . \mathrm{a.e.} a.e. x ∈ R n x\in\mathbb{R}^n x ∈ R n , we obtain the following.
lim sup r → 0 ∣ A r f ( x ) − f ( x ) ∣ = 0 ⟹ lim r → 0 A r f ( 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*}
⟹ r → 0 lim sup ∣ A r f ( x ) − f ( x ) ∣ r → 0 lim A r f ( x ) = 0 = f ( x )
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