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\documentclass [../script.tex] { subfiles}
%! TEX root = ../../script.tex
\begin { document}
\section { Limits and Functions}
In this chapter we will introduce the notation
\[
\oball (x) = (x - \epsilon , x + \epsilon )
\]
\begin { defi}
Let $ D \subset \realn $ and $ x \in \realn $ . $ x $ is called a boundary point of $ D $ if
\[
\forall \epsilon > 0: ~~D \cap \oball (x) \ne 0
\]
The set of all boundary points of $ D $ is called closure and is denoted as $ \closure { D } $ .
\end { defi}
\begin { eg}
\begin { enumerate} [(i)]
\item $ x \in D $ is always a boundary point of $ D $ , because
\[
x \in D \cap \oball (x)
\]
\item Boundary points don't have to be elements of $ D $ . If $ D = ( 0 , 1 ) $ , then $ 0 $ and $ 1 $ are boundary points, because
\[
\frac { \epsilon } { 2} \in (0, 1) \cap \oball (0) = (-\epsilon , \epsilon ) ~~\forall \epsilon > 0
\]
\item Let $ D = \ratn $ . Every $ x \in \realn $ is a boundary point, because $ \forall \epsilon > 0 $ , $ \oball ( x ) $ contains at least one rational number. I.e. $ \closure { \ratn } = \realn $ .
\end { enumerate}
\end { eg}
\begin { rem}
If $ x $ is a boundary point, then
\[
\forall \epsilon > 0 ~\exists y \in D: ~~|x - y| < \epsilon
\]
If $ x $ is not a boundary point, then
\[
\exists \epsilon > 0 ~\forall y \in D: ~~|x - y| \ge \epsilon
\]
\end { rem}
\begin { thm}
\[
x \in \realn \text { is a boundary point of } D \subset \realn \iff \exists \anyseqdef { D} \text { such that } x_ n \rightarrow x
\]
\end { thm}
2021-03-25 17:55:20 +00:00
\begin { proof}
Let $ x $ be a boundary point of $ D $ . Then
\begin { equation}
\forall n \in \natn ~\exists x_ n \in D \cap \left ( x - \frac { 1} { n} , x+ \frac { 1} { n} \right )
\end { equation}
The resulting sequence $ \seq { x } $ is in $ D $ , and
\begin { equation}
|x - x_ n| \le \frac { 1} { n}
\end { equation}
holds. Therefore, $ x _ n $ converges to $ x $ . Now let $ \anyseqdef { D } $ , with $ x _ n \rightarrow x $ . This means
\begin { equation}
\forall \epsilon > 0 ~\exists N \in \natn : ~~|x - x_ N| < \epsilon
\end { equation}
Then
\begin { equation}
x_ N \in D \cap \oball (x)
\end { equation}
Since $ \epsilon $ is arbitrary, $ x $ is a boundary point of $ D $ .
\end { proof}
\begin { defi}
Let $ D \subset \realn $ and $ f: D \rightarrow \realn $ . Let $ x _ 0 $ be a boundary point of $ D $ .
We say that $ f $ converges to $ y \in \realn $ for $ x \rightarrow x _ 0 $ and write
\[
\lim _ { x \rightarrow x_ 0} f(x) = y
\]
if
\[
\forall \epsilon > 0 ~\exists \delta > 0: ~~|x-x_ 0| < \delta \implies |f(x) - f(y)| < \epsilon
\]
\end { defi}
\begin { rem}
This definition only makes sense for boundary points $ x _ 0 $ of $ D $ . The most imoprtant case is
\[
D = (x_ 0 - a, x_ 0 + a) \setminus \set { x_ 0}
\]
\end { rem}
\begin { eg}
\begin { enumerate} [(i)]
\item Let $ a \in \realn $
\begin { align*}
f: \realn & \longrightarrow \realn \\
x & \longmapsto ax
\end { align*}
Consider $ a \ne 0 $ : Let $ \epsilon > 0 $ . We want that
\[
|f(x) - 0| = |a||x| \stackrel { !} { <} \epsilon
\]
Choose $ \delta = \frac { \epsilon } { |a| } $ . Then we have
\[
|x| = |x - 0| < \delta \implies |f(x) - 0| = |a||x| < |a| \delta = |a| \frac { \epsilon } { |a|} = \epsilon
\]
Therefore
\[
\lim _ { x \rightarrow 0} f(x) = 0
\]
\item Consider
\begin { align*}
f: \realn & \longrightarrow \realn \\
x & \longmapsto \begin { cases}
1 ,& x > 0 \\
-1 ,& x < 0 \\
\end { cases}
\end { align*}
$ f $ doesn't converge for $ x \rightarrow 0 $ . Assume $ y \in \realn $ is the limit of $ x $ at $ 0 $ . This means that there is a $ \delta > 0 $ such that
\[
|f(x) - y| < 1 \text { if } |x| = |x - 0| < \delta
\]
Then, for any $ x \in ( 0 , \delta ) $ we have
\[
2 = |f(x) - f(-x)| \le \underbrace { |f(x) - y|} _ { < 1} + \underbrace { |y - f(-x)|} _ { < 1} < 2
\]
which is a contradiction.
\end { enumerate}
\end { eg}
\begin { thm}
Let $ f: D \rightarrow \realn $ , $ x _ 0 $ a boundary point of $ D $ and $ y \in \realn $ . Then
\[
\lim _ { x \rightarrow x_ 0} f(x) = y \iff \forall \anyseqdef { D} \text { with } x_ n \longrightarrow x_ 0: ~~\limn f(x_ n) = x_ 0
\]
\end { thm}
\begin { proof}
Assume that $ \lim _ { x \rightarrow x _ 0 } f ( x ) $ and that there is $ \anyseqdef { D } $ converging to $ x $ .
Let $ \epsilon > 0 $ , then
\begin { equation}
\exists \delta > 0: ~~|x - x_ 0| < \delta \implies |f(x) - y| < \epsilon
\end { equation}
Since $ x _ n \rightarrow x _ 0 $ , we know that
\begin { equation}
\exists N \in \natn ~\forall n > N: ~~|x_ n - x_ 0| < \delta
\end { equation}
For such $ n $ , the epsilon criterion $ |f ( x _ n ) - y| < \epsilon $ also holds, and thus
\begin { equation}
f(x_ n) \convinf y
\end { equation}
Now to prove the "$ \impliedby $ " direction, assume that $ \lim _ { x \rightarrow x _ 0 } f ( x ) \ne y $ , i.e.
\begin { equation}
\exists \epsilon > 0 ~\forall \delta > 0 ~\exists x \in D: ~~|x - x_ 0| < \delta \wedge |f(x) - y| \ge \epsilon
\end { equation}
Choose $ \forall x \in \natn $ one $ x _ n $ such that
\begin { equation}
|x_ n - x_ 0| < \frac { 1} { n} \text { but } |f(x_ n) - y| \ge \epsilon
\end { equation}
Then $ x _ n \rightarrow x _ 0 $ , but $ |f ( x _ n ) - y| \ge \epsilon ~ \forall n \in \natn $ , so
\begin { equation}
\limn f(x_ n) \ne y
\end { equation}
This indirectly proves "$ \impliedby $ ".
\end { proof}
\begin { eg}
Consider $ D = \realn \subset \set { 0 } $ , we want to prove
\[
\lim _ { x \rightarrow 0} \frac { 1} { 1-x} = 1
\]
So let $ \anyseqdef { D } $ with $ x _ n \rightarrow 0 $ . Then
\[
\frac { 1} { 1-x_ n} \convinf 1
\]
\[
\implies \lim _ { x \rightarrow 0} \frac { 1} { 1-x} = 1
\]
However, the limit $ \lim _ { x \rightarrow 1 } $ doesn't exist. Let $ x _ n = \frac { 1 } { n } + 1 $ with $ x _ n \rightarrow 1 $ . Then
\[
\frac { 1} { 1 - (\frac { 1} { n} + 1)} = -n \convinf -\infty
\]
This doesn't converge, thus there is no limit.
\end { eg}
\begin { cor}
Let $ f, g: D \rightarrow \realn $ , $ x _ 0 $ a boundary point and $ y, z \in \realn $ such that
\begin { align*}
\lim _ { x \rightarrow x_ 0} f(x) = y & & \lim _ { x \rightarrow x_ 0} g(x) = z
\end { align*}
Then
\begin { align*}
\lim _ { x \rightarrow x_ 0} (f(x) + g(x)) & = y+z \\
\lim _ { x \rightarrow x_ 0} (f(x) \cdot g(x)) & = y \cdot z
\end { align*}
If $ z \ne 0 $ , then
\[
\lim _ { x \rightarrow x_ 0} (\frac { f(x)} { g(x)} ) = \frac { y} { z}
\]
\end { cor}
\begin { proof}
Here we will only prove the last statement.
Let $ \lim _ { x \rightarrow x _ 0 } = z \ne 0 $ . Then
\begin { equation}
\exists \delta > 0 ~\forall x \in \oball [\delta] (x_ 0): ~~|g(x) - z| < |z|
\end { equation}
$ g $ doesn't have any roots on $ \oball [ \delta ] ( x _ 0 ) $ . Let $ \anyseqdef { D \cap \oball [ \delta ] ( x _ 0 ) } $ converge to $ x _ 0 $ .
According to prerequisites, we have
\noindent \begin { subequations}
\begin { multicols} { 2}
\noindent
\begin { equation}
\limn f(x_ n) = y
\end { equation}
\begin { equation}
\limn g(x_ n) = z \ne 0
\end { equation}
\end { multicols}
\end { subequations}
\noindent Thus
\begin { equation}
\implies \limn \frac { f(x_ n)} { g(x_ n)} = \frac { y} { z} \implies \lim _ { x \rightarrow x_ 0} \frac { f(x)} { g(x)} = \frac { y} { z}
\end { equation}
\end { proof}
\begin { cor} [Squeeze Theorem]
Let $ f, g, h: D \rightarrow \realn $ and $ x $ a boundary point of $ D $ . If for $ y \in \realn $
\[
\lim _ { x \rightarrow x_ 0} f(x) = y = \lim _ { x \rightarrow x_ 0} h(x)
\]
and
\[
f(x) \le g(x) \le h(x) ~~\forall x \in \oball (x_ 0)
\]
then
\[
\lim _ { x \rightarrow x_ 0} g(x) = y
\]
\end { cor}
\begin { eg}
Consider $ \exp ( x ) $ . We already know that
\[
1 + x \le \exp (x) ~~\forall x \in \realn
\]
This also implies that
\[
1 - x \le \exp (-x) = \frac { 1} { \exp (x)} ~~\forall x \in \realn
\]
So
\[
1 + x \le \exp (x) \le \frac { 1} { 1 - x}
\]
The limits of these terms are
\begin { align*}
\lim _ { x \rightarrow 0} (1+x) = 1 & & \lim _ { x \rightarrow 0} \left (\frac { 1} { 1-x} \right ) = 1
\end { align*}
And using the squeeze theorem this results in
\[
\lim _ { x \rightarrow 0} \exp (0) = 1
\]
\end { eg}
\begin { defi}
Let $ f: D \rightarrow \realn $ and $ x _ 0 $ a boundary point of $ D $ . We say $ f $ diverges to infinity for $ x \rightarrow x _ 0 $ and write
\[
\lim _ { x \rightarrow x_ 0} f(x) = \infty
\]
if
\[
\forall K \in (0, \infty ) ~\exists \delta > 0: ~~|x - x_ 0| < \delta \implies f(x) \ge K
\]
\end { defi}
\begin { defi}
Let $ D \subset \realn $ be unbounded above. We say $ f $ converges for $ x \rightarrow \infty $ to $ y \in \realn $ and write
\[
\lim _ { x \rightarrow \infty } f(x) = y
\]
if
\[
\forall \epsilon > 0 ~\exists K \in (0, \infty ) ~\forall x > K: ~~|f(x) - y| < \epsilon
\]
\end { defi}
\begin { rem}
Let $ f: D \rightarrow \cmpln $ and $ x _ 0 $ a boundary point of $ D $ . Then
\begin { align*}
& \limes { x} { x_ 0} f(x) = y \in \cmpln \\
\iff & \limes { x} { x_ 0} \Re (f(x)) = \Re (y) \wedge \limes { x} { x_ 0} \Im (f(x)) = \Im (y) \\
\iff & \limes { x} { x_ 0} |f(x) - y| = 0
\end { align*}
\end { rem}
\begin { defi}
Let $ D \subset K $ , $ f:D \rightarrow K $ and $ x _ 0 \in D $ . $ f $ is called continuous in $ x _ 0 $ if
\[
\forall \epsilon > 0 ~\exists \delta > 0: ~~|x - x_ 0| < \delta \implies |f(x) - f(x_ 0)| < \epsilon
\]
If $ f $ is continuous in every point of $ D $ , we call $ f $ continuous.
$ f $ is called Lipschitz
continuous if
\[
\exists L \in (0, \infty ) ~\forall x, y \in D: ~~|f(x) - f(y)| \le L|x - y|
\]
$ L $ is called Lipschitz constant
\end { defi}
\begin { rem}
Let $ f: D \rightarrow \field $
\[
f \text { is continuous in } x_ 0 \in D \iff \limes { x} { x_ 0} f(x) = f(x_ 0)
\]
\end { rem}
\begin { eg}
We want to show that
\begin { align*}
f: \realn & \longrightarrow \realn \\
x & \longmapsto x^ 2
\end { align*}
is continuous. To do that, let $ x _ 0 \in \realn $ , $ \epsilon > 0 $ . We want
\[
|f(x) - f(x_ 0)| = |x^ 2 - x_ 0^ 2| = |x - x_ 0||x + x_ 0| \must [\le] \epsilon
\]
So we choose
\[
\delta = \min \set { 1, \frac { \epsilon } { 2|x_ 0| + 1} } > 0
\]
Then for every $ x $ with $ |x - x _ 0 | < \delta $
\begin { align*}
|f(x) - f(x_ 0)| & = |x - x_ 0||x + x_ 0| \le \delta (|x| + |x_ 0|) \le \delta (|x_ 0| + \delta + |x_ 0|) \\
& \le \delta (2|x_ 0| + 1) \le \frac { \epsilon } { 2|x_ 0| + 1} (2|x_ 0| + 1) = \epsilon
\end { align*}
\end { eg}
\begin { thm}
Every Lipschitz continuous function is continuous
\end { thm}
\begin { proof}
Let $ f: D \rightarrow \field $ be a Lipschitz continuous function with Lipschitz constant $ L > 0 $ . I.e.
\begin { equation}
\forall x, y \in D: ~~|f(x) - f(y)| \le L|x - y|
\end { equation}
Let $ x _ 0 \in \realn $ and $ \epsilon > 0 $ . Choose $ \delta = \frac { \epsilon } { L } $ . Then $ |x - x _ 0 | < \delta $ implies
\begin { equation}
|f(x) - f(x_ 0)| \le L|x - x_ 0| \le L \cdot \delta = \epsilon
\end { equation}
\end { proof}
\begin { eg}
\begin { enumerate} [(i)]
\item Consider the constant function $ x \mapsto c $ , $ c \in \field $ .
\[
|f(x) - f(y)| = |c - c| = 0 \le 1 \cdot |x - y|
\]
\item Consider the linear function $ x \mapsto cx $ , $ c \in \field $ .
\[
|f(x) - f(y)| = |cx - cy| = |c||x - y|
\]
\end { enumerate}
These two functions are Lipschitz continuous, and therefore continuous.
\begin { enumerate} [(i)]\setcounter { enumi} { 2}
\item Consider $ x \mapsto \Re ( x ) $ . Then
\[
|\Re (x) - \Re (y)| = |\Re (x - y)| \le |x - y|
\]
Analogously this works for $ \Im ( x ) $ . Both of those are Lipschitz continuous.
\item Lipschitz continuity depends on $ D $ . E.g.
\begin { align*}
f: [0, 1] & \longrightarrow \realn \\
x & \longmapsto x^ 2
\end { align*}
is Lipschitz continuous:
\[
|f(x) - f(y)| = |x-y||x+y| \le 2 \cdot |x - y|
\]
However,
\begin { align*}
g: \realn & \longrightarrow \realn \\
x & \longmapsto x^ 2
\end { align*}
is NOT Lipschitz continuous, because
\[
\frac { |g(n+1) - g(n)|} { (n+1) - n} = 2n + 1 \convinf \infty
\]
\end { enumerate}
\end { eg}
\begin { rem}
Let $ f: D \rightarrow \field $ .
\begin { gather*}
f \text { is continuous in } x_ 0 \in D \\
\iff \\
\forall \anyseqdef { D} \text { with } x_ n \rightarrow x_ 0: ~~\limn f(x_ n) = f(x_ 0)
\end { gather*}
If $ f, g $ are continuous in $ x _ 0 $ , then $ f + g $ and $ f \cdot g $ are also continuous in $ x _ 0 $ , and if $ g ( x _ 0 ) \ne 0 $ then $ f / g $ is also continuous in $ x _ 0 $ .
Notably, polynomials are continuous. A rational function (the quotient of two polynomials) is continuous in all points that are not roots of the denominator.
\end { rem}
\begin { thm}
Let $ D \subset \field $ , and let
\begin { subequations}
\begin { gather}
f: D \longrightarrow \field \text { continuous in } x_ 0 \in D \\
g: f(D) \longrightarrow \field \text { continuous in } f(x_ 0)
\end { gather}
\end { subequations}
Then $ g \circ f $ is also continuous in $ x _ 0 $ .
\end { thm}
\begin { proof}
Let $ \epsilon > 0 $ . Since $ g $ is continuous in $ f ( x _ 0 ) $ ,
\begin { equation}
\exists \delta _ 1 > 0: ~~|y - f(x_ 0)| < \delta _ 1 \implies |g(y) - g(f(x_ 0))| < \epsilon
\end { equation}
Since $ f $ is continuous in $ x _ 0 $ ,
\begin { equation}
\exists \delta _ 2 > 0: ~~|x - x_ 0| < \delta _ 2 \implies |f(x) - f(x_ 0)| < \delta _ 1
\end { equation}
For such $ x $ the following holds
\begin { equation}
|(g \circ f)(x) - (g \circ f)(x_ 0)| = |g(f(x)) - g(f(x_ 0))| < \epsilon
\end { equation}
which implies that $ g \circ f $ is continuous in $ x _ 0 $ .
\end { proof}
\begin { eg}
Consider the following mappings
\begin { align*}
& f: \realn \longrightarrow \realn , ~~x \longmapsto |x| \\
& g: \realn \longrightarrow \realn \setminus \set { -1} , ~~y \longmapsto \frac { 1 - y} { 1 + y} \\
& h: \realn \longrightarrow \realn , ~~x \longmapsto \frac { 1 - |x|} { 1 + |x|}
\end { align*}
It is clear that $ h = g \circ f $ . Since $ f $ , $ g $ are continuous, $ h $ must also be continuous.
\end { eg}
\begin { eg}
The functions $ \exp $ , $ \sin $ and $ \cos $ are continuous. We know that
\[
\limes { h} { 0} \frac { \exp (k) - 1} { h} = 1
\]
From this follows that
\[
\limes { h} { 0} \exp (k) = \exp (0) = 0
\]
Thus, $ \exp $ is continuous in $ 0 $ . Let $ x _ 0 \in \realn $ , then
\begin { align*}
\limes { x} { x_ 0} \exp (x) & = \limes { h} { 0} \exp (x_ 0 + h) = \limes { h} { 0} \exp (x_ 0)\exp (h) \\
& = \exp (x_ 0) - \limes { h} { 0} \exp (h) = \exp { x_ 0}
\end { align*}
Now, consider the function $ x \mapsto \exp ( ix ) $ . For $ x _ 0 \in \realn $
\begin { align*}
|\underbrace { \exp (i(x_ 0 + h))} _ { \exp (ix_ 0) \dot \exp (ih)} - \exp (i h_ 0)| & = \underbrace { |\exp (ix_ 0)|} _ 1|\exp (ih) - 1| \\
& \le 1 \cdot \left | \sum _ { k = 0} ^ { \infty } \frac { (ih)^ k} { k!} - 1 \right | = \left | \series { k} \frac { (ih)^ k} { k!} \right | \\
& \le \series { k} \left | \frac { (ih)^ k} { k!} \right | \\
& = \series { k} \frac { |h|^ k} { k!} = \sum _ { k = 0} ^ { \infty } \frac { |h|^ k} { k!} - 1 = \exp (|h|) - 1
\end { align*}
For $ h \rightarrow 0 $ , the absolute function converges $ |h| \rightarrow 0 $ , and therefore
\[
\lim { h} { 0} |\exp (i(x_ 0 + h)) - \exp (ix)| = 0
\]
due to the squeeze theorem. I.e., $ x \mapsto \exp ( ix ) $ is also continuous. Thus
\begin { align*}
\cos x = \Re (\exp (ix)) & & \sin x = \Im (\exp (ix))
\end { align*}
are also continuous due to the concatination of continuous functions.
\end { eg}
\begin { lem}
Let $ a, b \in \realn $ with $ a < b $ , and let
\[
f: [a, b] \longrightarrow \realn
\]
be a continuous function. Furthermore, let $ y \in \realn $ . Now if the set
\[
\set [f(x) \ge y] { x \in [a, b]}
\]
is non-empty, it has a smallest element.
\end { lem}
\begin { proof}
Let $ M $ be non-empty. Set $ x _ 0 = \inf \set { M } $ . Then it is to be shown that $ x _ 0 \in M $ , or that $ f ( x _ 0 ) \ge y $ .
There exists a sequence $ \anyseqdef { M } $ such that $ x _ n \rightarrow x _ 0 $ . Because of the continuity of $ f $ ,
\begin { equation}
f(x_ 0) = f(\limn x_ n) = \limn f(x_ n) \ge y
\end { equation}
holds, thus $ x _ 0 \in M $ .
\end { proof}
\begin { thm} [Extreme value theorem]
Let $ a, b \in \realn $ with $ a < b $ , and let $ f: [ a, b ] \rightarrow \realn $ continuous.
Then the function $ f $ attains a maximum, i.e.
\[
\exists x_ 0 \in [a, b] ~\forall x \in [a, b]: ~~f(x) \le f(x_ 0)
\]
\end { thm}
\begin { proof}
First we show that $ f $ is bounded. Assume $ f $ is unbounded above, i.e.
\begin { equation}
\set [f(x) \ge n] { x \in [a, b]} =: M_ n, ~~n \in \natn
\end { equation}
According to the last lemma, every $ M _ n $ has a smallest element $ x _ n $ .
The sequence $ ( x _ n ) _ { n \in \natn } $ is monotonically increasing ($ M _ { n + 1 } \subset M _ n $ ) and bounded above by $ b $ .
Thus, $ x _ n $ converges to some $ x _ 0 \in [ a, b ] $ . Now consider the sequence $ ( f ( x _ n ) ) _ { n \in \natn } $ . By definition
\begin { equation}
\limn f(x_ n) \ge \limn n = \infty
\end { equation}
And since $ f $ is continuous, $ \limn f ( x _ n ) = f ( x _ 0 ) $ must hold. This contradicts the assumption, so $ f $ is bounded.
Now set
\begin { equation}
y = \sup \set [{x \in [a, b] } ]{ f(x)}
\end { equation}
In case $ f $ is equal to $ y $ everywhere, there is nothing to show. So assume that there are values for which $ f \ne y $ .
According to the definition of the supremum, the sets
\begin { equation}
\set [f(x) \ge y - \frac{1}{n}] { x \in [a, b]}
\end { equation}
are non-empty for all $ n \in \natn $ , and thus they have a smallest element $ x _ n $ .
The sequence $ ( x _ n ) _ { n \in \natn } $ is monotonically increasing and bounded, i.e. it converges to $ x _ 0 \in [ a, b ] $ .
Therefore
\begin { equation}
y \ge f(x_ 0) = \limn f(x_ n) \ge \limn y - \frac { 1} { n} = y
\end { equation}
From this follows
\begin { equation}
f(x_ 0) = y \implies f(x_ 0) \text { upper bound of } \set [{x \in [a, b] } ]{ f(x)}
\end { equation}
\end { proof}
\begin { thm} [Intermediate value theorem]
Let $ a, b \in \realn $ with $ a < b $ , and $ f: [ a, b ] \rightarrow \realn $ a continuous function with $ f ( a ) < f ( b ) $ .
\[
y \in (f(a), f(b)) \implies \exists x_ 0 \in (a, b): ~~f(x_ 0) = y
\]
\end { thm}
\begin { proof}
\noproof
\end { proof}
\begin { eg}
$ \cos $ has in $ [ 0 , 2 ] $ exactly one root. Consider the definition
\[
\cos x = \sum _ { k = 0} ^ { \infty } \frac { (-1)^ k x^ { 2k} } { (2k)!}
\]
We know that $ \cos 0 = 1 $ . Furthermore we can show that
\[
-1 = \underbrace { 1 - \frac { 2^ 2} { 2!} } _ { \text { 2nd partial sum} } \le \cos (2) \le \underbrace { 1 - \frac { 2^ 2} { 2!} + \frac { 2^ 4} { 4!} } _ { \text { 3rd partial sum} } < 0
\]
The intermediate value theorem tells us that there exists a root in $ [ 0 , 2 ] $ . Now we need to show that $ \cos $ is strictly monotonically decreasing on $ [ 0 , 2 ] $ .
Choose $ z \in [ 0 , 2 ] $ . Then
\[
z \le \sin z \le z - \frac { z^ 3} { 3!}
\]
The addition theorem tells us that
\[
\cos (x) - \cos (y) = -2 \sin \left (\frac { x+y} { 2} \right ) \sin \left (\frac { x-y} { 2} \right ) < 0
\]
for $ x, y \in ( 0 , 2 ] $ and $ x > y $ . Thus $ \cos $ is strictly monotonically decreasing on $ [ 0 , 2 ] $ .
\end { eg}
\begin { cor}
Let $ I $ be an interval and $ f: I \rightarrow \realn $ continuous. Then $ f ( I ) $ is also an interval.
\end { cor}
\begin { proof}
\reader
\end { proof}
\begin { thm}
Let $ I $ be an interval, $ f: I \rightarrow \realn $ continuous. If $ f $ is strictly monotonically increasing, then the inverse function
$ \inv { f } : f ( I ) \rightarrow I $ exists and is continuous.
\end { thm}
\begin { hproof}
$ f ( I ) $ is an interval, and $ f $ is injective. This is because if $ f ( x ) = f ( \tilde { x } ) $ , then $ x = \tilde { x } $ or else $ f $ wouldn't be strictly monotonic.
This means
\begin { equation}
\exists g: f(I) \longrightarrow \realn : ~~f(x) = y \iff g(y) = x
\end { equation}
Let $ y _ 0 \in f ( I ) $ and $ \epsilon > 0 $ . We require that $ x _ 0 $ is not a boundary point of $ I $ . Then choose $ 0 < \tilde { \epsilon } < \epsilon $ such that
$ ( x _ 0 - \tilde { \epsilon } , x _ 0 + \tilde { epsilon } ) \in I $ . Choose
\begin { equation}
\delta = \min \set { \underbrace { f(x_ 0 + \tilde { \epsilon } ) - y_ 0} _ { > 0} , \underbrace { y_ 0 - f(x_ 0 - \tilde { \epsilon } )} _ { > 0} } > 0
\end { equation}
If $ y \in f ( I ) $ with $ |y - y _ 0 | < \delta $ then
\begin { equation}
f(x_ o - \tilde { epsilon} ) \le x_ 0 - \delta < y < y_ 0 + \delta \le f(x_ 0 + \tilde { \epsilon } )
\end { equation}
From the strict monotony of $ g $ we can conclude
\begin { equation}
x_ 0 - \tilde { epsilon} < g(y) < x_ 0 + \tilde { \epsilon }
\end { equation}
so
\begin { equation}
|g(y) - g(y_ 0)| = |g(y) - x_ 0| < \tilde { \epsilon } < \epsilon
\end { equation}
Thus, $ g $ is continuous in $ y _ 0 $ . Since $ y _ 0 \in f ( I ) $ was chose arbitrarily, all of $ g $ is continuous.
To prove the monotony of $ g $ , assume $ y < \tilde { y } $ and $ g ( y ) \ge g ( \tilde { y } ) $ for $ y, \tilde { y } \in f ( I ) $ . From the monotony of $ f $ we know that
\begin { equation}
y \ge \tilde { y}
\end { equation}
which is a contradiction, so $ g $ is strictly monotonic.
\end { hproof}
\begin { eg}
\begin { enumerate} [(i)]
\item Let $ n \in \natn $ and consider
\begin { align*}
f: [0, \infty ) & \longrightarrow \realn \\
x & \longmapsto x^ n
\end { align*}
$ f $ is continuous and strictly monotonically increasing. Thus the inverse function
\[
\sqrt [n] { \cdot } : [0, \infty ) \longrightarrow \realn ^ +
\]
is also continuous.
\item Consider $ \exp : \realn \rightarrow \realn $ . It's clear that $ \exp ( \realn ) = ( 0 , \infty ) $ , so the mapping
\[
\ln : (0, \infty ) \rightarrow \realn
\]
is continuous and strictly monotonically increasing.
\item Equal arguments can be made for the trigonometric functions.
\end { enumerate}
\end { eg}
2021-03-25 10:09:32 +00:00
\end { document}