Epsilon-delta definition of continuity – Serlo

Among the sequence criterion, the epsilon-delta criterion is another way to define the continuity of functions. This criterion describes the feature of continuous functions, that sufficiently small changes of the argument cause arbitrarily small changes of the function value.

Motivation

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In the beginning of this chapter, we learned that continuity of a function may - by a simple intuition - be considered as an absence of jumps. So if we are at an argument where continuity holds, the function values will change arbitrarily little, when we wiggle around the argument by a sufficiently small amount. So  , for   in the vicinity of   . The function values   may therefore be useful to approximate   .

Continuity when approximating function values

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If a function has no jumps, we may approximate its function values by other nearby values . For this approximation, and hence also for proofs of continuity, we will use the epsilon-delta criterion for continuity. So how will such an approximation look in a practical situation?

Suppose, we make an experiment that includes measuring the air temperature as a function of time. Let   be the function describing the temperature. So   is the temperature at time  . Now, suppose there is a technical problem, so we have no data for   - or we simply did not measure   at exactly this point of time. However, we would like to approximate the function value   as precisely as we can:

 
At time x_0 , the temperature is f(x_0)

Suppose, a technical issue prevented the measurement of   . Since the temperature changes continuously in time - and especially there is no jump at   - we may instead use a temperature value measured at a time close to   . So, let us approximate the value   by taking a temperature   with   close to   . That means,   is an approximation for  . How close must   come to   in order to obtain a given approximation precision?

Suppose that for the evaluation of the temperature at a later time   , the maximal error shall be   . So considering the following figure, the measured temperature should be in the grey region . Those are all temperatures with function values between   and   , i.e. inside the open interval   :

 
Epsilon-region around the function value f(x_0)

In this graphic, we may see that there is a region around   , where function values differ by less than   from   . So in fact, there is a time difference  , such that all function values are inside the interval   highlighted in grey:

 
Delta-region around x_0, where all function values lie in an epsilon-region around f(x_0)

Therefore, we may indeed approximate the missing data point   sufficiently well (meaning with a maximal error of  ) . This is done by taking a time   differing from   by less than   and then, the error of   in approximating   will be smaller than the desired maximal error  . So   will be the approximation for   .

Conclusion: There is a  , such that the difference   is smaller than   for all   smaller than   . I.e.  

Increasing approximation precision

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What will happen, if we need to know the temperature value to a higher precision due to increased requirements in the evaluation of the experiment? For instance, if the required maximal temperature error is set to   instead of   ?

 
Small epsilon-interval around the function value f(x_0)

In that case, thare is an interval around  , where function values do not deviate by more than   from   . Mathematically speaking, there a   exists, such that   differs by a maximum amount of   from   , if there is   :

 
Small delta-interval around x_0, where all function values are in a small interval around f(x_0)

No matter how small we choose   , thanks to the continuous temperature dependence, we may always find a   , such that   differs at most by   from   , whenever   is closer to   than   . We keep in mind:

No matter which maximal error   is required, there is always an interval around   , which is   with size  , where all approximated function values   deviate by less than   from the function value   to be approximated.

This holds true , since the function   does not have a jump at   . In other words, since   is continuous at  . Even beyond that, we may always infer from the above characteristic that there is no jump in the graph of   at  . Therefore, we may use it as a formal definition for continuity. As mathematicians frequently use the variables   and   when describing this characteristic, it is also called epsilon-delta-criterion for continuity.

Epsilon-delta-criterion for continuity

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Why does the epsilon-delta-criterion hold if and only if the graph of the function does not have a jump at some argument (i.e. it is continuous there)? The temperature example allows us to intuitively verify, that the epsilon-delta-criterion is satisfied for continuous functions. But will the epsilon-delta-criterion be violated, when a function has a jump at some argument? To answer this question, let us assume that the temperature as a function of time has a jump at some  :

 
Function with a jump at x_0

Let   be a given maximal error that is smaller than the jump:

 
Epsilon-interval with an epsilon smaller than the jump

In that case, we may not choose a  -interval   around  , where all function values have a deviation lower than   from  . If we, for instance, choose the following  , then there certainly is an   between   and   with a function value differing by more than   from  :

 
x is inside a delta-interval around x_0, but its function value f(x) has a distance larger than epsilon to f(x_0)

When choosing a smaller  , we will find an   with  , as well:

 
x is situated in a delta-interval around x_0, but f(x) differs by more than epsilon from f(x_0)

No matter how small we choose  , there will always be an argument   with a distance of less than   to  , such that the function value   differs by more than   from  . So we have seen that in an intuitive example, the epsilon-delta-criterion is not satisfied, if the function has a jump. Therefore, the epsilon-delta-criterion characterizes whether the graph of the function has a jump at the considered argument   or not. That means, we may consider it as a definition of continuity. Since this criterion only uses mathematically well-defined terms, it may be used not just as an intuitive, but also as a formal definition.

Hint

In the above example, we did not pay attention to some of the aspects we would have to consider when performing actual measurements. As an example, we assumed to have perfect measurements without any errors. Of course, this is not the case in reality. Every measurement at some time   has an outcome differing from the actual value  . In addition, we assumed instantaneous measurements at  . Usually, each recording of a value takes some time. These uncertainties have to be taken into account for real experiments.  

Definition

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Epsilon-Delta criterion for continuity

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The  -  definition of continuity at an argument   inside the domain of definition is the following:

Definition (Epsilon-Delta-definition of continuity)

A function   with   is continuous at  , if and only if for any   there is a   , such that   holds for all   with   . Written in mathematical symbols, that means   is continuous at   if and only if

 

Explanation of the quantifier notation:

 

The above definition describes continuity at a certain point (argument). An entire function   is called continuous, when it is continuous - according to the epsilon-delta criterion - at each of its arguments in the domain of definition.

Derivation of the Epsilon-Delta criterion for discontinuity

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We may also obtain a criterion of discontinuity by simply negating the above definition. Negating mathematical propositions has already been treated in chapter „Aussagen negieren“ . While doing so, an all quantifier   gets transformed into an existential quantifier   and vice versa. Concerning inner implication, we have to keep in mind that the negation of   is equivalent to   . Negating the epsilon-delta criterion of discontinuity, we obtain:

 

This gets us the negation of continuity (i.e. discontinuity):

 

Epsilon-Delta criterion for discontinuity

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Definition (Epsilon-Delta definition of discontinuity)

A function   with   is discontinuous at  , if and only if there is an   , such that for all   a   with   and   exists. Mathematically written,   is discontinuous at   iff

 

Explanation of the quantifier notation:

 

Further explanations considering the Epsilon-Delta criterion

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The inequality   means that the distance between   and   is smaller than   . Analogously,   tells us that the distance between   and   is smaller than   . Therefor, the implication   just says that whenever   and   are closer together than   , then we know that the distance between   and   before applying the function must have been smaller than   . Thus we may interpret the epsilon-delta criterion in the following way:

No matter how small we set the maximal distance   between function values   , there will always be a  , such that   and   (after being mapped) are closer together than   , whenever   is closer to   than   .

For continuous functions, we can control the error   to be lower than   by keeping the error in the argument sufficiently small (smaller than  ). Finding a   means answering the question: How low does my initial error in the argument have to be in order to get a final error smaller than   . This may get interesting when doing numerical calculations or measurements. Imagine, you are measuring some   and then using it to compute   where   is a continuous function. The epsilon-delta criterion allows you to find the maximal error   in   (i.e.  ), which guarantees that the final error   will be smaller than  .

A   may only be found if small changes around the argument   also cause small changes around the function value   . Hence, concerning functions continuous at   , there has to be:

 

I.e.: whenever   is sufficiently close to   , then   is approximately  . This may also be described using the notion of an  -neighborhood:

For every  -neighborhood   around   - no matter how small it may be - there is always a  -neighborhood   around  , whose function values are all mapped into the  -neighborhood.

In topology, this description using neighborhoods will be generalized to a topological definition of continuity.

Visualization of the Epsilon-Delta criterion

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Description of continuity using the graph

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The epsilon-delta criterion may nicely be visualized by taking a look at the graph of a funtion. Let's start by getting a picture of the implication  . This means, the distance between   and   is smaller than epsilon, whenever   is closer to   than   . So for  , there is  . Hence, the point   has to be inside the rectangle   . This is a rectangle with width   and height   centered at  :

 
The 2epsilon-2delta-rectangle

We will call this the  - -rectangle and only consider its interior. That means, the boundary does not belong to the rectangle. Following the epsilon-delta criterion, the implication   has to be fulfilled for all arguments   . Thus, all points making up the graph of   restricted to arguments inside the interval   (in the interior of the  - -rectangle, which is marked green) must never be above or below the rectangle (the red area):

 
The 2epsilon-2delta-rectangle with allowed and forbidden areas

So graphically, we may describe the epsilon-delta criterion as follows:

For all rectangle heights   , there is a sufficiently small rectangle width  , such that the graph of   restricted to   (i.e. the width of the rectangle) is entirely inside the green interior of the  - -rectangle, and never in the red above or below area.

Example of a continuous function

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For an example, consider the function   . This fucntion is continuous everywhere - and hence also at the argument  . There is  . At first, consider a maximal final error of   around  . With   , we can find a  , such that the graph of   is entirely situated inside the interior of the  - -rectangle:

 
Visualization of epsilon-delta continuity

But not only for  , but for any   we may find a   , such that the graph of   is situated entirely inside the respective  - -rectangle:

Example for a discontinuous function

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What happens if the function is discontinuous? Let's take the signum function  , which is discontinuous at 0:

 

And here is its graph:

 
Graph of the signum function

The graph intuitively allows to recognize that at   , there certainly is a discontinuity. And we may see this using the rectangle visualization, as well. When choosing a rectangle height  , smaller than the jump height (i.e.  ), then there is no  , such that the graph can be fitted entirely inside the  - -rectangle. For instance if   , then for any   - no matter how small - there will always be function values above or below the  - -rectangle. In fact, this apples to all values except for  :

Dependence of delta or epsilon choice

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Continuity

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How does the choice of   depend on   and  ? Suppose, an arbitrary   is given in order to check continuity of  . Now, we need to find a rectangle width   , such that the restriction of the graph of   to arguments inside the interval   entirely fits into the epsilon-tube   . This of course requires choosing  sufficiently small. When   is too large, there may be an argument   in  , where   has escaped the tube, i.e. it has a distance to   larger than   :

How small   has to be chosen, will depend on three factors: The function  , the given   and the argument  . Depending on the function slope, a different   chosen (steep functions require a smaller  ). Furthermore, for a smaller   we also have to choose a smaller   . The following diagrams illustrate this: Here, a quadratic function is plotted, which is continuous at   . For a smaller   , we also need to choose a smaller   :

 
Dependence of δ on ε: In general, δ has to be chosen smaller as ε shrinks.

The choice of   will depend on the argument  , as well. The more a function changes in the neighborhood of a certain point (i.e. it is steep around it), the smaller we have to choose   . The following graphic demonstrates this: The  -value proposed there is sufficiently small at   , but too large at   :

 
The value for delta is sufficiently small for x_0, but too large for x_1.

In the vicinity of   , the function   has a higher slope compared to  . Hence, we need to choose a smaller   at   . Let us denote the  -values at   and   correspondingly by   and   - and choose   to be smaller:

 
Both interval widths delta_1 and delta_2 are small enough for the given epsilon.

So, we have just seen that the choice of   depends on the function   to be considered, as well as the argument   and the given   .

Discontinuity

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For a discontinuity proof, the relations between the variables will interchange. This relates back to the interchange of the quantifiers under negation of propositions. In order to show discontinuity, we need to find an   small enough, such that for no   the graph of   fits entirely into the  - -rectangle. In particular, if the discontinuity is caused by a jump, then   must be chosen smaller than the jump height. For   too large, there might be a  , such that   does fit into the  - -rectangle:

Which  has to be chosen again depends on the function around   . After   has been chosen, an arbitrary   will be considered. Then, an   between   and   has to be found, such that   has a distance larger than (or equal to)   to   . That means, the point   has to be situated above or below the  - -rectangle. Which   has to be chosen depends on a varety of parameters: the chosen   and the arbitrarily given  , the discontinuity and the behavior of the function around it.

Example problems

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Continuity

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Exercise (Continuity of a linear function)

Prove that a linear function   with   is continuous.

How to get to the proof? (Continuity of a linear function)

 
Graph of a function   with  . Considering the graph , we see that this function is continuous everywhere.

To actually prove continuity of   , we need to check continuity at any argument   . So let   be an arbitrary real number. Now, choose any arbitrary maximal error   . Our task is now to find a sufficiently small   , such that   for all arguments   with   . Let us take a closer look at the inequality   :

 

That means,   has to be fulfilled for all   with   . How to choose   , such that   implies   ?

We use that the inequality   contains the distance   . As   we know that this distance is smaller than   . This can be plugged into the inequality   :

 

If   is now chosen such that   , then   will yield the inequality   which we wanted to show. The smallness condition for   can now simply be found by resolving   for  :

 

Any   satisfying   could be used for the proof. For instance, we may use  . As we now found a suitable  , we can finally conduct the proof:

Proof (Continuity of a linear function)

Let   with   and let   be arbitrary. In addition, consider any   to be given. We choose  . Let   with  . There is:

 

This shows  , and establishes continuity of   at   by means of the epsilon-delta criterion. Since   was chosen to be arbitrary, we also know that the entire function   is continuous.

Discontinuity

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Exercise (Discontinuity of the signum function)

Prove that the signum function is   is discontinuous:

 

How to get to the proof? (Discontinuity of the signum function)

In order to prove discontinuity of the entire function, we just have to find one single argument where it is discontinuous. Considering the graph of   , we can already guess, which argument this may be:

 
Graph of the signum function

The function has a jump at   . So we expect it to be discontinuous, there. It remains to choose an   that makes it impossible to find a   , that makes the function fit into the  - -rectangle. This is done by setting   smaller than the jump height   - for instance  . For that  , no matter how   is given, there will be function values above or below the  - -rectangle.

So let   be arbitrary. We need to show that there is an   with   but   . Let us take a look at the inequality   :

 

This inequality classifies all   that can be used for the proof. The particular   we choose has to fulfill   :

 

So our   needs to fulfill both   and   . The second inequality   may be achieved quite easily: For any   , the value   is either   or  . So   does always fulfill  .

Now we need to fulfill the first inequality  . From the second inequality, we have just concluded   . This is particularly true for all   with   . Therefore, we choos   to be somewhere between   and   , for instance  .

The following figure shows that this is a sensible choice. The  - -rectangle with   and   is drawn here. All points above or below that rectangle are marked red. These are exactly all   inside the interval   excluding  . Our chosen   (red dot) is situated directly in the middle of the red part of the graph above the rectangle:

 
At x=δ/2, the graph is above the 2ϵ-2δ-rectangle

So choosing   is enough to complete the proof:

Proof (Discontinuity of the signum function)

We set   (this is where   is discontinuous). In addition, we choose  . Let   be arbitrary. For that given  , we choose  . Now, on one hand there is:

 

But on the other hand:

 

So indeed,   is discontinuous at   . Hence, the function   is discontinuous itself.

Relation to the sequence criterion

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Now, we have two definitions of continuity: the epsilon-delta and the sequence criterion. In order to show that both definitions describe the same concept, we have to prove their equivalence. If the sequence criterion is fulfilled, it must imply that the epsilon-delta criterion holds and vice versa.

Epsilon-delta criterion implies sequence criterion

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Theorem (The epsilon-delta criterion implies the sequence criterion)

Let   with   be any function. If this function satisfies the epsilon-dela criterion at   , then the sequence criterion is fulfilled at   , as well.

How to get to the proof? (The epsilon-delta criterion implies the sequence criterion)

Let us assume that the function   satisfies the epsilon-delta criterion at   . That means:

For every   , there is a   such that   for all   with   .

We now want to prove that the sequence criterion is satisfied, as well. So we have to show that for any sequence of arguments   converging to   , there also has to be   . We therefor consider an arbitrary sequence of arguments   in the domain   with  . Our job is to show that the sequence of function values   converges to   . So by the definition of convergence:

For any   there has to be an   such that   for all  .

Let   be arbitrary. We have to find a suitable   with   for all sequence elements beyond that   , i.e.   . The inequality   seems familiar, recalling the epsilon-delta criterion. The only difference is that the argument   is replaced by a sequence element   - so we consider a special case for   . Let us apply the epsilon-delta criterion to that special case, with our arbitrarily chosen   being given:

There is a  , such that   for all sequence elements   fulfilling   .

Our goal is coming closer. Whenever a sequence element   is close to   with   , it will satisfy the inequality which we want to show, namely  . It remains to choose an  , where this is the case for all sequence elements beyond   . The convergence   implies that   gets arbitrarily small. So by the definition of continuity, we may find an  , with   for all   . This   now plays the role of our  . If there is  , it follows that   and hence   by the epsilon-delta criterion. In fact, any   will do the job. We now conclude our considerations and write down the proof:

Proof (The epsilon-delta criterion implies the sequence criterion)

Let   e a function satisfying the epsilon-delta criterion at   . Let   be a sequence inside the domain of definition, i.e.   for all   coverging as  . We would like to show that for any given   there exists an   , such that   holds for all   .

So let   be given. Following the epsilon-delta criterion, there is a  , with   for all   close to   , i.e.   . As   converges to   , we may find an   with   for all   .

Now, let   be arbitrary. Hence,  . The epsilon-delta criterion now implies  . This proves   and therefore establishes the epsilon-delta criterion.

Sequence criterion implies epsilon-delta criterion

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Theorem (The sequence criterion implies the epsilon-delta criterion)

Let   with   be a function. If   satisfies the sequence criterion at   , then the epsilon-delta criterion is fulfilled there, as well.

How to get to the proof? (The sequence criterion implies the epsilon-delta criterion)

We need to show that the following implication holds:

 

This time, we do not show the implication directly, but using a contraposition. So we will prove the following implication (which is equivalent to the first one):

 

Or in other words:

 

So let   be a function that violates the epsilon-delta criterion at   . Hence,   fulfills the discontinuity version of the epsilon-delta criterion at  . We can find an  ,such that for any   there is a   with   but   . It is our job now to prove, that the sequence criterion is violated, as well. This requires choosing a sequence of aguments   , converging as   but   .

This choice will be done exploiting the discontinuity version of the epsilon-delta criterion. That version provides us with an   , where   holds (so continuity is violated) for certain arguments   . We will now construct our sequence exclusively out of those certain   . This will automatically get us  .

So how to find a suitable sequence of arguments  , converging to   ? The answer is: by choosing a null sequence  . Practically, this is done as follows: we set   . For any   , we take one of the certain   for   as our argument   . Then,   but also  . These   make up the desired sequence  . On one hand, there is   and as   , the convergence   holds. But on the other hand   , so the sequence of function values   does not converge to   . Let us put these thoughts together in a single proof:

Proof (The sequence criterion implies the epsilon-delta criterion)

We establish the theorem by contraposition. It needs to be shown that a function   violating the epsilon-delta criterion at   also violates the sequence criterion at   . So let   with   be a function violating the epsilon-delta criterion at   . Hence, there is an  , such that for all   an   exists with   but   .

So for any   , there is an   with   but  . The inequality   can also be written  . As   , there is both   and  . Thus, by the sandwich theorem, the sequence   converges to  .

But since   for all   , the sequence   can not converge to   . Therefore, the sequence criterion is violated at   for the function   : We have found a sequence of arguments   with   but  .

Exercises

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Quadratic function

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Exercise (Continuity of the quadratic function)

Prove that the function   with   is continuous.

How to get to the proof? (Continuity of the quadratic function)

For this proof, we need to show that the square function is continuous at any argument   . Using the proof structure for the epsilon-delta criterion, we are given an arbitrary   . Our job is to find a suitable   , such that the inequality   holds for all  .

In order to find a suitable   , we plug in the definition of the function   into the expression   which shall be smaller than  :

 

The expression   may easily be controlled by  . Hence, it makes sense to construct an upper estimate for   which includes   and a constant. The factor   appears if we perform a factorization using the third binomial formula:

 

The requirement   allows for an upper estimate of our expression:

 

The   we are looking for may only depend on   and   . So the dependence on   in the factor   is still a problem. We resolve it by making a further upper estimate for the factor   . We will use a simple, but widely applied "trick" for that: A   is subtracted and then added again at another place (so we are effectively adding a 0) , such that the expression   appears:

 

The absolute   is obtained using the triangle inequality. This absolute   is again bounded from above by   :

 

So reshaping expressions and applying estimates, we obtain:

 

With this inequality in hand, we are almost done. If   is chosen in a way that   , we will get the final inequality   . This   is practically found solving the quadratic equation   for   . Or even simpler, we may estimate   from above. We use that we may freely impose any condition on   . If we, for instance, set  , then   which simplifies things:

 

So   will also do the job. This inequality can be solved for   to get the second condition on  (the first one was  ):

 

So any   fulfilling both conditions does the job:   and   have to hold. Ind indeed, both are true for  . This choice will be included into the final proof:

Proof (Continuity of the quadratic function)

Let   be arbitrary and  . If an argument   fulfills   then:

 

This shows that the square function is continuous by the epsilon-delta criterion.

Concatenated absolute function

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Exercise (Example for a proof of continuity)

Prove that the following function is continuous at  :

 

How to get to the proof? (Example for a proof of continuity)

We need to show that for each given   , there is a   , such that for all   with   the inequality   holds. In our case,  . So by choosing   for   small enough, we may control the expression   . First, let us plug   into   in order to simplify the inequality to be shown   :

 

The objective is to "produce" as many expressions   as possible, since we can control  . It requires some experience with epsilon-delta proofs in order to "directly see" how this is achieved. First, we need to get rid of the double absolute. This is done using the inequality   . For instance, we could use the following estimate:

 

However, this is a bad estimate as the expression   no longer tends to 0 as   . To resolve this problem, we use   before applying the inequality   :

 

A factor of   can be directly extracted out of this with the third binomial fomula:

 

And we can control it by  :

 

Now, the required   must only depend on   and   . Therefore, we have to get rid of the  -dependence of  . This can be done by finding an upper bound for   which does not depend on  . As we are free to chose any   for our proof, we may also impose any condition to it which helps us with the upper bound. In this case,   turns out to be quite useful. In fact,   or an even higher bound would do this job, as well. What follows from this choice?

As before, there has to be  . As   , we now have   and as   , we obtain   and  . This is the upper bound we were looking for:

 

As we would like to show   , we set  . And get that our final inequality holds:

 

So if the two conditions for   are satisfied, we get the final inequality. In fact, both conditions will be satisfied if  , concluding the proof. So let's conclude our ideas and write them down in a proof:

Proof (Example for a proof of continuity)

Let   be arbitrary and let  . Further, let   with  . Then:

Step 1:  

As   , there is  . Hence   and  . It follows that   and therefore  .

Step 2:  

 

Hence, the function is continuous at   .

Hyperbola

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Exercise (Continuity of the hyperbolic function)

Prove that the function   with   is continuous.

How to get to the proof? (Continuity of the hyperbolic function)

The basic pattern for epsilon-delta proofs is applied here, as well. We would like to show the implication   . Forst, let us plug in what we know and reshape our terms a bit until a   appears:

 

By assumption, there will be  , of which we can make use:

 

The choice of   may again only depend on   and   so we need a smart estimate for   in order to get rid of the  -dependence. To do so, we consider  .

Why was   and not   chosen? The explanation is quite simple: We need a  -neighborhood inside the domain of definition of  . If we had simply chosen   , we might have get kicked out of this domain. For instance, in case , the following problem appears:

The biggest  -value with   is   and the smallest one is  . However,   is not inside the domain of definition as  . In particular,   is element of that interval, where   cannot be defined at all.

A smarter choice for  , such that the  -neighborhood doesn't touch the  -axis is half of the distance to it, i.e.  . A third of this distance or other fractions smaller than 1 would also be possible:  ,   or  .

As we chose   and by   , there is  . This allows for an upper bound:   and we may write:

 

So we get the estimate:

 

Now, we want to prove   . Hence we choose  . Plugging this in, our final inequality   will be fulfilled.

So again, we imposed two conditions for   :   and  . Both are fulfilled by  , which we will use in the proof:

Proof (Continuity of the hyperbolic function)

Let   with   and let   be arbitrary. Further, let   be arbitrary. We choose  . For all   with   there is:

 

Hence, the function   is continuous at   . And as   was chosen to be arbitrary, the whole function   is continuous.

Concatenated square root function

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Exercise (Epsilon-Delta proof for the continuity of the Square Root Function)

Show, using the epsilon-delta criterion, that the following function is continuous:

 

How to get to the proof? (Epsilon-Delta proof for the continuity of the Square Root Function)

We need to show, that for any given   , there is a   , such that all   with   satisfy the inequality   . So let us take a look at the target inequality   and estimate the absolute   from above. We are able to control the term   . Therefor, would like to get an upper bound for   including the expression   . So we are looking for an inequality of the form

 

Here,   is some expression depending on   and   . The second factor is smaller than   and can be made arbitrarily small by a suitable choice of   . Such a bound is constructed as follows:

 

Since   , there is:

 

If we now choose   small enough, such that   , then we obtain our target inequality  . But   still depends on   , so   would have to depend on , too - and we required one choice of   which is suitable for all   . THerefore, we need to get rid of the  -dependence. This is done by an estimate of the first factor, such that our inequality takes the form   :

 

We even made   independent of   , which would in fact not have been necessary. So we obtain the following inequality

 

We need the estimate  , in order to fulfill the target inequality   . The choice of   is sufficient for that. So let us write down the proof:

Proof (Epsilon-Delta proof for the continuity of the Square Root Function)

Let   with  . Let   and an arbitrary   be given. We choose  . For all   with   there is:

 

Hence,   is a continuous function.

Discontinuity of the topological sine function

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Exercise (Discontinuity of the topological sine fucntion)

Prove the discontinuity at   for the topological sine function:

 

How to get to the proof? (Discontinuity of the topological sine fucntion)

In this exercise, discontinuity has to be shown for a given function. This is done by the negation of the epsilon-delta criterion. Our objective is to find both an   and an  , such that   and   . Here,   may be chosen depending on   , while   has to be the same for all   . For a solution, we may proceed as follows

Step 1: Simplify the target inequality

First, we may simplify the two inequalities which have to be fulfilled by plugging in   and  . We therefore get:   and  .

Step 2: Choose a suitable  

We consider the graph of the function   . It will help us finding the building bricks for our proof:

 
Graph of the topological sine function

We need to find an   , such that there are arguments in each arbitrarily narrow interval   whose function values have a distance larger than   from   . Visually, no matter how small the width   of the  - -rectangle is chosen, there will always be some points below or above it.

Taking a look at the graph, we see that our function oscillates between   and   . Hence,   may be useful. In that case, there will be function values with   in every arbitrarily small neighborhood around  . We choose  . This is visualized in the following figure:

 
The topological sine function oscillates between -1 and 1 nea the origin. Hence, in each neighborhood around 0, there will be arguments x , where f(x) has a distance larger than 1/2 to 0.

After   has been chosen, an arbitrary   will be assumed, for which we need to find a suitable  . This is what we will do next.

Step 3: Choice of a suitable  

We just set   . Therefore,   has to hold. So it would be nice to choose an   with   . Now,   is obtained for any   with   . The condition for   such that the function gets 1 is therefore:

 

So we found several   , where   . Now we only need to select one among them, which satisfies   for the given   . Our   depend on   . So we have to select a suitable   , where   . To do so, let us plug   into this inequality and solve it for   :

 

So the condition on   is  . If we choose just any natural number   above this threshold   , then   will be fulfilled. Such a   has to exist by Archimedes' axiom (for instance by flooring up the right-hand expression). So let us choose such a   and define   via   . This gives us both   and   . So we got all building bricks together, which we will now assemble to a final proof:

Proof (Discontinuity of the topological sine fucntion)

Choose   and let   be arbitrary. Choose a natural number   with  . Such a natural number   has to exist by Archimedes' axiom. Further, let  . Then:

 

In addition:

 

Hence, the function is discontinuous at  .