Lim sup and lim inf – Serlo

By limes superior and limes inferior, mathematicians denote the largest and the smallest accumulation point of a sequence. They are useful, if there are multiple limits and intuitively say what the "greatest limit" (limes superior) and the "smallest limit" (limes inferior) of that sequence are.

Motivation

Bearbeiten

We already learned about limits of a sequence. A limit is that unique number, to which a sequence tends. In every neighbourhood of the sequence, there are almost all elements, meaning only a finite number is allowed to be on the outside:

 
There are only finitely many elements outside the neighbourhood.

Sometimes, it seems like a sequence tends towards multiple numbers (like "multiple limits"). We also discussed that case: these numbers are then called "accumulation points" instead of "limits", since a limit must always be unique.

The set of accumulation points may be bounded or unbounded. In case it is bounded, there is a best upper and a best lower limit for the accumulation points, which we will call limes superior and limes inferior. Both are real numbers. Mathematically, for a sequence   we will denote the limes superior as   and the limes inferior as  .

The closed interval   then includes all accumulation points. We can even show that in any neighbourhood of this interval (i.e. a slightly bigger interval), there are almost all elements inside this neighbourhood. The following figure illustrates this situation for some  -neighbourhood   around the original interval:

 
Any interval that is slightly bigger than the grey one (both above and below) contains almost all sequence elements

Definition

Bearbeiten

Now, let us turn to a mathematical description of "greatest and smallest accumulation point". We can directly define:

Definition (limes superior)

For a sequence   bounded from above, the limes superior denotes the greatest accumulation point and is denoted by   . If the sequence is unbounded from above or there are no accumulation points, we write  .

Definition (limes inferior)

For a sequence   bounded from below, the limes inferior denotes the smallest accumulation point and is denoted by   . If the sequence is unbounded from below or there are no accumulation points, we write  .

But: Does this definition even make sense? The accumulation points form a set. Those sets need not to have a maximum (greatest value) or minimum (smallest value), but might instead just have a supremum or infimum. Mathematicians wondered, when this is the case and soon found a surprising answer: The "awkward case" that there is no greatest/smallest limit does never occur! This statement ca actually be proven

Theorem (greatest and smallest accumulation point exist)

If the accumulation points of a sequence   are bounded from above, then it has a greatest accumulation point. If the accumulation points of a sequence   are bounded from below, then it has a smallest accumulation point.

Proof (greatest and smallest accumulation point exist)

Suppose first that the accumulation points of   are bounded from above. Then, there must be a supremum   (smallest upper bound) for the accumulation points. If   is an accumulation point, it is also the greatest one and we get no contradiction to the above statement.

So let us assume that   is not an accumulation itself. In that case, each interval   for   must contain an accumulation point  . Otherwise,   would be an upper bound for the accumulation points which is smaller than   (which cannot be). But since each   subsequence element   with  . By the triangle inequality,  . This holds true for any  , so   is an accumulation point of   itself and we get a contradiction to   not being an accumulation point.

This theorem establishes that the two definitions above actually make sense, so limes superior and limes inferior are well-defined.

Examples

Bearbeiten

Example

Consider the sequence   . we can decompose it into the products   and  .

The sequence   diverges, but has two accumulation points   and  .

The sequence   is improperly convergent (which is a special kind of divergence): it goes to infinity  .

We multiply the limits/accumulation points of   and  . Since there is   , we obtain a subsequence of  , unbounded from below:  . And since   there is also a subsequence unbounded from above:  .

So   dies not converge improperly to   or  , but we can say that   and  .

Example

In case  , there is  . Since   converges, it has the unique accumulation point  . This must be the greatest and smallest accumulation point at the same time and we have

 

Example

For  , there is  . So   is unbounded from above and  . Further,   is bounded from below by  . But is has no accumulation points, as   there is   . So we also have  .

limsup, liminf and limit

Bearbeiten

If limes superior and limes inferior of a sequence   exist and coincide, then the greatest and smallest accumulation point are identical, so there can only be one accumulation point. And the sequence cannot be unbounded, so it should converge to this one accumulation point. But does it actually do that? And does the converse hold true? I.e., if the sequence   converges, are limes superior and inferior identical? The answer turns out to be yes:

Theorem (limes superior/inferior and convergence)

A sequence   converges if and only if

 

How to get to the proof? (limes superior/inferior and convergence)

We need to prove equivalence

 

which are two directions:

" " is easy: if a sequence   converges, then there is exactly one accumulation point (namely the limit  ). This must be the greatest and smallest accumulation point at the same time, so  .

" " needs some technical work, where we will use the definition of a limit and accumulation point via neighbourhoods. We recall:

  • A point   is the limit of   , if and only if   there are almost all  
  • A point   is an accumulation point of   , if and only if   there are infinitely many  .

Proof (limes superior/inferior and convergence)

Step 1: " "

If   , then the sequence   is bounded and   is its only accumulation point. By definition of limsup and liminf:

 

Step 2: " "

Let  .

Since   is the greatest accumulation point of   , we know that for all   , there are infinitely many sequence elements in   and almost all in   (i.e. only finitely many on the outside).

Since   is the smallest accumulation point of   , for any   , there are infinitely many sequence elements in  and almost all of them in   (i.e. only finitely many on the outside).

So if we fix   , then only "finite + finite = finite"-ly many sequence elements can be outside  . So almost all are on the inside which is equivalent to saying that   converges to  .

Hint

This theorem can be extended to improperly converging sequences:

 

Exercise (limes superior/inferior and improper convergence)

Prove that the statement in the above hint holds for  . (The case   is proven analogously)

How to get to the proof? (limes superior/inferior and improper convergence)

Again, we need to show two directions:  " is by definition of limsup and liminf and  " needs some technical work.

Proof (limes superior/inferior and improper convergence)

Step 1:  . Let  . Then,   is unbounded from above, but bounded from below. So by definition,   (and  ). Further,   has no accumulation point (otherwise it would not converge improperly to infinity), which implies by definition that  .

Step 2:  . Let  . Then,   is unbounded from above, but bounded from below. Since   we know that   has no accumulation points. We will show that this implies  :

Let   be any real sequence bounded from below, without an accumulation point in   . Then,   converges improperly to  .

This is shown by contradiction: Assume that   is bounded from below, but it does not converge improperly to  , which means

 

This means, there are infinitely many   with  . By means of the Bolzano-Weierstrass theorem, one can find a subsequence   of   which converges to some  . This means,   is an accumulation point of  , which contradicts   not having any accumulation points. So any   bounded from below without accumulation points must diverge improperly to  . This also holds true for our   above and by definition,  , which is what we wanted to show.

Alternative characterization

Bearbeiten

In the literature,   and   are often defined in a different but equivalent way: Suppose,   is bounded. Then we have:

Theorem (alternative definition of limsup and liminf)

If   is a bounded sequence, then

 

Intuitively, the limes superior is the "smallest upper" and the limes inferior the "greatest lower bound" of  , as  . Or in other words: The bound is allowed to be violated by finitely many elements.

Examples

Bearbeiten

Example

Let  . This sequence has two accumulation points:   and  . So by the original definition,   and  . In order to apply the alternative definition above, we have to determine   and   , as well as their limits. This is an easy task here: since   only attains the values   and both infinitely many, there is just   and   for all  . So we have two constant sequences with limits

 

and

 

and both definitions coincide.

Example

Consider  . this is a null sequence, so by the original definition,

 

For the new definition of limsup, we determine

 

which implies

 

and both definitions of the limsup coincide.

Question: Analogously, determine   by the new definition.

There is

 

so

 

which also coincides with the original definition.

Proof of the theorem

Bearbeiten

How to get to the proof? (alternative definition of limsup and liminf)

At first, we focus on the "limsup-case" and prove that   indeed converges. Since   This sequence is monotonously decreasing and bounded, so it converges by the monotony criterion. Then, we need to show that   indeed converges to  , i.e. the greatest accumulation point of  . This is done by establishing the two inequalities   and  .

The "liminf-case" works analogously. We use that   in monotonously increasing an d bounded, so it converges. And we show that the limit is indeed  , meaning the smallest accumulation point of  .

Proof (alternative definition of limsup and liminf)

Since   is bounded (by assumption), so is   . In addition,

 

So   is monotonously decreasing. By the monotony criterion,   converges to some limit which we call  .

Let us denote the greatest accumulation point of   by   . Our aim is to show  . This is done by proving   and  :

Since   is an accumulation point of   , we know that for each   there is some   with   and   for any   . This especially implies   for all  . Taking the limit, we obtain  .

On the other hand, as   is monotonously decreasing, there is also  . This holds for all  . Taking the limit   , we get  , which finishes the proof.

Rules for computing with limsup and liminf

Bearbeiten

Theorem (monotony rule)

Let   and   be bounded real sequences with   for all  . Then

 
and
 

Proof (monotony rule)

Let   be the greatest accumulation point of   and   the greatest accumulation point of  . Those accumulation points exist by the Bolzano-Weierstrass theorem and by boundedness of the sequences. Let   be given. since   is the greatest accumulation point of   , there must be an  , such that for all  :  . But since   , there is also  . Therefore   holds. Taking the limit   , we obtain  .

Exercise (v)

Analogously, prove that  .

Theorem (Relation between limsup and liminf - mirroring along the x-axis)

Let   be a bounded real sequence. Then,

 

Proof (Relation between limsup and liminf - mirroring along the x-axis)

Let   be the greatest accumulation point of  . We need to show that   , i.e.   is tha smallest accumulation point of   . This is done in two steps:

  1. We prove that   is an accumulation point of  
  2. We prove that   is the smallest accumulation point of  

Step 1: Since   , there is a subsequence   of   with  . By the limit theorems, we have  . So the subsequence   of   converges to  , i.e.   is an accumulation point of  .

Step 2: Let   be any accumulation point of  . Then, there is a subsequence   of   with  . By the limit theorems,  . hence,   is an accumulation point of  . Since   was the greatest accumulation point of   , we know that  , or equivalently  .

As   was any accumulation point of   , we know that any accumulation point is greater or equal   . So   is the smallest one and  .

Theorem (Sum rule)

Let   and   be real sequences. Then,

 

Proof (Sum rule)

Step 1: We start with the second inequality  :

Let  ,   and let   be an accumulation point of  . Then, there is a subsequence   of   with  .

Let further   be arbitrary. Since   is the greatest accumulation point of   and   is the greatest accumulation point of   , there must be a  , such that for all   there is:   and  . So, for   we also have  . By monotony of the limits, we know that  , so the   can be at most   above our desired threshold  . But now,   can be chosen arbitrarily close to 0, so we get  . Since this inequality holds for all accumulation points   of   , it also holds for the greatest one and

 

Step 2: Now, we prove  . This can be done by usind the second inequality which we just have proven and the rule  above. there is

 

This is exactly equivalent to  .

Exercise (Example for the sum rule)

Find explicit sequences   and   with strict bounds

 

Solution (Example for the sum rule)

The trick is to let sequence elements cancel against each other. One needs to play a bit around with alternating sequences to get to a solution. One example is

 

and

 

The first sequence elements are

 

and

 

So both   and   have the three accumulation points   and  . The sum of both sequences is

 

And has the accumulation points   and  . Therefore,