User:TakuyaMurata/Sequences of numbers

The chapter begins with the discussion of definitions of real and complex numbers. The discussion, which is often lengthy, is shortened by tools from abstract algebra.

Real numbers edit

Let   be the set of rational numbers. A sequence   in   is said to be Cauchy if   as  . Let   be the set of all sequences   that converges to  .   is then an ideal of  . It then follows that   is a maximal ideal and   is a field, which we denote by  .

The formal procedure we just performed is called field completion, and, clearly, a different choice of a valuation   could give rise to a different field. It turned out that every valuation for   is either equivalent to the usual absolute or some p-adic absolute value, where   is a prime. (w:Ostrowski's theorem) Define   where   is the maximal ideal of all sequences   that converges to   in  .

A p-adic absolute value is defined as follows. Given a prime  , every rational number   can be written as   where   are integers not divisible by  . We then let  . Most importantly,   is non-Archimedean; i.e.,

 

This is stronger than the triangular inequality since  

Example:  

2 Theorem If  , then  .
Proof:

  as  

Let  . Since  ,

 

Thus,  .

Let   be the closed unit ball of  . That   is compact follows from the next theorem, which gives an algebraic characterization of p-adic integers.

2 Theorem

 

where the project maps   are such that   with   being the projection  .

The theorem implies that   is a closed subspace of:

 ,

which is a product of compact spaces and thus is compact.

Sequences edit

We say a sequence of scalar-valued functions converges uniformly to another function   on   if  

1 Theorem (iterated limit theorem) Let   be a sequence of scalar-valued functions on  . If   exists and if   is uniformly convergent, then for each fixed  , we have:

 

Proof: Let  , and   be a uniform limit of  ; i.e.,  . Let   be given. By uniform convergence, there exists   such that

 

Then there is a neighborhood   of   such that:

  whenever  

Combine the two estimates:

 

Hence,

   

2 Corollary A uniform limit of a sequence of continuous functions is again continuous.

Real and complex numbers edit

In this chapter, we work with a number of subtleties like completeness, ordering, Archimedian property; those are usually never seriously concerned when Calculus was first conceived. I believe that the significance of those nuances becomes clear only when one starts writing proofs and learning examples that counter one's intuition. For this, I suggest a reader to simply skip materials that she does not find there is need to be concerned with; in particular, the construction of real numbers does not make much sense at first glance, in terms of argument and the need to do so. In short, one should seek rigor only when she sees the need for one. WIthout loss of continuity, one can proceed and hopefully she can find answers for those subtle questions when she search here. They are put here not for pedagogical consideration but mere for the later chapters logically relies on it.

We denote by   the set of natural numbers. The set   does not form a group, and the introduction of negative numbers fills this deficiency. We leave to the readers details of the construction of integers from natural numbers, as this is not central and menial; to do this, consider the pair of natural numbers and think about how arithmetical properties should be defined. The set of integers is denoted by  . It forms an integral domain; thus, we may define the quotient field   of  , that is, the set of rational numbers, by

 .

As usual, we say for two rationals   and     if   is positive.

We say   is bounded above if there exists some   in   such that for any    , and is bounded below if the reversed relation holds. Notice   is bounded above and below if and only if   is bounded in the definition given in the chapter 1.

The reason for why we want to work on problems in analysis with   instead of is a quite simple one:

2 Theorem Fundamental axiom of analysis fails in  .
Proof:  .  

How can we create the field satisfying this axiom? i.e., the construction of the real field. There are several ways. The quickest is to obtain the real field   by completing  .

We define the set of complex numbers   where   is just a symbol. That   is irreducible says the ideal generated by it is maximal, and the field theory tells that   is a field. Every complex number   has a form:

 .

Though the square root of -1 does not exist,   can be thought of as -1 since  . Accordingly, the term  is usually omitted.

2 Exercise Prove that there exists irrational numbers   such that   is rational.

Sequences edit

2 Theorem Let   be a sequence of numbers, be they real or complex. Then the following are equivalent:

  • (a)   converges.
  • (b) There exists a cofinite subsequence in every open ball.

Theorem (Bolzano-Weierstrass) Every infinite bounded set has a non-isolated point.
Proof: Suppose   is discrete. Then   is closed; thus,   is compact by Heine-Borel theorem. Since   is discrete, there exists a collection of disjoint open balls   containing   for each  . Since the collection is an open cover of  , there exists a finite subcover  . But

 

This contradicts that   is infinite.  .

2 Corollary Every bounded sequence has a convergent subsequence. Proof:

The definition of convergence given in Ch 1 is general enough but is usually inconvenient in writing proofs. We thus give the next theorem, which is more convenient in showing the properties of the sequences, which we normally learn in Calculus courses.

In the very first chapter, we discussed sequences of sets and their limits. Now that we have created real numbers in the previous chapter, we are ready to study real and complex-valued sequences. Throughout the chapter, by numbers we always means real or complex numbers. (In fact, we never talk about non-real and non-complex numbers in the book, anyway)

Given a sequence   of numbers, let  . Then we have:

   
 
 

The similar case holds for liminf as well.

Theorem Let   be a sequence. The following are equivalent:

  • (a) The sequence   converges to  .
  • (b) The sequence   is Cauchy; i.e.,   as  .
  • (c) Every convergent subsequence of   converges to  .
  • (d)  .
  • (e) For each  , we can find some real number   (i.e., N is a function of  ) so that
      for  .

Proof: From the triangular inequality it follows that:

 .

Letting   gives that (a) implies (b). Suppose (b). The Bolzano-Weierstrass theorem states that every bounded sequence has a convergent subsequence, say,  . Thus,

   
 
 
. Therefore,  . That (c) implies (d) is obvious by definition.

2 Theorem Let   and   converge to   and  , respectively. Then we have:

(a)  .
(b)  .

Proof: Let   be given. (a) From the triangular inequality it follows:

 

where the convergence of   and   tell that we can find some   so that

  and   for all  .

(b) Again from the triangular inequality, it follows:

   
 
  as  

where we may suppose that  .  

Other similar cases follows from the theorem; for example, we can have by letting  

 .

2.7 Theorem Given   in a normed space:

  • (a)   converges.
  • (b) The sequence   has the upper limit  . (Archimedean property)
  • (c)   converges.

Proof: If (b) is true, then we can find a   and   such that for all  :

 . Thus (a) is true since:,
  if  .

Continuity edit

Let  . We write   to mean the set  . In the same vein we also use the notations like  , etc.

We say,   is upper semicontinuous if the set   is open for every   and lower semicontinuous if   is upper semicontinuous.

2 Lemma The following are equivalent.

  • (i)   is upper semicontinuous.
  • (ii) If  , then there is a   such that  .
  • (iii)  .

Proof: Suppose  . Then we find a   such that  . If (i) is true, then we can find a   so that  . Thus, the converse being clear, (i)   (ii). Assuming (ii), for each  , we can find a   such that  . Taking inf over all   gives (ii)   (iii), whose converse is clear.  

2 Theorem If   is upper semicontinuous and   on a compact set  , then   is bounded from above and attains its maximum.
Proof: Suppose   for all  . For each  , we can find   such that  . Since   is upper semicontinuous, it follows that the sets  , running over all  , form an open cover of  . It admits a finite subcover since   is compact. That is to say, there exist   such that   and so:

 ,

which is a contradiction. Hence, there must be some   such that  .  

If   is continuous, then both   and   for all   are open. Thus, the continuity of a real-valued function is the same as its semicontinuity from above and below.

2 Lemma A decreasing sequence of semicontinuous functions has the limit which is upper semicontinuous. Conversely, let   be upper semicontinuous. Then there exists a decreasing sequence   of Lipschitz continuous functions that converges to f.
Proof: The first part is obvious. To show the second part, let  . Then   has the desired properties since the identity  .  

We say a function is uniform continuous on   if for each   there exists a   such that for all   with   we have  .

Example: The function   is uniformly continuous on   since

 

while the function   is not uniformly continuous on   since

 

and   can be made arbitrary large.

2 Theorem Let   for   compact. If   is continuous on  , then   is uniformly continuous on  .
Proof:

The theorem has this interpretation; an uniform continuity is a global property in contrast to continuity, which is a local property.

2 Corollary A function is uniform continuous on a bounded set   if and only if it has a continuos extension to  .
Proof:

2 Theorem if the sequence   of continuos functions converges uniformly on a compact set  , then the sequence   is equicontinuous.
Let   be given. Since   uniformly, we can find a   so that:

  for any   and any  .

Also, since   is compact,   and each   are uniformly continuous on   and so, we find a finite sequence   so that:

  whenever   and  ,

and for  ,

  whenever   and  .

Let  , and let   be given. If  , then

  whenever  .

If  , then

   
 

whenever  .  

2 Theorem A sequence   of complex-valued functions converges uniformly on   if and only if  as  
Proof: Let  . The direct part follows holds since the limit exists by assumption. To show the converse, let   for each  , which exists since the completeness of  . Moreover, let   be given. Since from the hypothesis it follows that the sequence   of real numbers is Cauchy, we can find some   so that:

  for all  .

The theorem follows. Indeed, suppose  . For each  , since the pointwise convergence, we can find some   so that:

  for all  .

Thus, if  ,

   

2 Corollary A numerical sequence   converges if and only if   as  .
Proof: Let   in the theorem be constant functions.  .

2 Theorem (Arzela) Let   be compact and metric. If a family   of real-valued functions on K bestowed with   is pointwise bounded and equicontinuous on a compact set  , then:

  • (i)   is uniformly bounded.
  • (ii)   is totally bounded.

Proof: Let   be given. Then by equicontinuity we find a   so that: for any   with  

 

Since   is compact, it admits a finite subset   such that:

 .

Since the finite union of totally and uniformly bounded sets is again totally and uniformly bounded, we may suppose that   is a singleton  . Since the pointwise boundedness we have:

  for any   and  ,

showing that (i) holds. To show (ii) let  . Then since   is compact,   is totally bounded; hence, it admits a finite subset   such that: for each  , we can find some   so that:

 .

Now suppose   and  . Finding some   in   we have:

 .

Since there can be finitely many such  , this shows (ii).  

2 Corollary (Ascoli's theorem) If a sequence   of real-valued functions is equicontinuous and pointwise bounded on every compact subset of  , then   admits a subsequence converging normally on  .
Proof: Let   be compact. By Arzela's theorem the sequence   is totally bounded with  . It follows that it has an accumulation point and has a subsequence converging to it on  . The application of Cantor's diagonal process on an exhaustion by compact subsets of   yields the desired subsequence.  

2 Corollary If a sequence   of real-valued   functions on   obeys: for some  ,

  and  ,

then   has a uniformly convergent subsequence.
Proof: We want to show that the sequence satisfies the conditions in Ascoli's theorem. Let   be the second sup in the condition. Since by the mean value theorem we have:

 ,

and the hypothesis, the sup taken all over the sequence   is finite. Using the mean value theorem again we also have: for any   and  ,

 

showing the equicontinuity.  

First and second countability edit

2 Theorem (first countability) Let   have a countable base at each point of  . Then we have the following:

  • (i) For  ,   if and only if there is a sequence   such that  .
  • (ii) A function is continuous on   if and only if   whenever  .

Proof: (i) Let   be a base at   such that  . If  , then every   intersects A</math>. Let  . It now follows: if  , then we find some  . Then   for  . Hence,  . Conversely, if  , then   is an open set containing   and no  . Hence, no sequence in   converges to  . That (ii) is valid follows since   is the composition of continuous functions   and  , which is again continuous. In other words, (ii) is essentially the same as (i).  .

2. 2 Theorem   has a countable basis consisting of open sets with compact closure.
Proof: Suppose the collection of interior of closed balls   in   for a rational coordinate  . It is countable since   is. It is also a basis of  ; since if not, there exists an interior point that is isolated, and this is absurd.

2.5 Theorem In   there exists a set consisting of uncountably many components.

Usual properties we expect from calculus courses for numerical sequences to have are met like the uniqueness of limit.

2 Theorem (uncountability of the reals) The set of all real numbers is never a sequence.
Proof: See [1].

Example: Let f(x) = 0 if x is rational, f(x) = x^2 if x is irrational. Then f is continuous at 0 and nowhere else but f' exists at 0.

2 Theorem (continuous extension) Let   be continuous. If   on  , then  .
Proof: Let  . Then clearly   is continuous on  . Since   is closed in  ,   is also closed. Hence,   on  .  

, and for each  ,  . Since for any subindex  , we have:

 .

That is to say the sequence   has the finite intersection property. Since   is coun

Since   is first countable,   is also sequentially countable. Hence, (a)   (b).

Suppose   is not bounded, then there exists some   such that: for any finite set  ,

 .

Let recursively   and  . Since   for any n, m,   is not Cauchy. Hence, (a) implies that   is totally bounded. Also,

 
separated by neighborhoods

3 Theorem the following are equivalent:

  • (a)   implies that  .
  • (b) Two points can be separated by disjoint open sets.
  • (c) Every limit is unique.

3 Theorem The separation by neighborhoods implies that a compact set   is closed in E.
Proof [2]: If  , then   is closed. If not, there exists a  . For each  , the hypothesis says there exists two disjoint open sets   containing   and   containing  . The collection   is an open cover of  . Since the compactness, there exists a finite subcover  . Let   =  . If  , then   for some  . Hence,  . Hence,  . Since the finite intersection of open sets is again open,   is open. Since the union of open sets is open,

  is open.  

Seminorm edit

 
Illustrations of unit circles in different norms.

Let   be a linear space. The seminorm of an element in   is a nonnegative number, denoted by  , such that: for any  ,

  1.  .
  2.  .
  3.  . (triangular inequality)

Clearly, an absolute value is an example of a norm. Most of the times, the verification of the first two properties while whether or not the triangular inequality holds may not be so obvious. If every element in a linear space has the defined norm which is scalar in the space, then the space is said to be "normed linear space".

A liner space is a pure algebraic concept; defining norms, hence, induces topology with which we can work on problems in analysis. (In case you haven't noticed this is a book about analysis not linear algebra per se.) In fact, a normed linear space is one of the simplest and most important topological space. See the addendum for the remark on semi-norms.

An example of a normed linear space that we will be using quite often is a sequence space  , the set of sequences   such that

For  ,  
For  ,   is a bounded sequence.

In particular, a subspace of   is said to have dimension n if in every sequence the terms after nth are all zero, and if  , then the subspace is said to be an Euclidean space.

An open ball centered at   of radius   is the set  . An open set is then the union of open balls.

Continuity and convergence has close and reveling connection.

3 Theorem Let   be a seminormed space and  . The following are equivalent:

  • (a)   is continuous.
  • (b) Let  . If  , then there exists a   such that   and  .
  • (c) Let  . For each  , there exists a   such that
  whenever   and  
  • (e) Let

Proof: Suppose (c). Since continuity, there exists a   such that:

  whenever  

The following special case is often useful; in particular, showing the sequence's failure to converge.

2 Theorem Let   be a sequence that converges to  . Then a function   is continuous at   if and only if the sequence   converges to  .
Proof: The function   of   is continuous on  . The theorem then follows from Theorem 1.4, which says that the composition of continuous functions is again continuous.  .

2 Theorem Let   be continuous and suppose   converges uniformly to a function   (i.e., the sequence   as  . Then   is continuous.
Proof: In short, the theorem holds since

 .

But more rigorously, let  . Since the convergence is uniform, we find a   so that

  for any  .

Also, since   is continuous, we find a   so that

  whenever  

It then follows that   is continuous since:

 

whenever    

2 Theorem The set of all continuous linear operators from   to   is complete if and only if   is complete.
Proof: Let   be a Cauchy sequence of continuous linear operators from   to  . That is, if   and  , then

  as  

Thus,   is a Cauchy sequence in  . Since B is complete, let

  for each  .

Then   is linear since the limit operator is and also   is continuous since the sequence of continuous functions converges, if it does, to a continuous function. (FIXME: the converse needs to be shown.)  

Metric spaces edit

We say a topological space is metric or metrizable if every open set in it is the union of open balls; that is, the set of the form   with radius   and center   where  , called metric, is a real-valued function satisfying the axioms: for all  

  1.  
  2.  
  3.   if and only if  . (Identity of indiscernibles)

It follows immediately that   for every  . In particular,   is never negative. While it is clear that every subset of a metric space is again a metric space with the metric restricted to the set, the converse is not necessarily true. For a counterexample, see the next chapter.

2 Theorem Let   be a compact metric space. If   is an open cover of  , then there exists a   such that for any   with     some member of  
Proof: Let   be in  , and suppose   is in some member   of   and   is in the complement of  . If we define a function   by for every  

 ,

then

 

The theorem thus follows if we show the inf of   over   is positive.  

2 Lemma Let   be a metric space. Then every open cover of   admits a countable subcover if and only if   is separable.
Proof: To show the direct part, fix   and let   be the collection of all open balls of radius  . Then   is an open cover of   and admits a countable subcover  . Let   be the centers of the members of  . Then   is a countable dense subset. Conversely, let   be an open cover of   and   be a countable dense subset of  . Since open balls of radii  , the centers lying in  , form a countable base for  , each member of   is the union of some subsets of countably many open sets  . Since we may suppose that for each     is contained in some   (if not remove it from the sequence) the sequence   is a countable subcover of   of  .  

Remark: For more of this with relation to cardinality see [3].

2 Theorem Let   be a metric space. Then the following are equivalent:

  • (i)   is compact.
  • (ii) Every sequence of   admits a convergent subsequence. (sequentially compact)
  • (iii) Every countable open cover of   admits a finite subcover. (countably compact)

Proof (from [4]): Throughout the proof we may suppose that   is infinite. Lemma 1.somthing says that every sequence of a infinite compact set has a limit point. Thus, the first countability shows (i)   (ii). Supposing that (iii) is false, let   be an open cover of   such that for each   we can find a point  . It follows that   does not have a convergent subsequence, proving (ii)   (iii). Indeed, suppose it does. Then the sequence   has a limit point  . Thus,  , a contradiction. To show (iii)   (i), in view of the preceding lemma, it suffices to show that   is separable. But this follows since if   is not separable, we can find a countable discrete subset of  , violating (iii).  

Remark: The proof for (ii)   (iii) does not use the fact that the space is metric.

2 Theorem A subset   of a metric space is precompact (i.e., its completion is compact) if and only if there exists a   such that   is contained in the union of finitely many open balls of radius   with the centers lying in E.

Thus, the notion of relatively compactness and precompactness coincides for complete metric spaces.

2 Theorem (Heine-Borel) If   is a subset of  , then the following are equivalent.

  • (i)   is closed and bounded.
  • (ii)   is compact.
  • (iii) Every infinite subset of   contains some of its limit points.

2 Theorem Every metric space is perfectly and fully normal.

2 Corollary Every metric space is normal and Hausdorff.

2 Theorem If   in a metric space   implies  , then   is continuous.
Proof: Let   and   the closure of  . Then there exists a   as   as  . Thus, by assumption  , and this means that   is in the closure of  . We conclude:  .  

2 Theorem Suppose that   is continuous and satisfies

  for all  

If   and   is a complete metric space, then   is closed.
Proof: Let   be a sequence in   such that  . Then by hypothesis  . Since   is complete in  , the limit   exists. Finally, since   is continuous,  , completing the proof.  

Measure edit

 
Cantor set

A measure, which we shall denote by   throughout this section, is a function from a delta-ring   to the set of nonnegative real numbers and   such that   is countably additive; i.e.,   for   distinct. We shall define an integral in terms of a measure.

4.1 Theorem A measure   has the following properties: given measurable sets   and   such that  ,

  • (1)  .
  • (2)  .
  • (3)   where the equality holds for  . (monotonicity)

Proof: (1)  . (2)   since measures are always nonnegative. Also,   if   since (2).

One example would be a counting measure; i.e.,   = the number of elements in a finite set  . Indeed, every finite set is measurable since the countable union and countable intersection of finite sets is again finite. To give another example, let   be fixed, and   if   is in   and 0 otherwise. The measure   is indeed countably additive since for the sequence   arbitrary,   for some   if   and 0 otherwise.

We now study the notion of geometric convexity.

2 Lemma

  for any  .

2 Theorem Let   be a convex subset of a vector space. If   and   for  , then

  for  

Proof: From the lemma we have:

   

Let   be a collection of subsets of a set  . We say   is a delta-ring if   has the empty set, G and every countable union and countable intersection of members of  . a member of   is called a measurable set and G a measure space, by analogy to a topological space and open sets in it.

2 Theorem (Hölder's inequality) For  , if  , then

 

Proof: By replacing   and   with   and  , respectively, we may assume that   and   are non-negative. Let  . If  , then the inequality is obvious. Suppose not, and let  . Then, since   is increasing and convex for  , by Jensen's inequality,

 .

Since  , this is the desired inequality.  

4 Corollary (Minkowski's inequality) Let   and  . If   and  , then

 

Proof (from [5]): If  , then the inequality is the same as Fubini's theorem. If  ,

   
(Fubini)  
(Hölder)  

By division we get the desired inequality, noting that   and  .  

TODO: We can probably simplify the proof by appealing to Jensen's inequality instead of Hölder's.

Remark: by replacing   by a counting measure we get:

 

under the same assumption and notation.

2 Lemma For   and  , if  ,

 

Proof: Let   for  . Then the derivative

 

becomes zero only when  . Thus, the minimum of   is attained there and is equal to  .  

When   is taken to 1, the inequality is known as Young's inequality.

2 Theorem (Hölder's inequality) For  , if  , then

 

Proof: If  , the inequality is clear. By the application of the preceding lemma we have: for any  

 

Taking the infimum we see that the right-hand side becomes:

   

The convex hull in   of a compact set K, denoted by   is:

 .

When   is linear (besides being analytic), we say the   is geometrically convex hull. That   is compact ensures that the definition is meaningful.

Theorem The closure of the convex hull of   in   is the intersection if all half-spaces containing  .
Proof: Let F = the collection of half-spaces containing  . Then   since each-half space in   is closed and convex. Yet, if  , then there exists a half-space   containing   which however does not contain x. Hence,  .  

Let  . A function   is said to be convex if

 .

for some   compact and any   harmonic on   and continuous on  .

Theorem The following are equivalent:

  • (a)   is convex on some   compact.
  • (b) if  , then
      for  .
  • (c) The difference quotient
      increases as   does.
  • (d)   is measurable and we have:
      for any  .
  • (e) The set   is convex for  .

Proof: Suppose (a). For each  , there exists some   such that  . Let  , and then since   and  ,

   
 

Thus, (a)   (b). Now suppose (b). Since  , for  , (b) says:

   
   

Since  , we conclude (b)   (c). Suppose (c). The continuity follows since we have:

 .

Also, let   such that  , for  . Then we have:

   
   
   

Thus, (c)   (d). Now suppose (d), and let  . First we want to show

 .

If  , then the inequality holds trivially. if the inequality holds for some  , then

   
 
 
 

Let   and  . There exists a sequence of rationals number such that:

 .

It then follows that:

   
 
 .

Thus, (d)   (e). Finally, suppose (e); that is,   is convex. Also suppose   is an interval for a moment. Then

 .  

4. Corollary (inequality between geometric and arithmetic means)

  if  ,   and  .

Proof: If some  , then the inequality holds trivially; so, suppose  . The function   is convex since its second derivative, again  , is  . It thus follows:

 .  

The convex hull of a finite set   is said to be a convex polyhedron. Clearly, the set of the extremely points is the subset of  .

4 Theorem (general Hölder's inequality) If   and   for   and   and  , then:

  (Hörmander 11)

Proof: Let  .

4. Theorem A convex polyhedron is the intersection of a finite number of closed half-spaces.
Proof: Use induction.  

4. Theorem The convex hull of a compact set is compact.
Proof: Let  . Then   is continuous since it is the finite sum of continuous functions  . Since the intersection of compact sets is compact and

 ,

  is compact.  

Example: Let  . Then the derivative of   has zeros in  .

Addendum edit

  1. Show the following are equivalent with assuming that   is second countable.
    • (1)   is compact.
    • (2) Every countable open cover of   admits a finite subcover (countably compact)
    • (3)   is sequentially compact.

Nets are, so to speak, generalized sequences.

  1. Show the following are equivalent with assuming Axiom of Choice:
    • (1)   is compact; i.e, every open cover admits a finite subcover.
    • (2) In   every net has a convergent subnet.
    • (3) In   every ultrafilter has an accumulation point (Bourbaki compact)
    • (4) There is a subbase   for   such that every open cover that is a subcollection of   admits a finite subcover. (subbase compact)
    • (5) Every nest of non-empty closed sets has a non-empty intersection (linearly compact) (Hint: use the contrapositive of this instead)
    • (6) Every infinite subset of   has a complete accumulation point (Alexandroff-Urysohn compact)