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.
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 valuationcould 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 TheoremIf , 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.
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 CorollaryA uniform limit of a sequence of continuous functions is again continuous.
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 TheoremFundamental 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 ExerciseProve that there exists irrational numbers such that is rational.
2 TheoremLet 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 CorollaryEvery 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.
TheoremLet 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 TheoremLet 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 TheoremGiven 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 :
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 LemmaThe 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 TheoremIf 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 LemmaA 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 TheoremLet 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 CorollaryA function is uniform continuous on a bounded set if and only if it has a continuos extension to .
Proof:
2 Theoremif 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 TheoremA 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 CorollaryA 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 CorollaryIf 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 ,
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 TheoremIn 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,
3 Theoremthe following are equivalent:
(a) implies that .
(b) Two points can be separated by disjoint open sets.
(c) Every limit is unique.
3 TheoremThe 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,
Let be a linear space. The seminorm of an element in is a nonnegative number, denoted by , such that: for any ,
.
.
. (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 dimensionn 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 TheoremLet 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 TheoremLet 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 TheoremLet 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 TheoremThe 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.)
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
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 TheoremLet 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 LemmaLet 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 TheoremLet 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 TheoremA 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 TheoremEvery metric space is perfectly and fully normal.
2 CorollaryEvery metric space is normal and Hausdorff.
2 TheoremIf 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 TheoremSuppose 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.
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 TheoremA 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 TheoremLet 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 LemmaFor 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.
TheoremThe 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 .
TheoremThe 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. TheoremA convex polyhedron is the intersection of a finite number of closed half-spaces.
Proof: Use induction.
4. TheoremThe 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 .