[PDF] Real Analysis - Harvard University





Previous PDF Next PDF



Notes in Introductory Real Analysis

These notes were written for an introductory real analysis class Math 4031



real analysis notes (2009)

Mathematics as they may not carry the same meaning in Mathematics as they do in everyday non-mathematical usage. One such word is or. In everyday parlance ...



Real Analysis(16SCCMM10) Study Material Class : III-B.Sc

Class : III-B.Sc Mathematics. Prepared by. M.Gunanithi. Assistant Professor



Real-Analysis-4th-Ed-Royden.pdf

notes for various analysis courses which have been incorporated into the ... mathematics analysis. Let f be integrable over the closed



study material for bsc mathematics real analysis - i semester - iii

STUDY MATERIAL FOR BSC MATHEMATICS. REAL ANALYSIS - I. SEMESTER - III ACADEMIC YEAR 2020-21. Page 1 of 49. UNIT. CONTENT. PAGE Nr. I. REAL NUMBER SYSTEM. 02.



MATH 36000: Real Analysis I Lecture Notes

Jul 20 2020 Analysis is one of the principle areas in mathematics. It provides the theoretical underpinnings of the calculus you know and love.



B.Sc. MATHEMATICS - III YEAR

2. Real Analysis – Vol. III – K. ChandrasekharaRao and K.S. Narayanan S. Viswanathan. Publisher. 3. Complex Analysis – Narayanan &ManicavachagamPillai.





SYLLABUS FOR B.SC MATHEMATICS HONOURS Structure of

Mathematical Modeling II. Optimization models on real life situations. One variable optimization multi-variable optimization



STUDY MATERIAL FOR B.SC. MATHEMATICS REAL ANALYSIS II

By the definition of open set it is clear that and are open sets. Page 5. STUDY MATERIAL FOR B.SC. MATHEMATICS. REAL ANALYSIS II. SEMESTER – 



real analysis notes (2009)

REAL ANALYSIS NOTES. (2009) 3.1 Real Numbers as a CompleteOrdered Field . ... same meaning in Mathematics as they do in everyday non-mathematical usage.



study material for bsc mathematics real analysis - i semester - iii

STUDY MATERIAL FOR BSC MATHEMATICS. REAL ANALYSIS - I. SEMESTER - III ACADEMIC YEAR 2020-21. Page 3 of 49. 6. I. Cauchy-schwarz inequality. Theorem:1.1 If.



Notes in Introductory Real Analysis

These notes were written for an introductory real analysis class Math 4031



B.Sc. MATHEMATICS - III YEAR

2. Real Analysis – Vol. III – K. ChandrasekharaRao and K.S. Narayanan S. Viswanathan. Publisher. 3. Complex Analysis – Narayanan &ManicavachagamPillai.



Introduction to real analysis / William F. Trench

the Editorial Board of the American Institute of Mathematics in algebra and differential equations to a rigorous real analysis course is a bigger step ...



Real-Analysis-4th-Ed-Royden.pdf

mathematical home the University of Maryland



STUDY MATERIAL FOR B.SC. MATHEMATICS REAL ANALYSIS II

STUDY MATERIAL FOR B.SC. MATHEMATICS. REAL ANALYSIS II. SEMESTER – V ACADEMIC YEAR 2020 - 21. Page 2 of 47. UNIT - I. METRIC SPACES. Introduction.



Basic Analysis: Introduction to Real Analysis

16-May-2022 It started its life as my lecture notes for teaching Math 444 at the University of. Illinois at Urbana-Champaign (UIUC) in Fall semester ...



SYLLABUS FOR B.SC MATHEMATICS HONOURS Structure of

Mathematical Modeling II. Optimization models on real life situations. One variable optimization multi-variable optimization



Lecture-Notes for The Students of B.Sc. (Mathematics Honours

Lecture-Notes for The Students of. B.Sc. (Mathematics Honours) Semester - II. Course: MATH-H-DC03 (Real Analysis). Module - 1: The Real Numbers.



Real Analysis - Harvard University

1 Introduction We begin by discussing the motivation for real analysis and especially for the reconsideration of the notion of integral and the invention of Lebesgue integration which goes beyond the Riemannian integral familiar from clas- sical calculus 1 Usefulness of analysis



MATH 36100: Real Analysis II Lecture Notes - Lewis University

Real Analysis is the formalizationof everything we learned in Calculus This enables you to make use of the examples andintuition from your calculus courses which may help you with your proofs Throughout thecourse we will be formally proving and exploring the inner workings of the Real NumberLine (hence the nameReal Analysis)



Ambar N Sengupta March 2014 - LSU

Notes in Introductory Real Analysis 19 1 2 1 Hilbert Maximality and the Completeness Property As we have mentioned before the structure of Euclidean geometry as formalized through the axioms of Hilbert produces an archimedean ordered ?eld





REAL MATHEMATICAL ANALYSIS - IIT Bombay

Real Analysis is all about formalizing and making precise a good deal of the intuition that resulted in the basic results in Calculus As it turns out the intuition is spot on in several instances but in some cases (and this is really why Real Analysis is important at



Lecture Notes in Real Analysis 2010 - IIT Bombay

Why real numbers? Example 1 Gaps in the rational number system By simply employing the unique factorization theorem for integers we can easily conclude that there is no rational number r such that r2 = 2 So there are gaps in the rational number system in this sense The gaps are somewhat subtle To illustrate this fact let us consider any



Searches related to real analysis notes for bsc mathematics pdf filetype:pdf

Analysis 1 Analysis 1 Lecture Notes 2013/2014 The original version of these Notes was written by Vitali Liskevich followed by minor adjustments by many Successors and presently taught by Misha Rudnev University of Bristol Bristol BS8 1TW UK Contents I Introduction to Analysis 1

Real Analysis

Course Notes

C. McMullen

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2 Set Theory and the Real Numbers . . . . . . . . . . . . . . . 4

3 Lebesgue Measurable Sets . . . . . . . . . . . . . . . . . . . . 13

4 Measurable Functions . . . . . . . . . . . . . . . . . . . . . . 26

5 Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

6 Dierentiation and Integration . . . . . . . . . . . . . . . . . 44

7 The Classical Banach Spaces . . . . . . . . . . . . . . . . . . 60

8 Baire Category . . . . . . . . . . . . . . . . . . . . . . . . . . 72

9 General Topology . . . . . . . . . . . . . . . . . . . . . . . . . 81

10 Banach Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . 97

11 Fourier Series . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

12 Harmonic Analysis onRandS2. . . . . . . . . . . . . . . . . 126

13 General Measure Theory . . . . . . . . . . . . . . . . . . . . . 131

A MeasurableAwithAAnonmeasurable . . . . . . . . . . . 136

1 Introduction

We begin by discussing the motivation for real analysis, and especially for the reconsideration of the notion of integral and the invention of Lebesgue integration, which goes beyond the Riemannian integral familiar from clas- sical calculus.

1.Usefulness of analysis.As one of the oldest branches of mathematics,

and one that includes calculus, analysis is hardly in need of justication. But just in case, we remark that its uses include:

1. The description of physical systems, such as planetary motion, by

dynamical systems (ordinary dierential equations);

2. The theory of partial dierential equations, such as those describing

heat ow or quantum particles;

3. Harmonic analysis on Lie groups, of whichRis a simple example;

4. Representation theory;

1

5. The description of optimal structures, from minimal surfaces to eco-

nomic equilibria;

6. The foundations of probability theory;

7. Automorphic forms and analytic number theory; and

8. Dynamics and ergodic theory.

2.Completeness.We now motivate the need for a sophisticated theory

of measure and integration, called the Lebesgue theory, which will form the rst topic in this course. In analysis it is necessary to take limits; thus one is naturally led to the construction of the real numbers, a system of numbers containing the rationals and closed under limits. When one considers functions it is again natural to work with spaces that are closed under suitable limits. For exam- ple, consider the space of continuous functionsC[0;1]. We might measure the size of a function here by kfk1=Z 1 0 jf(x)jdx: (There is no problem dening the integral, say using Riemann sums). But we quickly see that there are Cauchy sequences of continuous func- tions whose limit, in this norm, are discontinuous. So we should extend C[0;1] to a space that is closed under limits. It is not at rst even evident that the limiting objects should befunctions. And if we try to includeall functions, we are faced with the dicult problem of integrating a general function. The modern solution to this natural issue is to introduce the idea of measurable functions, i.e. a space of functions that is closed under limits and tame enough to integrate. The Riemann integral turns out to be inadequate for these purposes, so a new notion of integration must be invented. In fact we must rst examine carefully the idea of the mass ormeasureof a subset AR, which can be though of as the integral of its indicator function

A(x) = 1 ifx2Aand = 0 ifx62A.

3.Fourier series.More classical motivation for the Lebesgue integral

come from Fourier series. Supposef: [0;]!Ris a reasonable function. We dene the Fourier coecients offby a n=2 Z 0 f(x)sin(nx)dx: 2

Here the factor of 2=is chosen so that

2 Z 0 sin(nx)sin(mx)dx=nm:

We observe that if

f(x) =1X 1b nsin(nx); then at least formallyan=bn(this is true, for example, for a nite sum). This representation off(x) as a superposition of sines is very useful for applications. For example,f(x) can be thought of as a sound wave, where a nmeasures the strength of the frequencyn. Now what coecientsancan occur? The orthogonality relation implies that 2 Z 0 jf(x)j2dx=1X

1janj2:

This makes it natural to ask if, conversely, for anyansuch thatPjanj2<1, there exists a functionfwith these Fourier coecients. The natural function to try isf(x) =Pansin(nx). But why should this sum even exist? The functions sin(nx) are only bounded by one, andPjanj2<1is much weaker thanPjanj<1. One of the original motivations for the theory of Lebesgue measure and integration was to rene the notion of function so that this sum really does exist. The resulting functionf(x) however need to be Riemann inte- grable! To get a reasonable theory that includes such Fourier series, Cantor, Dedekind, Fourier, Lebesgue, etc. were led inexorably to a re-examination of the foundations of real analysis and of mathematics itself. The theory that emerged will be the subject of this course. Here are a few additional points about this example. First, we could try to dene the required space of functions | called L

2[0;] | to simply be the metric completion of, sayC[0;] with respect

tod(f;g) =Rjfgj2. The reals are dened from the rationals in a similar fashion. But the question would still remain, can the limiting objects be thought of as functions? Second, the set of pointERwherePansin(nx) actually converges is liable to be a very complicated set | not closed or open, or even a countable union or intersection of sets of this form. Thus to even begin, we must have a good understanding of subsets ofR. Finally, even if the limiting functionf(x) exists, it will generally not be Riemann integrable. Thus we must broaden our theory of integration to 3 deal with such functions. It turns out this is related to the second point | we must again nd a good notion for the length ormeasurem(E) of a fairly general subsetER, sincem(E) =RE.

2 Set Theory and the Real Numbers

The foundations of real analysis are given by set theory, and the notion of cardinality in set theory, as well as the axiom of choice, occur frequently in analysis. Thus we begin with a rapid review of this theory. For more details see, e.g. [Hal]. We then discuss the real numbers from both the axiomatic and constructive point of view. Finally we discuss open sets and Borel sets. In some sense, real analysis is a pearl formed around the grain of sand provided by paradoxical sets. These paradoxical sets include sets that have no reasonable measure, which we will construct using the axiom of choice. The axioms of set theory.Here is a brief account of the axioms. Axiom I. (Extension) A set is determined by its elements. That is, if x2A=)x2Band vice-versa, thenA=B. Axiom II. (Specication) IfAis a set thenfx2A:P(x)gis also a set. Axiom III. (Pairs) IfAandBare sets then so isfA;Bg. From this axiom and;= 0, we can now formf0;0g=f0g, which we call 1; and we can formf0;1g, which we call 2; but we cannot yet formf0;1;2g. Axiom IV. (Unions) IfAis a set, thenSA=fx:9B;B2A&x2

Bgis also a set. From this axiom and that of pairs we can formSfA;Bg=A[B. Thus we can denex+=x+ 1 =x[ fxg, and

form, for example, 7 =f0;1;2;3;4;5;6g. Axiom V. (Powers) IfAis a set, thenP(A) =fB:BAgis also a set. Axiom VI. (Innity) There exists a setAsuch that 02Aandx+12A wheneverx2A. The smallest such set is unique, and we call it

N=f0;1;2;3;:::g.

Axiom VII (The Axiom of Choice): For any setAthere is a function c:P(A) f;g !A, such thatc(B)2Bfor allBA. 4 Cardinality.In set theory, the natural numbersNare dened inductively by 0 =;andn=f0;1;:::;n1g. Thusn, as a set, consists of exactlyn elements. We writejAj=jBjto mean there is a bijection between the setsAand B; in other words, these sets have the samecardinality. A setAisniteif jAj=nfor somen2N; it iscountableifAis nite orjAj=jNj; otherwise, it isuncountable. A countable set is simply one whose elements can be written down in a (possibly nite) list, (x1;x2;:::). WhenjAj=jNjwe sayAiscountably innite. Inequalities.It is natural to writejAj jBjif there is an injective map A ,!B. By the Schroder{Bernstein theorem (elementary but nontrivial), we have jAj jBjandjBj jAj=) jAj=jBj: The power set.We letABdenote the set of all mapsf:B!A. The power setP(A)=2Ais the set of all subsets ofA. A profound observation, due to Cantor, is that jAjB=fx2A:x62f(x)g; but thenBcannot be in the image off, for ifB=f(x), thenx2Bi x62B. Russel's paradox.We remark that Cantor's argument is closely related to Russell's paradox: ifE=fX:X62Xg, then isE2E? Note that the axioms of set theory do not allow us to form the setE! Countable sets.It is not hard to show thatNNis countable, and consequently:

A countable union of countable sets is countable.

ThusZ;Qand the set of algebraic numbers inCare all countable sets. Remark: The Axiom of Choice.Recall this axiom states that for any setA,there is a mapc:P(A) f;g !Asuch thatc(A)2A. This axiom is often useful and indeed necessary in proving very general theorems; for example, if there is a surjective mapf:A!B, then there is an injective mapg:B!A(and thusjBj jAj). (Proof: setg(b) =c(f1(b)).) Another typical application of the axiom of choice is to show: 5

Every vector space has a basis.

To see this is nontrivial, consider the real numbers as a vector space overQ; can you nd a basis? The real numbers.In real analysis we need to deal with possibly wild functions onRand fairly general subsets ofR, and as a result a rm ground- ing in basic set theory is helpful. We begin with thedenitionof the real numbers. There are at least 4 dierent reasonable approaches. The axiomatic approach.As advocated by Hilbert, the real numbers can be approached axiomatically, like groups or plane geometry. Accordingly, the real numbers aredenedas acomplete, ordered eld. Note that in a eld, 06= 1 by denition. A eldKisorderedif it is equipped with a distinguished subsetK+that is closed under addition and multiplication, such that

K=K+t f0g t(K+):

It iscompleteif every nonempty setAKthat is bounded above has a least upper bound, which is denoted supA2K. Least upper bounds, limits and events.If we extend the real line by adding in1, thenanysubset ofRhas a natural supremum. For example, supZ= +1and sup;=1. The great lower bound forAis denoted by infA. From these notions we can extract the usual notion of limit in calculus, together with some useful variants. We rst note that monotone sequences always have limits, e.g.: Ifxnis an increasing sequence of real numbers, thenxn! sup(xn).

We then dene the important notion of lim-sup by:

limsupxn= limN!1sup n>Nxn: This is the limit of adecreasing sequence, so it always exists. The liminf is dened similarly, and nally we sayxnconvergesif limsupxn= liminfxn; in which case their common value is the usual limit, limxn. For example, (xn) = (2=1;3=2;+4=3;5=4;:::) has limsupxn= 1 even though supxn= 2. 6 The limsup and liminf of a sequence of 0's and 1's is again either 0 or 1. Thus given a sequence of setsEiR, there is a unique sets limsupEisuch that limsupEi= limsupEi; and similarly for liminfEi. In fact limsupEi=fx:x2Eifor innitely manyig; while limsupEi=fx:x2Eifor allifrom some point ong: These notions are particularly natural in probability theory, where we think of the setsEiasevents. Consequences of the axioms.Here are some rst consequences of the axioms.

1. The real numbers have characteristic zero. Indeed, 1 + 1 ++ 1 =

n >0 for alln, sinceR+is closed under addition.

2. Given a real numberx, there exists an integernsuch thatn > x.

Proof: otherwise, we would haveZ< xfor somex. By completeness, this means we have a real numberx0= supZ. Thenx01 isnotan upper bound forZ, sox01< nfor somen2Z. But thenn+1> x0, a contradiction.

3. Corollary: If >0 then >1=n >0 for some integern.

4. Any interval (a;b) contains a rational numberp=q. (In other words,Q

is dense inQ.) Constructions ofR.To show the real numbers exist, one must construct from rst principles (i.e. from the axioms of a set theory) a eld with the required properties. Here are 3 such constructions. Dedekind cuts.One can visualize a real numberxas acutthat partitions the rational numbers into 2 sets,

A=fr2Q:rxgandB=fr2Q:r > xg:

Thus one candeneRto consists of the set of pairs (A;B) forming partitions ofQinto nonempty sets withA < B,such thatBhas no least element. The latter convention makes the cut produced by a rational number unique. 7 Dedekind cuts work well for addition: we dene (A;B) + (A0;B0) = (A+A0;B+B0). Multiplication is somewhat trickier, but completeness works fairly well. As a rst approximation, one can dene sup(A;B) = ([A ;\B The problem here is that when the supremum is rational, the set TB might have a least element. (This suggest it might be better to introduce an equivalence relation on cuts, so that the `two versions' of each rational number are identied.) Theextended realsR[ 1are also nicely constructed using Dedekind cuts, by allowingAorBto be empty. We will often implicitly use the extended reals, e.g. by allowing the value of a sum of positive numbers to be innite rather than simply undened. For more on the ecient construction ofRusing Dedekind cuts, see [Con, p.25]. Remark: Ideals.Dedekind also proposed the notion of anidealIin the ring of integersAin a number eldK. The elementsn2Agiveprincipal ideals(n)Aconsisting of all the elements that are divisible byn. Ideals which are not principal can be thought of as `ideal' integers, which do not belong toAbut which can be seen implicitly through the set of elements of Athat they divide. In the same way a real number can be seen implicitly through the way it cutsQinto two pieces. Cauchy sequences.A more analytical approach to the real numbers is to deneRas the metric completion ofQ. Then a real number is represented by a Cauchy sequencexk2Q. This means for alln >0 there exists an

N >0 such that

jxixjj<1=n8i;j > N: We consider two Cauchy sequences to be equivalent ifjxiyij !0 asi! 1. This denition works well with respect to the eld operations, e.g. (xi) (yi) = (xiyi). It is slightly awkward to prove completeness, since we have dened completeness in terms of upper bounds. Decimals.A nal, perfectly serviceable way to dene the real numbers is in terms of decimals, such as= 3:14159265:::. As in the case of Dedekind cuts, one must introduce a convention for numbers of the formp=10n, to deal with the fact that 0:9999:::= 1:0. Other completions ofQ:One can also take the metric completion ofQ in other metrics, such as thed-adic norms wherejp=dnj=dn(assumingd does not dividep). These yield the ringsQdfor each integerd >1. All of these completions ofQaretotally disconnected. 8 The elements ofQ10can be thought of as decimal numbers which are niteafter the decimal point butnotbefore it. This ring is not a eld! If 5n accumulates onxand 2naccumulates ony, thenjxj10=jyj10= 1 butxy= 0. One can make the solution canonical by asking thatx= (0;1) andy= (1;0) inZ10=Z2Z5; theny=x+1 =:::4106619977392256259918212890625.)

On the other hand,Qpis a eld for all primesp.

The size of the real numbers.It is easy to prove:

The real numbersRare uncountable.

For example, if we had a list of all the real numbersx1;x2;:::, we could then construct a new real numberzwhoseith decimal digit diers from the ith decimal digit ofxi, so thatzis missing from the list. A more precise statement is thatjRj=jP(N)j. To see this, one can e.g. use decimals to show that 2

N,![0;1], and use binary numbers to show that

2 Nmaps onto [0;1], and nally show (by any number of arguments) that j[0;1]j=jRj. The continuum.The real numbers have a natural topology, coming from the metricd(x;y) =jxyj, with respect to which they are connected. In fact, classically the real numbers are sometimes called `the continuum' (cf.

Weyl), and its cardinality is denoted byc.

Thecontinuum hypothesisstates that any uncountable setARsatises jAj jRj. This statement isundecidablein traditional set theory, ZFC. The idea of the real numbers can be traced back to Euclid and plane geometry, where the real numbers appear as ageometric line. There is an interesting philosophical point here: classically, one can speak of a point on a line, but it is a major shift of viewpoint (from the synthetic to the analytical) to think of a line as simply a collection of points. The modern perspective onR, based on axioms and set theory, was not universally accepted at rst (cf. Brouwer). And as we will discuss below, it is worth noting that most points inRhave no names, and it is these nameless points that form the glue holding the continuum together. Intervals and open sets.We now return to a down-to-earth study of the real numbers. The simplest subsets of the real numbers are theopen intervals(a;b); we allowa=1and/orb= +1. We can also form closed intervals [a;b] or half-open intervals [a;b);(a;b]. Proposition 2.1Every open setURis a nite or countable union ofquotesdbs_dbs17.pdfusesText_23
[PDF] real analysis pdf notes

[PDF] real analysis problems and solutions pdf

[PDF] real analysis reference book

[PDF] real analysis solved problems pdf free download

[PDF] real analysis theorems

[PDF] real analysis topics

[PDF] real and complex solutions calculator

[PDF] real confederate money

[PDF] real estate closing checklist for attorneys ny

[PDF] real estate fundamentals course

[PDF] real estate market analysis textbook pdf

[PDF] real estate photography license

[PDF] real estate photography proposal

[PDF] real estate photography terms and conditions

[PDF] real estate salesperson licensing course