An Analysis of the Henstock-Kurzweil Integral

Size: px
Start display at page:

Download "An Analysis of the Henstock-Kurzweil Integral"

Transcription

1 An Analysis of the Henstock-Kurzweil Integral A Thesis Submitted to the Graduate School in Partial Fulfillment for the degree of Masters of Science by Joshua L. Turner Advisor: Dr. Ahmed Mohammed Ball State University July 25

2 ACKNOWLEDGEMENTS Thank you to my thesis advisor, Dr. Ahmed Mohammed, my thesis committee, Dr. Ralph Bremigan and Dr. Rich Stankewitz, and to Dr. Hanspeter Fischer for their guidance and their fortitude in enduring my ineptitude. 2

3 INTRODUCTION. Since the inception of integration theory, mathematicians have sought to find an integral which would make integration and differentiation truly inverse processes. Today, one of the first theories of integration that most mathematicians learn about is the Riemann integral. The Riemann integral, although very powerful is not without its flaws. One of the first mathematicians to exploit the flaws in Riemann s integral was the French mathematician Johann Peter Gustav Lejeune Dirichlet. Dirichlet constructed the following bounded function which is not Riemann integrable if x Q f(x) = if x R \ Q. This function illustrates an inherent flaw in Riemann s integral by showing that it cannot integrate functions with too many discontinuities. Mathematicians began to notice other problems with the Riemann s integral as well. For example, they realized that the Riemann integral cannot integrate every derivative. Hence, as an operator, it is not a true inverse to the derivative. Moreover, in order to integrate functions over infinite intervals or functions with vertical asymptotes, one must introduce an improper Riemann integral. Subsequently, these flaws led mathematicians to see integration in a whole new light. Prior to this time, the mathematical community had rarely considered pathological functions such as Dirichlet s. As a result, the very foundation of analysis seemed to be on unsteady ground. It was not until nearly one-hundred years later that a young mathematician named Henri Lebesgue developed a theory of integration that could handle most of the problems that plagued the Riemann integral. Lebesgue examined the effect of partitioning the range of a function rather than the domain thus allowing more control over small variations in the graph of the function. However, Lebesgue s theory was much more complicated than Riemann s and forced mathematicians to learn very deep mathematical concepts most of which were relatively unfamiliar and new to mathematics. After some time, as is their nature, mathematicians began finding flaws in Lebesgue s integral. First of all, like the Riemann integral, the Lebesgue integral is not a true inverse to differentiation. In addition, in the most general definition of the Lebesgue integral, the integrability of a function f is contingent upon the integrability of f. Although Lebesgue s integral would prove to be a valuable tool for the working mathematician, it was not the end of the story. Nearly twenty years after Lebesgue s death, two mathematicians simultaneously developed an integral that integrates any derivative making it a true inverse to differentiation. Furthermore, this new integral generalizes both the Riemann and Lebesgue integral. It is this theory that we discuss today. Let I = [a, b] R be a compact interval. Let f : I R be a real-valued function. We will investigate 3

4 the Henstock-Kurzweil or HK integral and compare it to the integrals of Riemann and Lebesgue. In the classic version of the Fundamental Theorem of Calculus, given a compact interval I = [a, b] R and functions f : I R and F : I R with F (x) = f(x) for all x I, neither the Riemann, or R integral nor the Lebesgue, or L integrals guarantees that b a f = F (b) F (a). However, the HK integral does guarantee this result. Furthermore, the HK integral is an non-absolute integral in the sense that a function f may be HK integrable without f being HK integrable. In addition, the space HK(I) of Henstock-Kurzweil integrable functions defined on a compact interval I = [a, b] R cannot be extended by adding on improper integrals in the sense that if a function f has an improper integral, then f is already HK integrable. In this paper we look at some of these results. We begin by investigating specific properties of the HK integral which illustrate how a relatively small change in the definition of the R integral can have far reaching consequences. We follow this by defining the HK integral and looking at some of its most powerful results. Next, we examine some of the differences between the HK integral and the integrals of Riemann and Lebesgue. In these sections, we look at various functions which are HK integrable and yet are neither Riemann nor Lebesgue integrable. One such function resembles the Volterra function, but with a much simpler construction. In particular, we show that R(I) L(I) HK(I) where R(I) and L(I) denote the space of Riemann and Lebesgue integrable functions defined on a compact interval I R respectively. In addition, we look at the benefit of being a non-absolute integral in the sense that a function f can be Henstock-Kurzweil integrable without f being Henstock-Kurzweil integrable. We exploit this property by showing that the HK integral can integrate any conditionally convergent series while the Lebesgue integral cannot. Finally, we discuss the consequences of using the HK integral in various areas of applied mathematics. 4

5 Contents INTRODUCTION 3 2 BASIC DEFINITIONS 6 3 GAUGES 9 4 THE HK INTEGRAL 5 PROPERTIES OF THE HK INTEGRAL 6 THE FUNDAMENTAL THEOREM OF CALCULUS 3 7 FUNCTIONS WHICH ARE HK INTEGRABLE BUT NOT R INTEGRABLE 5 8 FUNCTIONS WHICH ARE HK INTEGRABLE BUT NOT L INTEGRABLE 26 9 APPLICATIONS OF THE HK INTEGRAL 34 FINAL COMMENTS 36 5

6 2 BASIC DEFINITIONS. We begin by introducing some preliminary definitions which serve to illustrate the prowess of the HK integral. Let I = [a, b] be a compact interval in R with a < b. A partition P is a finite collection of non-degenerate closed intervals {I i } n i= I i = [x i, x i ], where a = x < x <... < x n = b. whose union is I. Here, We call each closed interval I k = [x k, x k ] a subinterval of the partition P. A tagged partition P = {(I i, t i )} n i= is a finite set of ordered pairs where the closed intervals I i form a partition of I and the numbers t i I i are the corresponding tags. x i x i. The mesh P of a partition P is given by max{l([x i, x i ]) : i =, 2,..., n} where l([x i, x i ]) = Given a tagged partition P = {(I i, t i )} n i= of I, and a function f : I R, the real-number S(f; P) = n f(t i ) x i, where x i = x i x i, is the Riemann Sum of f induced by P. i= Remark: As we will see, in our approach to integration we view the integral as a limit of Riemann sums. By using tagged partitions, we allow ourselves some flexibility with the placement of tags in that adding or eliminating points from a partition P, often the tags themselves, if done with care, will not effect the value of the Riemann sum. For example, let P = {(I i, t i )} n i= be a tagged partition of I. Let t k be an interior point of the subinterval I k = [x k, x k ]. Now, let Q be the partition of I obtained from P by adding the new partition point ξ = t k, so that a = x <... < x k < ξ < x k <... < x n = b. We can now use ξ as the tag for both subintervals [x k, ξ] and [x k, ξ] of Q. Since t k = ξ, and f(t k )(x k x k ) = f(ξ)(ξ x k ) + f(ξ)(x k ξ), 6

7 S(f; P) = S(f; Q). This process can also be reversed by merging two subintervals which share a tag ξ. In this case, the tag of the resulting subinterval will no longer be an endpoint. Thus, when using tagged partitions, we may assume any of the following: Every tag t k is an endpoint of a subinterval I k. No point t k is a tag for two distinct subintervals I k and I k+. Let f : I R be a real-valued function. We say that f is Riemann or R integrable on I if there is a real number A such that for every ɛ > there is a number δ ɛ > such that if P = {(I i, t i )} n i= is any tagged partition of I with P < δ ɛ, then S(f; P) A < ɛ. It can be shown that the number A is unique, and in this case, A = R or if it is clear that we are using a Riemann integral, b a f A = b Remark: If f is Riemann integrable on I then it is known that f is bounded on I. Using an alternate scheme, we can view the Riemann integral through the lens of the following terminology. a f. Let f : A R be a bounded real-valued function and A a non-empty subset of R. We define the oscillation of f on A to be ω f (A) = supf(x) inf f(x). x A x A Let f : I R be a bounded real-valued function. Let P be a partition of I. Then define M j = sup f(x), m j = inf f(x), x [x j,x j] x [x j,x j] 7

8 n n U(P; f) = M j x j and L(P; f) = m j x j j= j= where x j = (x j x j ). The following criteria for Riemann integrability is useful: f is Riemann integrable if and only if there exists a partition P of I such that for each ɛ >, U(P; f) L(P; f) < ɛ. We can rephrase the above criteria in terms of the oscillation since U(P; f) L(P; f) = = = n n M j x j m j x j j= j= n (M j m j ) x j j= n ω f ([x j, x j ]) x j. j= Let A R. The outer measure of A is defined to be { } inf l(i k ) A U k k= k= where {U k } k= is a collection of nonempty, open, bounded intervals. Let A R and f : A R a real-valued function. We call f a null function if the set {x A : f(x) } has outer measure zero. A subset A of R is said to be a null set if its outer measure is zero. Let f : I R. The variation of f over I is given by { n } V ar(f; I) = sup f(x i ) f(x i ) P = {x, x,..., x n } is a partition of I. i= If V ar(f; I) <, we say that f is of bounded variation on I. We denote the collection of functions on I that 8

9 are of bounded variation by BV(I). Let I = [a, b] R be a compact interval. Let f : I R be an HK integrable function (see section 4.) We say that f is absolutely integrable on I if f is also integrable on I. A function that is integrable on I but not absolutely integrable on I is said to be non-absolutely integrable on I. 3 GAUGES. We now discuss different methods of measuring the fineness of partitions. In the traditional approach to the Riemann integral, one measures the fineness of a partition P with regard to the mesh P of P in the sense that the length of each subinterval I k of P must be no greater than the length of P. In Lebesgue theory, the concept of fineness is developed from the theory of outer measure. In order to develop the Henstock-Kurzweil integral, we introduce the following terminology. Let I = [a, b] be a compact interval in R. (3.) Definition. A function δ : I (, ) is called a gauge. For each t I the interval around t controlled by the gauge δ is the interval B(t; δ(t)) = (t δ(t), t + δ(t)). (3.2) Definition. Let P = {(I i, t i )} n i= be a tagged partition of I. Given a gauge δ on I, we say that P is δ-fine if I i (t i δ(t i ), t i + δ(t i )) for all i =, 2,..., n. If a tagged partition P is δ-fine we say that P is subordinate to δ. (3.3) Definition. The Riemann integral relies on what is known as a constant gauge. Let I = [a, b] be a compact interval, and let δ be any positive real number. The function δ : I (, ) on I given by δ(t) = δ for all t I is a constant gauge on I. Any tagged partition P = {(I i, t i )} n i= on I will be subordinate to δ if and only if I i (t i δ, t i + δ ) = B(t i ; δ ) for all i =, 2,..., n. 9

10 One of the primary benefits of using gauges lies in their ability to force a given point to be a tag for a partition P. For example, let I = [a, b] R and let P = {(I i, t i )} n i= be a tagged partition of I. Let δ : I (, ) be given by 4 if t = a δ(t) = t a if a < t b. 2 Then, for any δ-fine partition P = {a = x < x <... < x n = b} of [a, b] the tag t for [a, x ] is forced to be t = a as we now show. To see this, since P is δ-fine, we must have that [a, x ] (t δ(t ), t + δ(t )). Hence, t δ(t ) < a, and this would imply t 2 t a < a or equivalently t a < 2 (t a) if a < t b, which is a contradiction. Thus, a must be the tag for [a, x ]. From this a very natural question arises. Given a compact interval I and a gauge δ : I (, ), is it always possible to find a tagged partition P which is δ-fine? The answer is yes, as given by the following theorem. (3.4) Cousin s Theorem. If I = [a, b] R is a nondegenerate compact interval, and δ is a gauge on I, then there exists a tagged partition of [a, b] that is δ-fine. For a proof of Cousin s Theorem, we refer the reader to []. Thus, given any compact interval [a, b] R, and a gauge δ on [a, b], a δ-fine partition of [a, b] always exists. Now that we have some preliminary definitions and results out of the way, we define the Henstock-Kurzweil integral. 4 THE HK INTEGRAL. We begin by defining the HK integral. Let I = [a, b] R be a compact interval. (4.) Definition. Let f : I R be a function. We say that f is Henstock-Kurzweil, HK, Gauge, or Generalized Riemann Integrable on I if there is some real number A such that for every ɛ > there is a gauge

11 δ ɛ : I (, ) such that if P = {(I i, t i )} n i= is any tagged partition of I that is δ ɛ-fine, then S(f; P) A < ɛ. As with the Riemann integral, one can show that A is unique. In this case, A = HK or if it is clear that we are using an HK integral, b a f A = b a f. In some cases, we can use an appropriately defined constant gauge δ and construct our partitions so that the length of the mesh is always smaller than δ. In this way, it is easy to see that the R integral is a special case of the HK integral. Indeed, in the definition of the R integral we defined our limit in terms of the mesh of a partition. However, after some reconsideration, we actually see that the mesh P of a partition P is just a constant gauge. In fact, by using gauges, we are making only a small change to the classic definition of the Riemann integral. However, this small change will prove to have large consequences. Intuitively, whether using the Riemann approach or the Henstock-Kurzweil approach, we are using the fineness of the subintervals of the partition over which the function is defined to approximate the integral. The Riemann approach measures that fineness by taking the mesh of the partition. So, the lengths of subintervals are all less than or equal to some real number. By using a gauge, we allow more variation in the lengths of those subintervals. In this way, we get a better approximation of the area beneath a curve via Riemann sums. For intervals upon which the curve is changing rapidly, we use subintervals with sufficiently small length and for intervals where the change is slow, we use subintervals of larger length. This turns out to be one of the key advantages of the HK integral. In addition, a gauge allows us to enclose a countable set of points A within a collection of subintervals {J k } j= so that k= J k has very small outer measure thus nullifying the effect that A has on the Riemann sums. This is a handy tool when dealing with discontinuities. Furthermore, as we have already shown, a gauge can force certain problem points to be tags. This allows us to deal with asymptotes. Finally, as we will see, the use of gauges will give an improved version of the Fundamental Theorem of Calculus. We now look at some of the important results tied to the HK integral.

12 5 PROPERTIES OF THE HK INTEGRAL. (5.) Theorem. Let I = [a, b] be a compact interval in R. Let A I be a set of outer measure zero. Let ϕ be defined as follows: if x A ϕ(x) = if x I \ A. Then, ϕ HK(I) and b a φ =. Proof: Let ɛ > be given. Let {J k } k= be a countable collection of open intervals such that A k= J k and l(j k ) < ɛ. k= We define a gauge on I as follows. If t I \ A, put δ ɛ (t) =. If t A, let k(t) be the smallest index k such that t J k and choose δ ɛ (t) > such that (t δ ɛ (t), t + δ ɛ (t)) J k(t). Now, let P = {(I i, t)} n i= be a δ ɛ-fine partition of I. If t I \ A, then ϕ(t) = and the Riemann sum ϕ(t i ) x i =. Since, P is δ ɛ -fine, if t A, t i I\A J k(ti) (t δ ɛ (t), t + δ ɛ (t)) I i. So, for each k N, the (nonoverlapping) intervals I i with tags in A J k have total length less than or equal to l(j k ) by countable subadditivity. So for each k N, the Riemann sum ϕ(t i ) x i l(j k ). Therefore, t i I k ϕ(t i ) x i + ϕ(t i ) x i l(j k ) l(j k ) < ɛ. t i I k t i I\A k= k= Thus, ϕ HK(I) and b a φ =. 2

13 The next result, the proof of which can be found in [] reveals one of the primary differences between the HK integral and the Lebesgue integral. (5.2) Theorem. Let k= a k be any convergent series. Say k= a k = A. Let us define a sequence {c n } n= as c n = 2 n. Now, let h : [, ] R be defined as follows: 2 k a k if x [c k, c k ) k N h(x) = if x = In this case, h HK([, ]) and h = A = a k. k= Another impressive result which comes from the HK integral is the so called Hake s Theorem. One can find the proof of this in [] (5.3) Hake s Theorem. A function f HK([a, b]) if and only if f HK([a, c]) for every c [a, b) and c lim f <. In this case, c b a b a f = lim c b c a f. Hake s Theorem tells us that the space HK(I) cannot be extended by adjoining improper integrals. If such an integral exists, then the integrand must already belong to HK(I). This is not so for Riemann and Lebesgue integrals. We now examine one of the most powerful aspects of the HK integral - the Fundamental Theorem of Calculus. 6 THE FUNDAMENTAL THEOREM OF CALCULUS. Unlike the R and L integrals, the HK integral can integrate every derivative. In order to fully formulate the Fundamental Theorem of Calculus for HK integrals, we first give some preliminary definitions. Let I = [a, b] R be a compact interval. (6.) Definition. Let F, f : I R. We say that F is a Primitive of f on I if F (x) exists and F (x) = f(x) for all x I. 3

14 (6.2) Definition. Let F, f : I R. We say that F is an a-primitive, c-primitive or f-primitive of f on I if F is continuous on I and there is a null, countable or finite set, respectively, E I so that F = f on I \ E. We call the set E the exceptional set for f. (6.3) Definition. Suppose that f HK(I) and let u I. The function F u : I R given by F u (x) = is called an indefinite integral of f with base point u. If the base point is the left endpoint of I or is well understood, then we may omit the subscript. Any function that differs from F u by a constant is called an indefinite integral of f. x u f We can now begin our discussion of the Fundamental Theorem of Calculus for HK integrals. To understand why we get an improved version of the Fundamental Theorem, we must first consider the classic definition of the derivative. (6.4) Definition. Given a differentiable function F : [a, b] R, we say that F is differentiable at t [a, b], with derivative f(t), if for all ɛ > there is a δ ɛ (t) > such that if < x t < δ ɛ (t), where x [a, b], then F (x) F (t) x t f(t) < ɛ. Notice that the number δ ɛ (t) can just as easily be thought of as a function of t and ɛ. Thus, if a function F is differentiable at a point t [a, b], there is a built-in gauge. It is this very idea that lies at the heart of the following result. (6.5) The Fundamental Theorem of Calculus I. Let I = [a, b] R be a compact interval. Let f : I R be a function. If f has a c-primitive F on I, then f HK(I) and b a f = F (b) F (a). () Notice that in the hypothesis of the Fundamental Theorem of Calculus for the HK integral we need not assume that f HK(I). This is not the case for the R integral, and for the Lebesgue integral additional 4

15 constraints are necessary to make equation () valid. Consequently, this version of the Fundamental Theorem of Calculus makes differentiation and integration truly inverse processes. Furthermore, we have the following version of the Fundamental Theorem of Calculus II. (6.6) The Fundamental Theorem of Calculus II. If f HK(I) then any indefinite integral F is continuous on I and is an a-primitive of f on I. Thus, there exists a null set A I such that F (x) = f(x) for all x I \ A. For the proofs of the above theorems, we refer the reader to []. Remark: A primary feature of the HK integral is its relationship to the c-primitive. The following statements are meant to add clarity to the subtle distinction between c-primitives and indefinite integrals. An HK integrable function f always has an indefinite integral and every indefinite integral of a function in HK(I) is an a-primitive. An HK integrable function does not always have a c-primitive. If F is a c-primitive of f : I R, then f HK(I) and F is an indefinite integral of f. If F is an a-primitive of f HK(I), then F need not be an indefinite integral of f. Examples or counterexamples for each of these assertions can be found in []. Now that we have discussed some preliminary results, we consider the effect of these results. We first show that R(I) HK(I). 7 FUNCTIONS WHICH ARE HK INTEGRABLE BUT NOT R INTEGRABLE. The very first integral that most mathematicians learn about is Riemann s. While the importance of the Riemann integral to a general theory of integration cannot be overemphasized, it is not without its 5

16 drawbacks. In this section we examine some of those drawbacks. We first show the power of the HK version of the Fundamental Theorem of Calculus. (7.) Example. Consider the function x 4 if x (, ] f(x) = if x =. Since f is not bounded, it fails to be Riemann integrable. Let F : [, ] R be given by F (x) = 4 3 x 3 4. Then, F is continuous on [, ] and F (x) = f(x) for all x (, ] but F () does not exist. Thus, F is an f-primitive for f on [, ] with exceptional set E = {}. Therefore, by the Fundamental Theorem of Calculus I for the HK integral (6.5), f(x) dx = F () F () = 4 3. In practice, we write x 4 dx with the understanding that the integrand is zero at x =. In any undergraduate real analysis course, students learn that the Riemann integral can handle any function with a finite number of discontinuities. This idea is later extended by saying that the set of discontinuities of a Riemann integrable function must have measure zero. Using this idea, we can create bounded functions which are not Riemann integrable. To show that such functions are actually HK integrable we construct a gauge which will enclose the points of discontinuity in a set with small outer measure making the contribution of said discontinuities to the Riemann sums negligible. To illustrate the full power of this technique, we will now construct such a function. (7.2) Example. Let A be a countable, dense subset of [, ]. Examples include, but are not limited to, the algebraic numbers and the rational numbers. We claim that the following function is HK integrable but not R integrable. if x A f(x) = if x [, ] \ A 6

17 Proof: We begin by showing that f is not R integrable. To this end, let ɛ = 2, and let P = {I i} n i= be a partition of [, ]. Since A and [, ] \ A are both dense in [, ], for each subinterval I i induced by P, I i contains both an element of A and an element of [, ] \ A. So, M i = and m i = for i =, 2,..., n. Clearly, L(P; f) =, and U(P; f) = = = n M i x j j= n x j j= n x j j= = ( ) =. Thus, U(P; f) L(P; f) = =. Since P was arbitrary, we see that U(P; f) L(P; f) ɛ = 2 for all partitions P. Therefore, f is not Riemann integrable on [, ]. It is clear, by Theorem (5.), that f HK([, ]). We will now examine this assertion in further detail by using an explicit gauge. Since A is a countable set, it is enumerable. Let A = {r, r 2,...} be an enumeration of A. Let ɛ > be given. Consider the following gauge on [, ]. if t [, ] \ A δ ɛ (t) = ɛ if t = r 2 k+ k A. Let P be a δ ɛ -fine, tagged partition of [, ]. Since f = on [, ] \ A, the tags in [, ] \ A contribute nothing to the Riemann sum of f induced by P. So, since P is δ ɛ -fine, we need only to consider the following sum: S(f; P) ɛ 2 k = ɛ. k= Therefore, f HK([, ]) and f =. 7

18 In the above example, we constructed a gauge which allowed us to nullify the effect that the points of A had on the Riemann sums. By doing this, we have effectively made f identically zero on [, ]. However, this is not surprising since, alternatively, we could have shown that f HK([, ]) using Theorem (6.5) and considering the function F (x) = for all x [, ]. Notice that F is a c-primitive for f on [, ] with exceptional set A. Hence, by the HK version of the Fundamental Theorem of Calculus, f(x)dx = F () F () =. We have now shown that R(I) HK(I). However, the above functions, or variations therein, are so well known that in some sense they are trivial examples. We now construct one final example which will show the power of the Fundamental Theorem of Calculus for HK integrals. The following is a bounded function which is the derivative of another function, yet which is not Riemann integrable. The initial construction of this function was suggested by Goffmann.[2] (7.3) Example. We now construct an oscillating function on a set of positive outer measure by using a method similar in spirit to the construction of the classic Volterra function. We begin with the unit interval, which we denote by K = [, ]. Consider x = 2, the midpoint of K. First, we delete the interval G = I = ( 3 8, 5 8 ) from K. Note that I is symmetric about x and l(i ) = 4. We are now left with two closed intervals, K 2 = [, 3 8 ] and K 3 = [ 5 8, ]. Let L = K 2 K 3. Let x 2 = 3 6 and x 3 = 3 6, the midpoints of K 2 and K 3 respectively. We now delete the open intervals I 2 = ( 5 32, 7 32 ) and I 3 = ( 25 32, ), which are symmetric about x 2 and x 3, from K 2 = [, 3 8 ] and K 3 = [ 5 8, ] respectively. Note that l(i k ) = 6 = [l(i )] 2 for k = 2, 3. Let G 2 = I 2 I 3 = ( 5 32, 7 ) ( , 27 ). 32 8

19 This leaves us with the four closed intervals K 4 = [, 5 ] [ 7, K 5 = 32 32, 3 ] [ ] [ ] 5, K 6 = 8 8, and K 7 = 32 32,. Let L 2 = K 4 K 5 K 6 K 7. Let x 4 = 5 64, x 5 = 9 64, x 6 = and x 7 = which are the midpoints of K 4, K 5, K 6, and K 7 respectively. Next, we delete the open intervals I 4 = ( 9 28, ) ( 37, I 5 = 28 28, 39 ) ( 89, I 6 = 28 28, 9 ) ( 7 and I 7 = 28 28, 9 ) 28 from K 4 = [, 32] 5, K5 = [ 7 32, ] 3 8, K6 = [ 5 8, ] and K7 = [ 27 32, ] respectively. Note that l(i k ) = 64 = [l(i )] 3 for k = 4, 5, 6, 7. Let G 3 = I 4 I 5 I 6 I 7 = ( 9 28, ) ( , 39 ) ( , 9 ) ( , 9 ). 28 If we continue this process inductively, we obtain the following construction: G = I. G n = I 2 n I 2 n +... I 2 n +(2 n ) for n 2, where n N. l(i k ) = [l(i )] n = ( 4) n where k = 2 n, 2 n +..., 2 n + (2 n ) for each n N. I j I k = for all j k G j G k = for all j k. For each n N, we define λ (G n ) to be the outer measure of G n. Since G n is the union of 2 n disjoint open 9

20 intervals, each of length [l(i )] n = ( 4) n, by countable additivity, λ (G n ) = 2 n [l(i )] n = 2 n ( 4 = ) n ( ) n+. 2 Now, let us define the set G = G k. k= By countable additivity, ( ) λ (G) = λ G k = = k= λ (G k ) k= k= = 2. ( ) k+ 2 Notice that after the nth iteration in the construction of G we are left with a set L n, a union of 2 n closed intervals each of which we denoted by K k for some k N. Then, K = L n = [, ] \ G n= is a fat Cantor set with outer measure λ (K) = 2. Since the Cantor set is known to be totally disconnected, its only connected sets are singletons. Thus, given any point x [, ]\G, and any open interval U = (x ɛ, x+ɛ) containing x, U G. Hence, x cl(g) and [, ] cl(g). Clearly, [, ] cl(g). So, [, ] = cl(g) and G is dense in [, ]. Thus, G has the following properties: G is a union of pairwise disjoint open intervals. G is dense in [, ]. G has outer measure λ (G) = 2. 2

21 We can now begin constructing a bounded function f which is the derivative of another function, but which is not Riemann integrable. We begin with the open interval I = ( 3 8, 5 8 ) of length 4, and the point x = 2 which is the midpoint of I. Let J = [ 5 32, 7 32 ] be the closed interval of length 6 = ( ) 2 4 = [l(i )] 2 which is symmetric about x = 2. Define f( 2 on the open intervals ( 5 32, 2 ) and ( 2, ) =, f( 32 ) = f( 32 ) =. Let f be linear and continuous ) connecting f( 5 32 ) to f( 2 ) and f( 2 7 ) to f( 32 ) respectively. Define f = on I \ J. Next, consider the open intervals I 2 = ( 5 32, 7 32 ) and I 3 = ( 25 32, ), each of length 6, which are symmetric about x 2 = 3 6 and x 3 = 3 6 respectively. From I 2 and I 3, we construct the closed intervals J 2 = [ 23 28, ] and J 3 = [ 3 28, 5 28 ] of length 64 = ( 6) 2 = [l(ik )] 2, for k = 2, 3, symmetrically about x 2 and x 3, respectively. Define f( ) = f( 6 ) =, f( 28 ) = f( 28 and continuous on the open intervals ( 23 28, 3 6 ), ( 3 6, ), ( f( ) to f( 28 ), f( 3 28 ) to f( , 3 6 ) = f( 3 28 ), and ( 3 6, ) = f( 28 ) =. Let f be linear ), connecting f( ) to f( 3 6 ), 3 5 ), and f( 6 ) to f( 28 ). Finally, define f to be identically zero on I k \ J k where k = 2, 3. Continuing this process inductively, we obtain the following construction: Let I n be the nth open interval, of length ( 4) n in the construction of G. Let Jn = [a n, b n ] I n be a closed interval which is symmetric about the midpoint x n of I n so that l(j n ) = [l(i n )] 2 = [( 4) n ] 2 for each n N. Define the function f : [, ] [, ] follows: Let f(x n ) = and f(a n ) = f(b n ) = for each n. Let f be linear and continuous on the open intervals (a n, x n ) and (x n, b n ) connecting f(a n ) = to f(x n ) = and f(x n ) = to f(b n ) =. Define f(x) = for all x I n \ J n. Finally, define f = on [, ] \ G. Since f(x) for all x [, ], f is bounded on [, ]. Our function can be seen in the following diagram: Figure : HK integrable but not R integrable 2

22 We claim that f is not Riemann integrable. To see this, first let O be an open subset of [, ] such that O K. Since O is open, we can find distinct points x and y in O K. Without loss of generality, suppose that x < y. Then, since K is a Cantor-like set, it contains no isolated points and is totally disconnected. So, by construction of G, J n I n (x, y) O for some positive integer n. Let P = { = x < x <... < x n = b} be any partition of [, ]. Now, let us consider n K \ {} = K \ {} [x j, x j ) j= n = [(K \ {}) [x j, x j )]. j= Recall, λ (G) = 2. So, λ (K) = λ ([, ] \ G) = 2. Thus, 2 = λ (K) = λ (K \ {}) n = λ (K \ {}) [x j, x j )) j= K (x j,x j) l((x j, x j )). When K (x j, x j ), we can find a positive integer n = n(j) such that J n I n (x j, x j ). Therefore, M j = and m j =, when K (x j, x j ). 22

23 Hence, U(P; f) L(P; f) = = n (M j m j ) x j j= 2. (M j m j ) x j K (x j,x j) K (x j,x j) x j Thus, f R([, ]). We now show that f is the derivative of the following improper integral. Consider the function F (x) = f(t)dt. k= J k [,x] We claim that F (x) = f(x) for all x [, ]. Choose an open interval I [, ] so that I ([, ] \ G). Then, I I n J n for some positive integer n. Choose n N so that I J n and let S n = l(i n ). Then, by construction, S n 2. Hence, from the fact that x 2 if and only if 2(x x2 ) x, we conclude that 2 [S n [S n ] 2 ] 4 S n. Now, I ([, ] \ G), I J n, and l(j n ) = [l(i n )] 2 = [S n ] 2. So, l(i I n ) 2 l(i n) 2 [l(j n)] = 2 [S n [S n ] 2 ] 4 S n since I n and J n are both symmetric about the midpoint of I n. Therefore, 6[l(I I n )] 2 S 2 n, (2) and by monotonicity, l(i J n ) l(j n ) = [S n ] 2. 23

24 Hence, with this last inequality together with (2), we conclude l(i J n ) l(j n ) = [S n ] 2 6[l(I I n )] 2. Now, consider the set J = {n N : I J n }. Then, l(i J n ) 6 [l(i I n )] 2 n J n J [ 6 l(i I n ) n J n J ] 2 [ ( )] 2 λ I I n = 6 [λ ( I )] 2 I n n J 6[l(I)] 2. (3) We now show that F (x) = f(x) for all x [, ]. Let x [, ] \ G, and let y [, ] with y x. Without loss of generality assume x < y. Then, F (y) F (x) = n J J n [,y]f(t)dt n J = f(t)dt n J J n [,y] f(t)dt = n J n J J n [x,y] l(j n [x, y]). J n [,x] J n [,x] f(t)dt f(t)dt By assumption, x < y. So F (x) F (y) and F (y) F (x). Therefore, since f(t) for all t, F (y) F (x) y x = y x n J J n [x,y] f(t)dt y x n J l ([x, y] J n ) y x 6(y x)2 6(y x), by (3). 24

25 Note: By using the closed interval [x, y], rather than the open interval (x, y), we have not changed the outer measure of (x, y), so the result still holds by (3). Thus, F (y) F (x) y x 6(y x). Then, F F (y) F (x) (x) = lim lim 6(y x) =. y x y x y x Therefore, since f(x) = for all x [, ] \ G, F (x) = f(x) for all x [, ] \ G. Now, let x G. Consider F (x) = n J f(t)dt. J n [,x] Since x G, x I n for some n N. Note that if x I n \ J n for some n N, then F (x) = f(x). So, let x J n, and suppose x > x. Then F (x) F (x ) = n J f(t)dt = J n [x,x] x x f(t)dt, since f on I n \ J n. So, x F (x) = F (x ) + f(t)dt. x Since f is continuous on each I n, we may apply the Fundamental Theorem of Calculus II, giving us F (x) = d ( d x ) (F (x)) = F (x ) + f(t)dt dx dx x = + f(x). Thus, F (x) = f(x). If x x we may use the above proof with the identity x F (x ) F (x) = f(t)dt. x 25

26 Therefore, F (x) = f(x) for all x G, so F (x) = f(x) for all x [, ]. Hence, f is the derivative of F on [, ]. In other words, F is the primitive of f on [, ]. Hence, by The Fundamental Theorem of Calculus for HK integrals, and Hake s Theorem, f HK([, ]). The above examples not only show some of the most powerful applications of gauges, but also the deficiencies of the Riemann integral. The previous function f definitely seems like it should be Riemann integrable, we are after all simply adding up the areas of triangles, but we have shown that it is not. The function oscillates much too wildly on a set with positive outer measure. However, the function does belong to HK([, ]). Furthermore, in Example (7.2) we showed that the Henstock-Kurzweil integral is able to handle certain pathological functions that the R integral simply cannot. In that example, we constructed a gauge which encloses each point of A in an open interval with arbitrarily small length. By doing that, we obtained a collection of sets whose union has an arbitrarily small outer measure, ultimately rendering the effect that the set A has on the Riemann sums of a partition P negligible. However, these examples have revealed something deeper. The use of gauges allows us to bridge the very small gap between HK(I) and L(I). In fact, as we will now show, it is only a class of highly oscillatory functions which lie in the space between. 8 FUNCTIONS WHICH ARE HK INTEGRABLE BUT NOT L INTEGRABLE. In any basic measure theory class, one learns about the Lebesgue integral in steps. For brevity, we characterize the class of Lebesgue integrable functions in terms of the HK integral. The proof of this assertion can be found in [5]. (8.) Theorem. Let I = [a, b] R be a compact interval. Let f : I R be a function defined on I. Then, f is Lebesgue integrable if and only if f is HK integrable. In either case, the integrals agree. An application of this result will help us to show that HK(I) is a space of non-absolutely integrable functions. Consequently, L(I) is a space of absolutely integrable functions. Hence, a function f can be Henstock- Kurzweil integrable without f being Henstock-Kurzweil integrable, but this is not true for Lebesgue integrable functions. In this way, we can think of HK(I) as being analogous to the class of conditionally convergent series and L(I) as being analogous to the class of absolutely convergent series. To classify those functions which are absolutely integrable, we employ the following result. 26

27 (8.2) Theorem. Let I = [a, b] R be a compact interval. Let f : I R be a function defined on I. Let f HK(I). Then, f is HK integrable if and only if the indefinite integral F (x) = has bounded variation on I. In this case, x a f b a f = V ar(f ; I). The proof of this assertion can be found in []. Thus, Theorem 8. and Theorem 8.2 together show that if F is of bounded variation on I, then F is Lebesgue integrable on I. Using these characterizations, we look at some functions which are HK integrable but not Lebesgue integrable. (8.3) Example. Consider the function F : [, ] R given by x 2 cos ( ) π x if x (, ] F (x) = 2 if x =. This function has a derivative given by: 2x cos ( ) π x + 2π f(x) = 2 x sin ( ) π x if x (, ] 2 if x =. We claim that F is not of bounded variation on [, ], which will in turn implies that F = f L([, ]). To 27

28 see this, consider the sequence x k = k where k =, 2,..., N. Then, N N F (x k ) F (x k+ ) = k k= = = k= N k= cos kπ k + ( k + ( + 2 = 2() + 2 = 2 N k= ) k + ) ( ) 3 ( ) ( k + N +. cos(k + )π ( + ) ( N ) ( N + ) N + ) + N + Since the harmonic series diverges, we see that this series goes to + as N +. Thus, F is not of bounded variation on [, ]. So, f = F L([, ]). However, according to the Fundamental Theorem of Calculus I for HK integrals, since F is a primitive for f on [, ], we see that f = F does belong to HK([, ]), and HK f(x)dx = F () F () =. In the spirit of Theorem (5.2), we will now construct another example of a function which is not Lebesgue integrable but is HK integrable. This example illustrates the strength of non-absolute integrability. (8.4) Example. Consider n= ( ) n+ log n. n We claim that this series is not absolutely convergent. Consider ( ) n log n n = n= n= log n n. For all n 3, log n n n. Since the series n= n is known to diverge, by the comparison test, n= log n n diverges as well. Thus, n= ( ) n+ log n n 28

29 is not absolutely convergent. However, letting a n = log n, we see that lim a log n n = lim n n n =. n Letting f(x) = log x x, f (x) = log x x, and 2 since f (x) < for all x > e, a n is a decreasing sequence. So, by the alternating series test, n= ( ) n+ log n n is a convergent series. Thus, by Theorem 5.2, the function κ : [, ] R given by: 2 k ( ) k+ log k k if x [c k, c k ) for k N κ(x) = if x = where c k = 2 k is HK integrable. However, we claim that κ is not absolutely integrable, hence not Lebesgue integrable. To see this, let K(x) = x κ(t)dt be an indefinite integral for κ with base point. Note that K() = and Now, consider K(c n ) = n K(c n ) K(c n ) = k= = log n n n k= ( ) k+ log k. k ( ) k+ log k k n k= ( ) k+ log k k Using parts of our sequence c k as a partition of [, ], we set P = { = y, y,..., y n = } where y =, y = c, y 2 = c 2,..., y n = c n, y n =. 29

30 Then, n i= K(y i ) K(y i ) + log log log(n 2) n 2 + log(n ). n Taking n, we see that K BV([, ]), since log n n= n diverges. Therefore, κ is not HK integrable on [, ]. Hence, κ is not Lebesgue integrable on [, ]. However, by Theorem (5.2), since ( ) n+ log n n= n does converge, κ HK([, ]) and HK κ = k= where γ is the Euler-Mascheroni constant given by γ = lim n [ n k= ( ) n+ log n n = γ log 2 [log 2]2 2 ] k log n.5772 (see[8].) Here, κ fails to be Lebesgue integrable because κ is not HK integrable. However, upon deeper inspection, we realize that κ fails to be HK integrable because x κ BV([, ]). Indeed, by simply looking at the first few partial sums we can see that the function oscillates wildly. The following diagram shows the graph of K(c 2 ) : Figure 2: K(c 2 ) We will now look at one final function which belongs to HK(I) but not L(I). In the process we show the power of Hake s Theorem. (8.5) Example. Consider the following function. 3

31 x f(x) = sin ( ) x if x 3 if x =. We cannot express the integral x f with elementary functions. However, consider the function g(x) = x sin t dt. t It is a commonly known fact that lim g(x) = π x 2 [9]. Armed with this fact, we can now evaluate the integral of f as an improper Riemann integral in the following manner. Let t = x, then 3 ( ) x sin x 3 dx = 3 ( = 3 sin t dt t ) lim g(x) g() x = (π 2g()) <. 6 Now, let u = x and dv = sin x dx. Then, du = x 2 and v = cos x, and we have A sin x x dx = cos x x = cos A A cos A A cos x dx x 2 A cos x x 2 dx. Now, exists since and A cos x cos x lim A x 2 dx = x 2 dx cos x x 2 x 2 on [, ), dx <. x2 3

32 So, A lim A cos x x 2 dx converges. Hence, ( ) x sin x 3 dx = 3 = 3 ( sin t dt = t 3 lim cos cos A A A A ( cos ) cos x x 2 dx. ) cos x x 2 dx So, f is improper Riemann integrable, and Hake s Theorem guarantees that it is a proper HK integral. However, f is not Lebesgue integrable. To see this, we use the fact that a Lebesgue integrable function must be absolutely integrable. For k N consider (k+)π π sin t t dt = = = k j= jπ π k j= π k j= (j+)π sin t t dt. Then, letting u = t jπ, du = dt. So sin(u + jπ) du u + jπ sin u du, since u π. u + jπ So, since u+jπ (j+)π for u π, we have k j= π sin u u + jπ du 2 π k j= (j + )π k j= j +. π sin u du So, k j= (j+)π jπ sin t t dt = 2 π k j= j +. 32

33 Therefore, ( ) x sin x 3 dx = 3 = 3 = 3 2 3π π π sin t t dt sin t t dt + n 3 j= sin t t dt + 2 n 3π n j= j +. j= (j+)π jπ j + sin t t dt Taking n, we see that ( ) x sin x 3 dx diverges since the harmonic series is divergent. So, f is not absolutely integrable hence not Lebesgue integrable. Again the function is not L integrable because x f BV([, ]). Notice, in the above example, we have inadvertently found a function which does not belong to HK([, ]). Namely, For if h HK([, ]), then both and ( ) h(x) = x sin x 3. ( ) h(x) = x sin x 3 x f(x) = sin ( ) x if x 3 if x = belong to HK([, ]), which would imply that f L([, ]). However, as we just showed, this is not the case. Therefore, h HK([, ]). This illustrates an important point. Although the HK integral is a very powerful tool, it cannot integrate every function. Since it is a well known fact that R(I) L(I), we have shown that R(I) L(I) HK(I). We conclude the paper by discussing various strengths of the HK integral over the R and L integrals in applied mathematics. 33

34 9 APPLICATIONS OF THE HK INTEGRAL. Until now, we have mainly examined the differences between the HK integral and the classic Riemann and Lebesgue integrals by using pathological functions. However, Kurzweil originally developed the HK integral as a way to solve complicated differential equations. Indeed, due to the improved Fundamental Theorem of Calculus, the HK integral is a powerful tool for solving differential equations especially those involving highly oscillatory functions. (9.) Example. Recall from Example (8.3), the function F : [, ] R be given by: x 2 cos ( ) π x if x (, ] F (x) = 2 if x = with derivative 2x cos ( ) π F x 2π (x) = 2 x sin( π x ) if x (, ] 2 if x =. Now, consider the initial value ODE: y (t) = t 2 y(t) + F (t), y() =, and t. Recall that F is not Lebesgue integrable. So, F (x, t) = t 2 y(t) + F (t) cannot be solved by Lebesgue or Riemann integration. However, consider the following function: y(t) = e t3 3 [ HK t ] e s3 3 F (s)ds. Then, y() = and y (t) = t 2 e t3 3 [ HK t ] e s3 3 F (s)ds + e t3 3 [ d HK dt t ] e s3 3 F (s)ds. Now, by the Fundamental Theorem of Calculus II for HK integrals, [ d HK dt t ] e s3 3 F (s)ds = e t3 3 F (t), 34

35 and y (t) = t 2 e t3 3 [ HK t ] [ e s3 3 F (s)ds + e t33 e t33 F (t) = t 2 e t3 3 ( HK t )] e s3 3 F (s)ds + F (t), or equivalently, y (t) = t 2 y(t) + F (t), t, and y() =. Thus, y(t) = e t3 3 [ HK t ] e s3 3 F (s)ds is indeed a solution to the aforementioned ODE. Although differential equations play an important part in the applicability of the HK integral, working mathematicians who regularly study the HK integral and its applications are also making headway in areas such as probability, statistics, physics and finance. For example, a Brownian motion X = (X t )( < t, X = ) with drift rate (rate at which the average changes) µ t and variance σ t can be constructed from a standard Brownian motion W = (W t ) by the equation: X t = t σ s dw s + t Although the first integral is L integrable, the second, which is called a Stochastic integral, is not. Almost all of the sample paths given by x(s)( < s t, x() = ) - which are continuous functions between topological spaces that produce a set of values according to the rules of the process - are of unbounded variation. So, for any path x if µ x ((u, v]) µ s ds. is even as simple as x(v) x(u), then the integral t dµ x does not exist. This is due to the fact that the Lebesgue integral is an absolutely convergent integral. When considered seperately, the sums of all paths x so that x(v) x(u) 35

36 and x(v) x(u) < diverge to and respectively. However, when considered as a HK integral, the integral exists. Indeed, given a partition P = { = u, u,..., u n = t} of [, t], n µ x ((u j, u j ]) = x(u ) x(u ) + x(u 2 ) x(u ) x(u n ) x(u n ) j= = x(u n ) x(u ) = x(t). So, it turns out that t dµ x is finite and is equal to x(t). In terms of Brownian motion, the stochastic integral on (, t] is given by t dw s = W t. Furthermore, much research has been done on the uses of the HK integral in quantum mechanics. Particularly when considering transforms and Feynman paths, which are often highly oscillatory by nature. FINAL COMMENTS. The HK integral is one of the most powerful methods of integration currently being researched by mathematicians. By using gauges, one can evaluate functions on more of a local level than one can with the traditional Riemann integral. This seemingly small change to the traditional definition of the Riemann integral has proven to have far reaching consequences. For example, the HK integral makes integration and differentiation truly inverse processes. The fact that the HK integral is a non-absolutely convergent integral makes it ideal for integrating functions which oscillate wildly, a feature not always available with the L integral. This allows one to look at the integration process as a whole, rather than being forced to consider the negative and nonnegative cases separately as is often the case in Lebesgue integration theory. However, this advantage does have its drawbacks. To date no one has developed a suitable norm for the space HK(I). However, all of the above results can be generalized to R n along with HK versions of Fubini s Theorem for iterated 36

37 integrals and the Divergence Theorem similar to the ones learned in second or third year calculus courses. In addition, Hake s theorem tells us that there are no improper HK integrals, another result unavailable in R and L integration theory. Furthermore, the definition of the Henstock-Kurzweil integral is relatively simple and requires no knowledge of measure theory making it a viable alternative to the traditional Riemann integral. In fact, there is a petition to replace the R integral in undergraduate analysis courses with the HK integral. The use of gauges may help students develop a deeper understanding of epsilon-delta style proofs, and give them some rudimentary intuition about outer measure. The HK integral s ability to integrate functions of a highly oscillatory nature has proven to be a valuable tool in many areas of applied mathematics including differential equations, stochastic probability and quantum mechanics. Although, no one has found a suitable norm for the space of Henstock-Kurzweil integrable functions, there are semi-norms available. Even so, one cannot deny the Henstock integral s value as an important supplement to the theory of integration. Although the HK integral may not be the apotheosis of integration theory, it is an important mathematical tool with far reaching consequences. Its sheer simplicity and ability to generalize all previous integrals make it an important addition to integration theory, and although the HK integral cannot totally replace the Lebesgue integral, it is a tool that should be considered by any serious student of integration theory. 37

38 References [] Bartle, R. G., A Modern Theory of Integration, American Mathematical Society, Rhode Island 2. [2] Goffman, C., A Bounded Derivative Which is Not Riemann Integrable, The American Mathematical Monthly, Vol. 84 No. 3, March 977, pps [3] Rudin, W., Principles of Mathematical Analysis, McGraw-Hill Inc., New York, 976. [4] Royden, H.L., Fitzpatrick, P.M, Real Analysis, New Jersey, 2. [5] Kurtz, D.S., Swartz, C.W., Theories of Integration: The Integrals of Riemann, Lebesgue, Henstock- Kurzweil, and McShane, World Scientific, New Mexico, 24. [6] Myers, T., The Gauge Integral and its Relationship to the Lebesgue Integral, Google Books, California, 27 [7] Dummit, D.S., Foote, R.M.,Abstract Algebra, John Wiley and Sons Inc., New Jersey, 24. [8] Gourdon,X., Sebah,P., (April 24), Numbers, Constants and Computation, numbers.computation.free.fr, [9] LOYA, P., (Feb. 25), Dirichlet and Fresnel Integrals via Iterated Integration, Mathematics Magazine, VOL. 78, NO., 38

Mathematical Methods for Physics and Engineering

Mathematical Methods for Physics and Engineering Mathematical Methods for Physics and Engineering Lecture notes for PDEs Sergei V. Shabanov Department of Mathematics, University of Florida, Gainesville, FL 32611 USA CHAPTER 1 The integration theory

More information

Bounded Derivatives Which Are Not Riemann Integrable. Elliot M. Granath. A thesis submitted in partial fulfillment of the requirements

Bounded Derivatives Which Are Not Riemann Integrable. Elliot M. Granath. A thesis submitted in partial fulfillment of the requirements Bounded Derivatives Which Are Not Riemann Integrable by Elliot M. Granath A thesis submitted in partial fulfillment of the requirements for graduation with Honors in Mathematics. Whitman College 2017 Certificate

More information

convergence theorem in abstract set up. Our proof produces a positive integrable function required unlike other known

convergence theorem in abstract set up. Our proof produces a positive integrable function required unlike other known https://sites.google.com/site/anilpedgaonkar/ profanilp@gmail.com 218 Chapter 5 Convergence and Integration In this chapter we obtain convergence theorems. Convergence theorems will apply to various types

More information

Measure and integration

Measure and integration Chapter 5 Measure and integration In calculus you have learned how to calculate the size of different kinds of sets: the length of a curve, the area of a region or a surface, the volume or mass of a solid.

More information

Final. due May 8, 2012

Final. due May 8, 2012 Final due May 8, 2012 Write your solutions clearly in complete sentences. All notation used must be properly introduced. Your arguments besides being correct should be also complete. Pay close attention

More information

II - REAL ANALYSIS. This property gives us a way to extend the notion of content to finite unions of rectangles: we define

II - REAL ANALYSIS. This property gives us a way to extend the notion of content to finite unions of rectangles: we define 1 Measures 1.1 Jordan content in R N II - REAL ANALYSIS Let I be an interval in R. Then its 1-content is defined as c 1 (I) := b a if I is bounded with endpoints a, b. If I is unbounded, we define c 1

More information

MORE ON CONTINUOUS FUNCTIONS AND SETS

MORE ON CONTINUOUS FUNCTIONS AND SETS Chapter 6 MORE ON CONTINUOUS FUNCTIONS AND SETS This chapter can be considered enrichment material containing also several more advanced topics and may be skipped in its entirety. You can proceed directly

More information

The Gauge Integral of Denjoy, Luzin, Perron, Henstock and Kurzweil

The Gauge Integral of Denjoy, Luzin, Perron, Henstock and Kurzweil The Gauge Integral of Denjoy, Luzin, Perron, Henstock and Kurzweil Tim Sullivan tjs@caltech.edu California Institute of Technology Ortiz Group Meeting Caltech, California, U.S.A. 12 August 2011 Sullivan

More information

3 (Due ). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure?

3 (Due ). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure? MA 645-4A (Real Analysis), Dr. Chernov Homework assignment 1 (Due ). Show that the open disk x 2 + y 2 < 1 is a countable union of planar elementary sets. Show that the closed disk x 2 + y 2 1 is a countable

More information

Some Background Material

Some Background Material Chapter 1 Some Background Material In the first chapter, we present a quick review of elementary - but important - material as a way of dipping our toes in the water. This chapter also introduces important

More information

The Lebesgue Integral

The Lebesgue Integral The Lebesgue Integral Brent Nelson In these notes we give an introduction to the Lebesgue integral, assuming only a knowledge of metric spaces and the iemann integral. For more details see [1, Chapters

More information

MAT1000 ASSIGNMENT 1. a k 3 k. x =

MAT1000 ASSIGNMENT 1. a k 3 k. x = MAT1000 ASSIGNMENT 1 VITALY KUZNETSOV Question 1 (Exercise 2 on page 37). Tne Cantor set C can also be described in terms of ternary expansions. (a) Every number in [0, 1] has a ternary expansion x = a

More information

Lebesgue Measure on R n

Lebesgue Measure on R n CHAPTER 2 Lebesgue Measure on R n Our goal is to construct a notion of the volume, or Lebesgue measure, of rather general subsets of R n that reduces to the usual volume of elementary geometrical sets

More information

MAT 570 REAL ANALYSIS LECTURE NOTES. Contents. 1. Sets Functions Countability Axiom of choice Equivalence relations 9

MAT 570 REAL ANALYSIS LECTURE NOTES. Contents. 1. Sets Functions Countability Axiom of choice Equivalence relations 9 MAT 570 REAL ANALYSIS LECTURE NOTES PROFESSOR: JOHN QUIGG SEMESTER: FALL 204 Contents. Sets 2 2. Functions 5 3. Countability 7 4. Axiom of choice 8 5. Equivalence relations 9 6. Real numbers 9 7. Extended

More information

Theorems. Theorem 1.11: Greatest-Lower-Bound Property. Theorem 1.20: The Archimedean property of. Theorem 1.21: -th Root of Real Numbers

Theorems. Theorem 1.11: Greatest-Lower-Bound Property. Theorem 1.20: The Archimedean property of. Theorem 1.21: -th Root of Real Numbers Page 1 Theorems Wednesday, May 9, 2018 12:53 AM Theorem 1.11: Greatest-Lower-Bound Property Suppose is an ordered set with the least-upper-bound property Suppose, and is bounded below be the set of lower

More information

i. v = 0 if and only if v 0. iii. v + w v + w. (This is the Triangle Inequality.)

i. v = 0 if and only if v 0. iii. v + w v + w. (This is the Triangle Inequality.) Definition 5.5.1. A (real) normed vector space is a real vector space V, equipped with a function called a norm, denoted by, provided that for all v and w in V and for all α R the real number v 0, and

More information

Math212a1413 The Lebesgue integral.

Math212a1413 The Lebesgue integral. Math212a1413 The Lebesgue integral. October 28, 2014 Simple functions. In what follows, (X, F, m) is a space with a σ-field of sets, and m a measure on F. The purpose of today s lecture is to develop the

More information

Real Analysis Math 131AH Rudin, Chapter #1. Dominique Abdi

Real Analysis Math 131AH Rudin, Chapter #1. Dominique Abdi Real Analysis Math 3AH Rudin, Chapter # Dominique Abdi.. If r is rational (r 0) and x is irrational, prove that r + x and rx are irrational. Solution. Assume the contrary, that r+x and rx are rational.

More information

Indeed, if we want m to be compatible with taking limits, it should be countably additive, meaning that ( )

Indeed, if we want m to be compatible with taking limits, it should be countably additive, meaning that ( ) Lebesgue Measure The idea of the Lebesgue integral is to first define a measure on subsets of R. That is, we wish to assign a number m(s to each subset S of R, representing the total length that S takes

More information

Lebesgue Integration on R n

Lebesgue Integration on R n Lebesgue Integration on R n The treatment here is based loosely on that of Jones, Lebesgue Integration on Euclidean Space We give an overview from the perspective of a user of the theory Riemann integration

More information

Lebesgue measure and integration

Lebesgue measure and integration Chapter 4 Lebesgue measure and integration If you look back at what you have learned in your earlier mathematics courses, you will definitely recall a lot about area and volume from the simple formulas

More information

Construction of a general measure structure

Construction of a general measure structure Chapter 4 Construction of a general measure structure We turn to the development of general measure theory. The ingredients are a set describing the universe of points, a class of measurable subsets along

More information

Metric Spaces and Topology

Metric Spaces and Topology Chapter 2 Metric Spaces and Topology From an engineering perspective, the most important way to construct a topology on a set is to define the topology in terms of a metric on the set. This approach underlies

More information

van Rooij, Schikhof: A Second Course on Real Functions

van Rooij, Schikhof: A Second Course on Real Functions vanrooijschikhof.tex April 25, 2018 van Rooij, Schikhof: A Second Course on Real Functions Notes from [vrs]. Introduction A monotone function is Riemann integrable. A continuous function is Riemann integrable.

More information

We are going to discuss what it means for a sequence to converge in three stages: First, we define what it means for a sequence to converge to zero

We are going to discuss what it means for a sequence to converge in three stages: First, we define what it means for a sequence to converge to zero Chapter Limits of Sequences Calculus Student: lim s n = 0 means the s n are getting closer and closer to zero but never gets there. Instructor: ARGHHHHH! Exercise. Think of a better response for the instructor.

More information

Measure Theory and Lebesgue Integration. Joshua H. Lifton

Measure Theory and Lebesgue Integration. Joshua H. Lifton Measure Theory and Lebesgue Integration Joshua H. Lifton Originally published 31 March 1999 Revised 5 September 2004 bstract This paper originally came out of my 1999 Swarthmore College Mathematics Senior

More information

LEBESGUE MEASURE AND L2 SPACE. Contents 1. Measure Spaces 1 2. Lebesgue Integration 2 3. L 2 Space 4 Acknowledgments 9 References 9

LEBESGUE MEASURE AND L2 SPACE. Contents 1. Measure Spaces 1 2. Lebesgue Integration 2 3. L 2 Space 4 Acknowledgments 9 References 9 LBSGU MASUR AND L2 SPAC. ANNI WANG Abstract. This paper begins with an introduction to measure spaces and the Lebesgue theory of measure and integration. Several important theorems regarding the Lebesgue

More information

G1CMIN Measure and Integration

G1CMIN Measure and Integration G1CMIN Measure and Integration 2003-4 Prof. J.K. Langley May 13, 2004 1 Introduction Books: W. Rudin, Real and Complex Analysis ; H.L. Royden, Real Analysis (QA331). Lecturer: Prof. J.K. Langley (jkl@maths,

More information

Measures and Measure Spaces

Measures and Measure Spaces Chapter 2 Measures and Measure Spaces In summarizing the flaws of the Riemann integral we can focus on two main points: 1) Many nice functions are not Riemann integrable. 2) The Riemann integral does not

More information

arxiv: v2 [math.ca] 4 Jun 2017

arxiv: v2 [math.ca] 4 Jun 2017 EXCURSIONS ON CANTOR-LIKE SETS ROBERT DIMARTINO AND WILFREDO O. URBINA arxiv:4.70v [math.ca] 4 Jun 07 ABSTRACT. The ternary Cantor set C, constructed by George Cantor in 883, is probably the best known

More information

FUNDAMENTALS OF REAL ANALYSIS by. II.1. Prelude. Recall that the Riemann integral of a real-valued function f on an interval [a, b] is defined as

FUNDAMENTALS OF REAL ANALYSIS by. II.1. Prelude. Recall that the Riemann integral of a real-valued function f on an interval [a, b] is defined as FUNDAMENTALS OF REAL ANALYSIS by Doğan Çömez II. MEASURES AND MEASURE SPACES II.1. Prelude Recall that the Riemann integral of a real-valued function f on an interval [a, b] is defined as b n f(xdx :=

More information

Entrance Exam, Real Analysis September 1, 2017 Solve exactly 6 out of the 8 problems

Entrance Exam, Real Analysis September 1, 2017 Solve exactly 6 out of the 8 problems September, 27 Solve exactly 6 out of the 8 problems. Prove by denition (in ɛ δ language) that f(x) = + x 2 is uniformly continuous in (, ). Is f(x) uniformly continuous in (, )? Prove your conclusion.

More information

1 Lyapunov theory of stability

1 Lyapunov theory of stability M.Kawski, APM 581 Diff Equns Intro to Lyapunov theory. November 15, 29 1 1 Lyapunov theory of stability Introduction. Lyapunov s second (or direct) method provides tools for studying (asymptotic) stability

More information

Introduction to Real Analysis Alternative Chapter 1

Introduction to Real Analysis Alternative Chapter 1 Christopher Heil Introduction to Real Analysis Alternative Chapter 1 A Primer on Norms and Banach Spaces Last Updated: March 10, 2018 c 2018 by Christopher Heil Chapter 1 A Primer on Norms and Banach Spaces

More information

van Rooij, Schikhof: A Second Course on Real Functions

van Rooij, Schikhof: A Second Course on Real Functions vanrooijschikhofproblems.tex December 5, 2017 http://thales.doa.fmph.uniba.sk/sleziak/texty/rozne/pozn/books/ van Rooij, Schikhof: A Second Course on Real Functions Some notes made when reading [vrs].

More information

Connectedness. Proposition 2.2. The following are equivalent for a topological space (X, T ).

Connectedness. Proposition 2.2. The following are equivalent for a topological space (X, T ). Connectedness 1 Motivation Connectedness is the sort of topological property that students love. Its definition is intuitive and easy to understand, and it is a powerful tool in proofs of well-known results.

More information

1/12/05: sec 3.1 and my article: How good is the Lebesgue measure?, Math. Intelligencer 11(2) (1989),

1/12/05: sec 3.1 and my article: How good is the Lebesgue measure?, Math. Intelligencer 11(2) (1989), Real Analysis 2, Math 651, Spring 2005 April 26, 2005 1 Real Analysis 2, Math 651, Spring 2005 Krzysztof Chris Ciesielski 1/12/05: sec 3.1 and my article: How good is the Lebesgue measure?, Math. Intelligencer

More information

(1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define

(1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define Homework, Real Analysis I, Fall, 2010. (1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define ρ(f, g) = 1 0 f(x) g(x) dx. Show that

More information

Spring 2014 Advanced Probability Overview. Lecture Notes Set 1: Course Overview, σ-fields, and Measures

Spring 2014 Advanced Probability Overview. Lecture Notes Set 1: Course Overview, σ-fields, and Measures 36-752 Spring 2014 Advanced Probability Overview Lecture Notes Set 1: Course Overview, σ-fields, and Measures Instructor: Jing Lei Associated reading: Sec 1.1-1.4 of Ash and Doléans-Dade; Sec 1.1 and A.1

More information

Quick Tour of the Topology of R. Steven Hurder, Dave Marker, & John Wood 1

Quick Tour of the Topology of R. Steven Hurder, Dave Marker, & John Wood 1 Quick Tour of the Topology of R Steven Hurder, Dave Marker, & John Wood 1 1 Department of Mathematics, University of Illinois at Chicago April 17, 2003 Preface i Chapter 1. The Topology of R 1 1. Open

More information

REAL AND COMPLEX ANALYSIS

REAL AND COMPLEX ANALYSIS REAL AND COMPLE ANALYSIS Third Edition Walter Rudin Professor of Mathematics University of Wisconsin, Madison Version 1.1 No rights reserved. Any part of this work can be reproduced or transmitted in any

More information

Math 172 HW 1 Solutions

Math 172 HW 1 Solutions Math 172 HW 1 Solutions Joey Zou April 15, 2017 Problem 1: Prove that the Cantor set C constructed in the text is totally disconnected and perfect. In other words, given two distinct points x, y C, there

More information

Measure and Integration: Concepts, Examples and Exercises. INDER K. RANA Indian Institute of Technology Bombay India

Measure and Integration: Concepts, Examples and Exercises. INDER K. RANA Indian Institute of Technology Bombay India Measure and Integration: Concepts, Examples and Exercises INDER K. RANA Indian Institute of Technology Bombay India Department of Mathematics, Indian Institute of Technology, Bombay, Powai, Mumbai 400076,

More information

Real Analysis Problems

Real Analysis Problems Real Analysis Problems Cristian E. Gutiérrez September 14, 29 1 1 CONTINUITY 1 Continuity Problem 1.1 Let r n be the sequence of rational numbers and Prove that f(x) = 1. f is continuous on the irrationals.

More information

Analysis Qualifying Exam

Analysis Qualifying Exam Analysis Qualifying Exam Spring 2017 Problem 1: Let f be differentiable on R. Suppose that there exists M > 0 such that f(k) M for each integer k, and f (x) M for all x R. Show that f is bounded, i.e.,

More information

Chapter 1 Preliminaries

Chapter 1 Preliminaries Chapter 1 Preliminaries 1.1 Conventions and Notations Throughout the book we use the following notations for standard sets of numbers: N the set {1, 2,...} of natural numbers Z the set of integers Q the

More information

Measures. Chapter Some prerequisites. 1.2 Introduction

Measures. Chapter Some prerequisites. 1.2 Introduction Lecture notes Course Analysis for PhD students Uppsala University, Spring 2018 Rostyslav Kozhan Chapter 1 Measures 1.1 Some prerequisites I will follow closely the textbook Real analysis: Modern Techniques

More information

MTH 404: Measure and Integration

MTH 404: Measure and Integration MTH 404: Measure and Integration Semester 2, 2012-2013 Dr. Prahlad Vaidyanathan Contents I. Introduction....................................... 3 1. Motivation................................... 3 2. The

More information

A LITTLE REAL ANALYSIS AND TOPOLOGY

A LITTLE REAL ANALYSIS AND TOPOLOGY A LITTLE REAL ANALYSIS AND TOPOLOGY 1. NOTATION Before we begin some notational definitions are useful. (1) Z = {, 3, 2, 1, 0, 1, 2, 3, }is the set of integers. (2) Q = { a b : aεz, bεz {0}} is the set

More information

+ 2x sin x. f(b i ) f(a i ) < ɛ. i=1. i=1

+ 2x sin x. f(b i ) f(a i ) < ɛ. i=1. i=1 Appendix To understand weak derivatives and distributional derivatives in the simplest context of functions of a single variable, we describe without proof some results from real analysis (see [7] and

More information

Class Notes for MATH 255.

Class Notes for MATH 255. Class Notes for MATH 255. by S. W. Drury Copyright c 2006, by S. W. Drury. Contents 0 LimSup and LimInf Metric Spaces and Analysis in Several Variables 6. Metric Spaces........................... 6.2 Normed

More information

A Measure and Integral over Unbounded Sets

A Measure and Integral over Unbounded Sets A Measure and Integral over Unbounded Sets As presented in Chaps. 2 and 3, Lebesgue s theory of measure and integral is limited to functions defined over bounded sets. There are several ways of introducing

More information

CHAPTER 6. Limits of Functions. 1. Basic Definitions

CHAPTER 6. Limits of Functions. 1. Basic Definitions CHAPTER 6 Limits of Functions 1. Basic Definitions DEFINITION 6.1. Let D Ω R, x 0 be a limit point of D and f : D! R. The limit of f (x) at x 0 is L, if for each " > 0 there is a ± > 0 such that when x

More information

Measures. 1 Introduction. These preliminary lecture notes are partly based on textbooks by Athreya and Lahiri, Capinski and Kopp, and Folland.

Measures. 1 Introduction. These preliminary lecture notes are partly based on textbooks by Athreya and Lahiri, Capinski and Kopp, and Folland. Measures These preliminary lecture notes are partly based on textbooks by Athreya and Lahiri, Capinski and Kopp, and Folland. 1 Introduction Our motivation for studying measure theory is to lay a foundation

More information

Part III. 10 Topological Space Basics. Topological Spaces

Part III. 10 Topological Space Basics. Topological Spaces Part III 10 Topological Space Basics Topological Spaces Using the metric space results above as motivation we will axiomatize the notion of being an open set to more general settings. Definition 10.1.

More information

2 Sequences, Continuity, and Limits

2 Sequences, Continuity, and Limits 2 Sequences, Continuity, and Limits In this chapter, we introduce the fundamental notions of continuity and limit of a real-valued function of two variables. As in ACICARA, the definitions as well as proofs

More information

Solutions to Problem Set 5 for , Fall 2007

Solutions to Problem Set 5 for , Fall 2007 Solutions to Problem Set 5 for 18.101, Fall 2007 1 Exercise 1 Solution For the counterexample, let us consider M = (0, + ) and let us take V = on M. x Let W be the vector field on M that is identically

More information

Part V. 17 Introduction: What are measures and why measurable sets. Lebesgue Integration Theory

Part V. 17 Introduction: What are measures and why measurable sets. Lebesgue Integration Theory Part V 7 Introduction: What are measures and why measurable sets Lebesgue Integration Theory Definition 7. (Preliminary). A measure on a set is a function :2 [ ] such that. () = 2. If { } = is a finite

More information

consists of two disjoint copies of X n, each scaled down by 1,

consists of two disjoint copies of X n, each scaled down by 1, Homework 4 Solutions, Real Analysis I, Fall, 200. (4) Let be a topological space and M be a σ-algebra on which contains all Borel sets. Let m, µ be two positive measures on M. Assume there is a constant

More information

MATH NEW HOMEWORK AND SOLUTIONS TO PREVIOUS HOMEWORKS AND EXAMS

MATH NEW HOMEWORK AND SOLUTIONS TO PREVIOUS HOMEWORKS AND EXAMS MATH. 4433. NEW HOMEWORK AND SOLUTIONS TO PREVIOUS HOMEWORKS AND EXAMS TOMASZ PRZEBINDA. Final project, due 0:00 am, /0/208 via e-mail.. State the Fundamental Theorem of Algebra. Recall that a subset K

More information

FUNDAMENTALS OF REAL ANALYSIS by. IV.1. Differentiation of Monotonic Functions

FUNDAMENTALS OF REAL ANALYSIS by. IV.1. Differentiation of Monotonic Functions FUNDAMNTALS OF RAL ANALYSIS by Doğan Çömez IV. DIFFRNTIATION AND SIGND MASURS IV.1. Differentiation of Monotonic Functions Question: Can we calculate f easily? More eplicitly, can we hope for a result

More information

(B(t i+1 ) B(t i )) 2

(B(t i+1 ) B(t i )) 2 ltcc5.tex Week 5 29 October 213 Ch. V. ITÔ (STOCHASTIC) CALCULUS. WEAK CONVERGENCE. 1. Quadratic Variation. A partition π n of [, t] is a finite set of points t ni such that = t n < t n1

More information

1 Measurable Functions

1 Measurable Functions 36-752 Advanced Probability Overview Spring 2018 2. Measurable Functions, Random Variables, and Integration Instructor: Alessandro Rinaldo Associated reading: Sec 1.5 of Ash and Doléans-Dade; Sec 1.3 and

More information

Introductory Analysis I Fall 2014 Homework #9 Due: Wednesday, November 19

Introductory Analysis I Fall 2014 Homework #9 Due: Wednesday, November 19 Introductory Analysis I Fall 204 Homework #9 Due: Wednesday, November 9 Here is an easy one, to serve as warmup Assume M is a compact metric space and N is a metric space Assume that f n : M N for each

More information

CHAPTER 5. The Topology of R. 1. Open and Closed Sets

CHAPTER 5. The Topology of R. 1. Open and Closed Sets CHAPTER 5 The Topology of R 1. Open and Closed Sets DEFINITION 5.1. A set G Ω R is open if for every x 2 G there is an " > 0 such that (x ", x + ") Ω G. A set F Ω R is closed if F c is open. The idea is

More information

STRONGLY CONNECTED SPACES

STRONGLY CONNECTED SPACES Undergraduate Research Opportunity Programme in Science STRONGLY CONNECTED SPACES Submitted by Dai Bo Supervised by Dr. Wong Yan-loi Department of Mathematics National University of Singapore Academic

More information

MATH 131A: REAL ANALYSIS (BIG IDEAS)

MATH 131A: REAL ANALYSIS (BIG IDEAS) MATH 131A: REAL ANALYSIS (BIG IDEAS) Theorem 1 (The Triangle Inequality). For all x, y R we have x + y x + y. Proposition 2 (The Archimedean property). For each x R there exists an n N such that n > x.

More information

2 (Bonus). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure?

2 (Bonus). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure? MA 645-4A (Real Analysis), Dr. Chernov Homework assignment 1 (Due 9/5). Prove that every countable set A is measurable and µ(a) = 0. 2 (Bonus). Let A consist of points (x, y) such that either x or y is

More information

THE STONE-WEIERSTRASS THEOREM AND ITS APPLICATIONS TO L 2 SPACES

THE STONE-WEIERSTRASS THEOREM AND ITS APPLICATIONS TO L 2 SPACES THE STONE-WEIERSTRASS THEOREM AND ITS APPLICATIONS TO L 2 SPACES PHILIP GADDY Abstract. Throughout the course of this paper, we will first prove the Stone- Weierstrass Theroem, after providing some initial

More information

Chapter 4. Measure Theory. 1. Measure Spaces

Chapter 4. Measure Theory. 1. Measure Spaces Chapter 4. Measure Theory 1. Measure Spaces Let X be a nonempty set. A collection S of subsets of X is said to be an algebra on X if S has the following properties: 1. X S; 2. if A S, then A c S; 3. if

More information

Lebesgue Measure on R n

Lebesgue Measure on R n 8 CHAPTER 2 Lebesgue Measure on R n Our goal is to construct a notion of the volume, or Lebesgue measure, of rather general subsets of R n that reduces to the usual volume of elementary geometrical sets

More information

Problem List MATH 5143 Fall, 2013

Problem List MATH 5143 Fall, 2013 Problem List MATH 5143 Fall, 2013 On any problem you may use the result of any previous problem (even if you were not able to do it) and any information given in class up to the moment the problem was

More information

Problem set 1, Real Analysis I, Spring, 2015.

Problem set 1, Real Analysis I, Spring, 2015. Problem set 1, Real Analysis I, Spring, 015. (1) Let f n : D R be a sequence of functions with domain D R n. Recall that f n f uniformly if and only if for all ɛ > 0, there is an N = N(ɛ) so that if n

More information

REAL VARIABLES: PROBLEM SET 1. = x limsup E k

REAL VARIABLES: PROBLEM SET 1. = x limsup E k REAL VARIABLES: PROBLEM SET 1 BEN ELDER 1. Problem 1.1a First let s prove that limsup E k consists of those points which belong to infinitely many E k. From equation 1.1: limsup E k = E k For limsup E

More information

Homework 1 Real Analysis

Homework 1 Real Analysis Homework 1 Real Analysis Joshua Ruiter March 23, 2018 Note on notation: When I use the symbol, it does not imply that the subset is proper. In writing A X, I mean only that a A = a X, leaving open the

More information

Differentiation. Chapter 4. Consider the set E = [0, that E [0, b] = b 2

Differentiation. Chapter 4. Consider the set E = [0, that E [0, b] = b 2 Chapter 4 Differentiation Consider the set E = [0, 8 1 ] [ 1 4, 3 8 ] [ 1 2, 5 8 ] [ 3 4, 8 7 ]. This set E has the property that E [0, b] = b 2 for b = 0, 1 4, 1 2, 3 4, 1. Does there exist a Lebesgue

More information

Economics 204 Fall 2011 Problem Set 2 Suggested Solutions

Economics 204 Fall 2011 Problem Set 2 Suggested Solutions Economics 24 Fall 211 Problem Set 2 Suggested Solutions 1. Determine whether the following sets are open, closed, both or neither under the topology induced by the usual metric. (Hint: think about limit

More information

MATHS 730 FC Lecture Notes March 5, Introduction

MATHS 730 FC Lecture Notes March 5, Introduction 1 INTRODUCTION MATHS 730 FC Lecture Notes March 5, 2014 1 Introduction Definition. If A, B are sets and there exists a bijection A B, they have the same cardinality, which we write as A, #A. If there exists

More information

Analysis III. Exam 1

Analysis III. Exam 1 Analysis III Math 414 Spring 27 Professor Ben Richert Exam 1 Solutions Problem 1 Let X be the set of all continuous real valued functions on [, 1], and let ρ : X X R be the function ρ(f, g) = sup f g (1)

More information

Real Analysis Notes. Thomas Goller

Real Analysis Notes. Thomas Goller Real Analysis Notes Thomas Goller September 4, 2011 Contents 1 Abstract Measure Spaces 2 1.1 Basic Definitions........................... 2 1.2 Measurable Functions........................ 2 1.3 Integration..............................

More information

Lecture Notes in Advanced Calculus 1 (80315) Raz Kupferman Institute of Mathematics The Hebrew University

Lecture Notes in Advanced Calculus 1 (80315) Raz Kupferman Institute of Mathematics The Hebrew University Lecture Notes in Advanced Calculus 1 (80315) Raz Kupferman Institute of Mathematics The Hebrew University February 7, 2007 2 Contents 1 Metric Spaces 1 1.1 Basic definitions...........................

More information

Dedicated to Prof. Jaroslav Kurzweil on the occasion of his 80th birthday

Dedicated to Prof. Jaroslav Kurzweil on the occasion of his 80th birthday 131 (2006) MATHEMATICA BOHEMICA No. 4, 365 378 ON MCSHANE-TYPE INTEGRALS WITH RESPECT TO SOME DERIVATION BASES Valentin A. Skvortsov, Piotr Sworowski, Bydgoszcz (Received November 11, 2005) Dedicated to

More information

for all x,y [a,b]. The Lipschitz constant of f is the infimum of constants C with this property.

for all x,y [a,b]. The Lipschitz constant of f is the infimum of constants C with this property. viii 3.A. FUNCTIONS 77 Appendix In this appendix, we describe without proof some results from real analysis which help to understand weak and distributional derivatives in the simplest context of functions

More information

Review of Multi-Calculus (Study Guide for Spivak s CHAPTER ONE TO THREE)

Review of Multi-Calculus (Study Guide for Spivak s CHAPTER ONE TO THREE) Review of Multi-Calculus (Study Guide for Spivak s CHPTER ONE TO THREE) This material is for June 9 to 16 (Monday to Monday) Chapter I: Functions on R n Dot product and norm for vectors in R n : Let X

More information

Continuum Probability and Sets of Measure Zero

Continuum Probability and Sets of Measure Zero Chapter 3 Continuum Probability and Sets of Measure Zero In this chapter, we provide a motivation for using measure theory as a foundation for probability. It uses the example of random coin tossing to

More information

Sequences and Series of Functions

Sequences and Series of Functions Chapter 13 Sequences and Series of Functions These notes are based on the notes A Teacher s Guide to Calculus by Dr. Louis Talman. The treatment of power series that we find in most of today s elementary

More information

Continuity. Chapter 4

Continuity. Chapter 4 Chapter 4 Continuity Throughout this chapter D is a nonempty subset of the real numbers. We recall the definition of a function. Definition 4.1. A function from D into R, denoted f : D R, is a subset of

More information

d(x n, x) d(x n, x nk ) + d(x nk, x) where we chose any fixed k > N

d(x n, x) d(x n, x nk ) + d(x nk, x) where we chose any fixed k > N Problem 1. Let f : A R R have the property that for every x A, there exists ɛ > 0 such that f(t) > ɛ if t (x ɛ, x + ɛ) A. If the set A is compact, prove there exists c > 0 such that f(x) > c for all x

More information

Math Real Analysis The Henstock-Kurzweil Integral

Math Real Analysis The Henstock-Kurzweil Integral Math 402 - Real Analysis The Henstock-Kurzweil Integral Steven Kao & Jocelyn Gonzales April 28, 2015 1 Introduction to the Henstock-Kurzweil Integral Although the Rieann integral is the priary integration

More information

Integration on Measure Spaces

Integration on Measure Spaces Chapter 3 Integration on Measure Spaces In this chapter we introduce the general notion of a measure on a space X, define the class of measurable functions, and define the integral, first on a class of

More information

THE CANTOR GAME: WINNING STRATEGIES AND DETERMINACY. by arxiv: v1 [math.ca] 29 Jan 2017 MAGNUS D. LADUE

THE CANTOR GAME: WINNING STRATEGIES AND DETERMINACY. by arxiv: v1 [math.ca] 29 Jan 2017 MAGNUS D. LADUE THE CANTOR GAME: WINNING STRATEGIES AND DETERMINACY by arxiv:170109087v1 [mathca] 9 Jan 017 MAGNUS D LADUE 0 Abstract In [1] Grossman Turett define the Cantor game In [] Matt Baker proves several results

More information

MATH 202B - Problem Set 5

MATH 202B - Problem Set 5 MATH 202B - Problem Set 5 Walid Krichene (23265217) March 6, 2013 (5.1) Show that there exists a continuous function F : [0, 1] R which is monotonic on no interval of positive length. proof We know there

More information

A Short Journey Through the Riemann Integral

A Short Journey Through the Riemann Integral A Short Journey Through the Riemann Integral Jesse Keyton April 23, 2014 Abstract An introductory-level theory of integration was studied, focusing primarily on the well-known Riemann integral and ending

More information

David M. Bressoud Macalester College, St. Paul, Minnesota Given at Allegheny College, Oct. 23, 2003

David M. Bressoud Macalester College, St. Paul, Minnesota Given at Allegheny College, Oct. 23, 2003 David M. Bressoud Macalester College, St. Paul, Minnesota Given at Allegheny College, Oct. 23, 2003 The Fundamental Theorem of Calculus:. If F' ( x)= f ( x), then " f ( x) dx = F( b)! F( a). b a 2. d dx

More information

After taking the square and expanding, we get x + y 2 = (x + y) (x + y) = x 2 + 2x y + y 2, inequality in analysis, we obtain.

After taking the square and expanding, we get x + y 2 = (x + y) (x + y) = x 2 + 2x y + y 2, inequality in analysis, we obtain. Lecture 1: August 25 Introduction. Topology grew out of certain questions in geometry and analysis about 100 years ago. As Wikipedia puts it, the motivating insight behind topology is that some geometric

More information

Compendium and Solutions to exercises TMA4225 Foundation of analysis

Compendium and Solutions to exercises TMA4225 Foundation of analysis Compendium and Solutions to exercises TMA4225 Foundation of analysis Ruben Spaans December 6, 2010 1 Introduction This compendium contains a lexicon over definitions and exercises with solutions. Throughout

More information

MATH41011/MATH61011: FOURIER SERIES AND LEBESGUE INTEGRATION. Extra Reading Material for Level 4 and Level 6

MATH41011/MATH61011: FOURIER SERIES AND LEBESGUE INTEGRATION. Extra Reading Material for Level 4 and Level 6 MATH41011/MATH61011: FOURIER SERIES AND LEBESGUE INTEGRATION Extra Reading Material for Level 4 and Level 6 Part A: Construction of Lebesgue Measure The first part the extra material consists of the construction

More information

16 1 Basic Facts from Functional Analysis and Banach Lattices

16 1 Basic Facts from Functional Analysis and Banach Lattices 16 1 Basic Facts from Functional Analysis and Banach Lattices 1.2.3 Banach Steinhaus Theorem Another fundamental theorem of functional analysis is the Banach Steinhaus theorem, or the Uniform Boundedness

More information

Set, functions and Euclidean space. Seungjin Han

Set, functions and Euclidean space. Seungjin Han Set, functions and Euclidean space Seungjin Han September, 2018 1 Some Basics LOGIC A is necessary for B : If B holds, then A holds. B A A B is the contraposition of B A. A is sufficient for B: If A holds,

More information

Chapter 10. Multivariable integral Riemann integral over rectangles Rectangles and partitions

Chapter 10. Multivariable integral Riemann integral over rectangles Rectangles and partitions Chapter 10 Multivariable integral 10.1 iemann integral over rectangles ote:??? lectures As in chapter chapter 5, we define the iemann integral using the Darboux upper and lower integrals. The ideas in

More information