REAL ANALYSIS I HOMEWORK 2

Size: px
Start display at page:

Download "REAL ANALYSIS I HOMEWORK 2"

Transcription

1 REAL ANALYSIS I HOMEWORK 2 CİHAN BAHRAN The questions are from Stein and Shakarchi s text, Chapter 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 is a point z / C that lies in between x and y, and yet C has no isolated points. [Hint: If x, y C and x y > 1/3 k, then x and y belong to two different intervals in C k. Also, given any x C there is an end-point y k of some interval in C k that satisfies x y k and x y k 1/3 k.] Given two distinct points x, y C, since x y > 0 there exists k N such that x y > 1/3 k. Because C k is a union of closed intervals of length 1/3 k and x, y C k, there exists z in between x and y which does not lie in C k. Thus z / C. And given x C, for every k N, x lies in one of the 2 k intervals that make up C k. Thus there exists an end-point y k in C k such that x y k 1/3 k. We may assume y k x here (if x happens to be an end-point of an interval in C k itself, choose the other end-point of the interval to be y k ). But we know that the end-points survive the Cantor intersection, that is they lie in C. Hence [x 1/3 k, x + 1/3 k ] {x} intersects C for every k. Since x C was arbitrary, we conclude that C has no isolated points. 2. The Cantor set C can also be described in terms of ternary expansions. (a) Every number in [0, 1] has a ternary expansion x = a k 3 k, where a k = 0, 1 or 2. k=1 Note that this decomposition is not unique since, for example, 1/3 = k=2 2/3 k. Prove that x C if and only if x has a representation as above where every a k is either 0 or 2. The question states that there is a well-defined surjective map f : {0, 1, 2} N [0, 1] (a n ) a n 3 n. The question asks us to prove f({0, 2} N ) = C. In the last homework, I showed that f Ä {0, 2} Nä C (I also showed that f maps {0, 2} N injectively to C and from here deduced that C is uncountable). So it s enough to show that C f Ä {0, 2} Nä, or equivalently [0, 1] f Ä {0, 2} Nä [0, 1] C. So let x [0, 1] f Ä {0, 2} Nä. Since f is surjective there exists a sequence (a n ) with a n {0, 1, 2} such that x = a n 3 n. By assumption, the set {n N : a n = 1} must be nonempty. So pick the least element k from that set. Thus a k = 1 but 1

2 REAL ANALYSIS I HOMEWORK 2 2 a 1,..., a k 1 {0, 2}. Let y = k 1 a i 3 i. Note that y is an end-point in C k 1. More precisely, [y, y + 3 k+1 ] is one of the intervals in C k 1. Note that on one hand x y = a i 3 i = 3 k + a i 3 i 3 k and on the other hand which implies x y 3 k + 2 i=k+1 i=k 3 i = 3 k + 2 i=k+1 3 k = 3 k + 3 k = 2 3 k (y + 3 k+1 ) x = y k x 3 k. Thus we get x î y + 3 k, (y + 3 k+1 ) 3 kó, which is the middle third of the interval [y, y + 3 k+1 ]. Moreover, y and y + 3 k+1 = y + i=k 2 3 i lie in f({0, 2} N ), thus x Ä y + 3 k, (y + 3 k+1 ) 3 kä and so x / C k as C k loses this interval while being constructed from C k 1. In particular x / C. (b) The Cantor-Lebesgue function is defined on C by F (x) = b n 2 n if x = a n 3 n where b n = a n /2. In this definition we choose the expansion of x in which a k = 0 or 2. Show that F is well-defined and continuous on C, and moreover F (0) = 0 as well as F (1) = 1. In (a), we showed that there is a bijection f : {0, 2} N C (a n ) a n 3 n. Note that there is a surjection g : {0, 1} N [0, 1] (b n ) b n 2 n since every number in [0, 1] has a binary expansion like Now we can define F = g ι f 1 : C [0, 1] where ι : {0, 2} N {0, 1} N (a n ) (a n /2). If we let 0 to be simply the sequence consisting entirely of 0 s, we have thus (g ι)(0) = g(0) = 0 = f(0) F (0) = (g ι)(f 1 (0)) = (g ι)(0) = 0.

3 REAL ANALYSIS I HOMEWORK 2 3 And if we let 2 to be the sequence consisting entirely of 2 s and 1 to be the sequence of 1 s, we have thus (g ι)(2) = g(1) = 2 n = 1 = 2 3 n = f(2) F (1) = (g ι)(f 1 (1)) = (g ι)(2) = 1. For continuity, consider the discrete topology on {0, 1} and then endow the set of sequences {0, 1} N with the product topology. Do the same for {0, 2} N. Then being continuous coordinate-wise, ι is definitely continuous. We will show that f and g are also continuous. From here it follows that F is continuous, and since the domain {0, 2} N of f is compact (Tychonoff s theorem!) and the codomain C of f is Hausdorff, the bijective continuous map f is a homeomorphism; hence F is a composite of continuous maps. And Proposition 2 yields that f and g are continuous (g by taking d = 2 and f by taking d = 3 and restricting to {0, 2} N ). Lemma 1. Let d be a natural number greater than 1 and write D = {0,..., d 1}. Let (a n ) and (b n ) be two distinct sequences with elements in D. Let k = min{n N : a n b n }. Then b n d n a n d n < if and only if one of the three possibilities below holds: (1) a k < b k 1. (2) a k = b k 1 and b l > 0 for some l > k. (3) a k = b k 1 and a l < d 1 for some l > k. Proof. Omitted. This is a standard base-d expansion result. Proposition 2. Let d be a natural number greater than 1. Put the discrete topology on the set D = {0,..., d 1} and consider D N with the product topology. Then the surjective map is continuous. h : D N [0, 1] (a n ) a n d n Proof. It is enough to show that for every b [0, 1] the set h 1 ((, b) [0, 1]) = {(a n ) : a n d n < b} is open in D N. Pick (b n ) such that b n d n = b. If b n s eventually become 0, replace them by a sequence which is eventually d 1 which still is an expansion of b. Write U k = {b 1 } {b k 1 } {c D : c < b k 1} D D D V k,l = {b 1 } {b k 1 } {b k 1} D D D (D {d 1}) D D

4 REAL ANALYSIS I HOMEWORK 2 4 for every k, l N with l > k where the D {d 1} term in V k,l occurs at the l-th coordinate. Note that every U k and V k,l is open in D N. Now by Lemma 1 we get that {(a n ) : a n d n < b} = U k V k,l k N k N l>k which is open. (c) Prove that F : C [0, 1] is surjective. We know that f is bijective and g is surjective. ι is also clearly surjective by its definition. Thus F = g ι f 1 is also surjective. (d) One can also extend F to be a continuous function on [0, 1] as follows. Note that if (a, b) is an open interval of the complement of C, then F (a) = F (b). Hence we may define F to have constant value on that interval. A connected component of the complement of C is of the form ( n ) n a i 3 i + 3 n, a i 3 i n for some a 1,..., a n {0, 2}. Write r = Note that and as desired. n n r = a i 3 i i C i=n+1 n F (r) = (a i /2)2 i + 2 i i=n+1 n = (a i /2)2 i + 2 n n 1 = (a i /2)2 i + a n n 2 ( n 1 ) = F a i 3 i + (a n + 2)3 n ( n ) = F a i 3 i n = F (r + 3 n ) 5. Suppose E is a given set, and O n is the open set Show: O n = {x R d : d(x, E) < 1/n}. (a) If E is compact, then m(e) = lim n m(o n ). a i 3 i + 3 n so the interval is (r, r + 3 n ).

5 REAL ANALYSIS I HOMEWORK 2 5 Note that since E is closed, it is measurable so writing m(e) is OK. Also note that (O n ) is a decreasing family of open sets. Let O be an arbitrary open set containing E and write C = R d O. So E and C are disjoint, moreover since E is compact and C is closed they are distant by a previous exercise. Hence d(c, E) 1/n for some n. That is, every point in C is at least 1/n away from E hence C O n =. This implies that O n O. So we showed the set {O n : n N} is cofinal in {O R d : E O-open} with respect to the reverse containment. Thus by the monotonicity of m the set {m(o n ) : n N} is cofinal in {m(o) : E O-open} with respect to. Thus their infima coincide: lim O n = inf{m(o n ) : n N} = inf{m(o) : E O-open} = m(e). n (b) However, the conclusion in (a) may be false for E closed and unbounded; or E open and bounded. For the first part, take E = N as a subset of R, which is closed and unbounded. In this case, O n = (N 1/2n, N + 1/2n). N N Since the union is disjoint, by countable additivity of m we have whereas m(e) = 0, being a countable set. m(o n ) = N N 1/n = For the second part, let (q n ) be an enumeration of Q [0, 1] and take E = (q n 4 n, q n + 4 n ). E is certainly open and bounded. Now by countable subadditivity we have m(e) 2 4 n = /4 = /4 = 2/3. However, E is dense in [0, 1]. So given x [0, 1], for every n N there exists q E such that d(x, q) < 1/n so x O n. Thus [0, 1] O n for every n and hence for every n. Therefore 1 = m([0, 1]) m(o n ) lim m(o n) 1. n 11. Let A be the subset of [0, 1] which consists of all numbers which do not have the digit 4 appearing in their decimal expansion. Find m(a). This corresponds to dividing [0, 1] into 10 equal pieces, labeling them from 0 to 9 and taking away the piece with label 4 (since the numbers between 0.4 and 0.5 should be deleted). Then this process is applied to the 9 remaining pieces. So at the first step

6 REAL ANALYSIS I HOMEWORK 2 6 we take away an interval of length 1/10, at the second step we take away 9 intervals of length 1/100 and so on. So the complement of A has measure 9 n = 1 n 10 Ç å 9 n 1 = = 1 10 hence A has measure The following deals with G δ and F σ sets. (a) Show that a closed set is a G δ and an open set an F σ. [Hint: If F is closed, consider O n = {x : d(x, F ) < 1/n}.] Let s use the notation of the hint. Since F is closed, d(x, F ) = 0 if and only if x F therefore F = O n. Let G be an open set. Then G c is closed and hence is a G δ set. Therefore G is an F σ set by de Morgan. (b) Give an example of an F σ that is not a G δ. [Hint: This is more difficult; let F be a denumerable set that is dense.] We can definitely choose an F as in the hint for any R d because R d is a separable topological space (points with rational coordinates form a dense set). Since F is a countable union of singletons, it is an F σ. To show that it is not G δ we will refer to the Baire category theorem. Definition 3. A topological space X is called a Baire space if for any countable collection {A n } of closed sets of X each of which has empty interior in X, their union An also has empty interior in X. Theorem 4. (Baire category theorem) Complete metric spaces are Baire spaces. Now suppose F is G δ to get a contradiction. Then F = U n where U n s are a countable collection of open sets. Since F is dense, each U n is dense. Write C n = R d U n. Then since Int(C n ) is disjoint from the dense set U n, we have Int(C n ) =. So R d F = C n is a countable union of closed sets with empty interiors. But F is also a countable union of closed sets with empty interiors, namely singletons. Thus R d = (R d F ) F is a countable union of closed sets with empty interiors. But by Baire category theorem R d is a Baire space hence R d has empty interior, nonsense. Therefore F is not G δ. (c) Give an example of a Borel set which is not a G δ nor an F σ. Lemma 5. Let X be any topological space and A, B X. (1) If A and B are F σ sets, so are A B and A B.

7 REAL ANALYSIS I HOMEWORK 2 7 (2) If A and B are G δ sets, so are A B and A B. Proof. (2) follows from (1) by taking complements. To prove (1), write A = F n and B = L n where F n, L n are closed. Then A B = (F n L n ), A B = (F n L m ) are F σ sets. n,m N Let F = [0, ) Q and G = (, 0] (R Q) in R. Note that closed sets in R are trivially F σ and also G δ by part (a). By Lemma 5, F is an F σ set and G is a G δ set. Let E = F G. Being the union of two Borel sets, E is certainly Borel. Suppose that E is G δ. Then by Lemma 5 the set E [0, ) = F is G δ. But then the set F = (, 0] Q is also G δ because F is the image of F under the homeomorphism x x of R. Thus F F = Q is G δ. This contradicts what we ve shown in part (b). Thus E is not G δ. Now suppose that E is F σ. Then E (, 0] = G is F σ. Similar to above, from here it follows that R Q is F σ which then implies that Q is G δ, again a contradiction. Thus E is neither G δ nor F σ. 16. The Borel-Cantelli lemma. Suppose {E k } k=1 is a countable family of measurable subsets of R d such that m(e k ) <. Let k=1 = lim sup(e k ). k (a) Show that E is measurable. [Hint: Write E = n=1 k n E k ]. E = {x R d : x E k, for infinitely many k} Let s verify the hint. Assume x E k for infinitely many k. This implies that for every n N, there exists k n such that x E k. That is, for every n N, x k n E k and hence x k n E k. Conversely, assume that x k n E k. Since x k 1 E k, there exists k 1 1 such that x E k1. And since x k 2 E k, there exists k 2 > max{2, k 1 } such that x E k2. Going on like this, we can construct a sequence k 1 < k 2 < k 3 such that x E kn for every n. Thus x lies in infinitely many E k. Having proved the claim, we are done since the collection of measurable sets is closed under countable unions and countable intersections. (b) Prove m(e) = 0. Since k=1 m(e k ) <, for every ε > 0 there exists n N such that Ñ é ε > m(e k ) m m(e). k n E k k n

8 REAL ANALYSIS I HOMEWORK 2 8 Thus m(e) = Let {f n } be a sequence of measurable functions on [0, 1] with f n (x) < for a.e. x. Show that there exists a sequence c n of positive real numbers such that f n (x) c n 0 a.e. x [Hint: Pick c n such that m({x : f n (x)/c n > 1/n}) < 2 n, and apply the Borel- Cantelli lemma.] Fix n. Since f n < a.e., for every n there exists d n > 0 such that m({x : f n (x) > d n }) < 2 n. Now let c n = nd n. Clearly (c n ) is a sequence of positive real numbers. If we write E n = {x : f n (x) > d n } = x : f n(x) > 1/n, c n we have m(e n ) < 2 n = 1 <. So by the Borel-Cantelli lemma, the E := lim sup n (E n ) is a null set. Now by definition, every x E c lies in only finitely many E n s. That is, given x E c, there exists N N such that for every n N we have Therefore f n(x) c n 0 for every x E c. f n (x) c n 1/n. 29. Suppose E is a measurable subset of R with m(e) > 0. Prove that the difference set of E, which is defined by {x y : x, y E} contains an open interval centered at the origin. It is enough to prove the claim for a measurable subset of E with positive measure, so we do some reductions by finding some nice subsets of E like this and replacing E with these subsets. First, since the collection {E (n, n + 1] : n Z} of disjoint measurable sets cover E, by countable additivity there exists n N such that m(e (n, n + 1]) > 0. So we may assume that E has finite measure. Second, since 0 < m(e) <, by an exercise in the previous homework there exists a compact set K contained in E such that (choosing ε = m(e)/2) m(e K) m(e)/2. Then by addivity of the measure we get m(k) m(e)/2 > 0. So we may assume that E is compact.

9 REAL ANALYSIS I HOMEWORK 2 9 Third, since 0 < m(e) < there exists an open set U containing E such that m(u E) m(e)/2. Hence m(u) 3/2 m(e) < 2m(E). Now E and U c are disjoint sets where E is compact and U c is closed. Therefore δ := d(e, U c ) > 0. We claim that ( δ, δ) lies in the difference set of E. So let t ( δ, δ). Then by the definition of δ, the set E + t = {x + t : x E} does not intersect U c, therefore E + t U and hence (E + t) E U. Note that E + t is a measurable set with m(e + t) = m(e). Suppose (E + t) E =. Then by additivity, we get m(u) m((e + t) E) = 2m(E) which is a contradiction. Thus there exists x, y E such that x + t = y, so t lies in the difference set of E. 30. If E and F are measurable subsets of R and m(e) > 0, m(f ) > 0, prove that contains an interval. E + F = {x + y : x E, y F } We show that the difference set (E, F ) = {x y : x E, y F } contains an interval under the same assumptions. This implies the desired conclusion because then the set F = { y : y F } is also measurable and m( F ) = m(f ) > 0, so E +F = (E, F ) contains an interval. By Exercise 28, for every α (0, 1) there exists an open interval I and an open interval J such that m(e I) 3m(I) and m(f J) 3 m(j). WLOG, we may assume 4 4 m(i) m(j). Then there exists a R such that J + a I. Write δ = 1 m(j). Observe that for any 0 < c < δ, the intervals I and J + a + c 4 intersect in an interval K of length more than 3m(J). Writing E 4 0 = E K and F 0 = (F + a + c) K, we have hence m(e I) = m(e 0 ) + m(e (I K)) < m(e 0 ) m(j) m(e 0 ) > 3 4 m(i) 1 4 m(j) > 3 4 m(j) 1 4 m(j) = 1 2 m(j). And so m(f J) = m((f + a + c) (J + a + c)) = m(f 0 ) + m((f + a + c) (J + a + c) K) < m(f 0 ) m(j) m(f 0 ) > 3 4 m(j) 1 4 m(j) = 1 2 m(j). Note that E 0 F 0 is contained in K and hence m(e 0 F 0 ) m(k) m(j). But both E 0 and F 0 has measure strictly greater than 1 m(j), so by the addivity of the measure 2 we conclude that E 0 F 0. Thus E (F + a + c), so there exists x F such

10 REAL ANALYSIS I HOMEWORK 2 10 that x + a + c E. Therefore a + c (E, F ). Since this is true whenever 0 < c < δ, the interval (a δ, a + δ) is contained in (E, F ). 33. Let N denote the non-measurable set constructed in the text. Recall from the exercise above that measurable subsets of N have measure zero. Show that the set N c = I N satisfies m (N c ) = 1, and conclude that if E 1 = N and E 2 = N c, then although E 1 and E 2 are disjoint. m (E 1 ) + m (E 2 ) m (E 1 E 2 ) [Hint: To prove that m (N c ) = 1, argue by contradiction and pick a measurable set U such that U I, N c U and m (U) < 1 ε.] Suppose m (N c ) < 1, so there exists ε > 0 such that m (N c ) < 1 ε. Since m (N c ) = inf{m(u) : N c U-open} there exists an open, hence measurable set U containing N c such that m(u) < 1 ε. Note that U I is also a measurable containing N c with m(u I) < 1 ε, so we may assume U I. Since N c = I N U I, we have I U N. But I U is a measurable set so by additivity of the measure we have m(i U) = m(i) m(u) = 1 m(u) > ε. So I U is a measurable subset of N with positive measure; a contradiction. Therefore m (N c ) 1 but on the other hand m (N c ) m (I) = 1 hence m (N c ) = 1. We know that sets with outer measure zero are measurable, so m (N ) > 0. Thus m (N ) + m (N c ) > 1 = m (I) = m (N N c ). 34. Let C 1 and C 2 be any two Cantor sets (constructed in Exercise 3). Show that there exists a function F : [0, 1] [0, 1] with the following properties: (i) F is continuous and bijective. (ii) F is monotonically increasing. (iii) F maps C 1 surjectively onto C 2. [Hint: Copy the construction of the standard Cantor-Lebesgue function.] Let C be a Cantor set of constant dissection as in Exercise 3. By construction, C is the intersection of a family {C n } of closed sets where each C n is a disjoint union of 2 n closed intervals. So we can label these 2 n intervals from left to right by bit strings of length n, that is, words of length n consisting of 0 s and 1 s. So for example C 1 = I 0 I 1 where I 0 is the interval on the left hand side in C 1 and I 1 is the one on the right. Keeping the labeling in a lexicographic order, we have C 2 = I 00 I 01 I 10 I 11 and in general C n is the union of I b s where b s vary over length n bit strings. Note that I b I c if and only if c can be truncated from the right to obtain b. For example I 0 I 01 I 010 I In general given an infinite sequence a = (a n ) of 0 s and 1 s, if we write a n for its n-truncation (a 1,..., a n ) there is a decreasing sequence I a 1 I a 2 I a 3

11 By compactness, the intersection REAL ANALYSIS I HOMEWORK 2 11 I a n which lies in C, is nonempty. Yet the diameter of the intersection is zero, hence it must be a singleton. Therefore every infinite sequence a of 0 s and 1 s uniquely determines a point in C. So we get a map f : {0, 1} N C which is surjective since points in C by definition survives the intersection of C n s hence lie in infinitely many (hence in an infinite decreasing chain of) I b s. If two infinite sequences are distinct, they have different truncations so as the intervals get finer, the two points these sequences determine will fall into different intervals. Hence f is a bijection. Two points in C lie in the same I b where b is a finite bit string if and only if their inverse images under f both start with b. It follows from this observation (as we did for the middle thirds Cantor set in Exercise 2) that f is continuous. And since f goes from a compact space to a Hausdorff space, f is a homeomorphism. Also observe that if we order {0, 1} N by lexicographic ordering, then f preserves the order. Because if a sequence beats another sequence lexicographically, then at some point it will lie to the right side of a dissection while the other lies on the left side. So if C 1 and C 2 are two Cantor sets, we have order preserving homeomorphisms f 1 : {0, 1} N C 1 and f 2 : {0, 1} N C 2 ; thus f 2 f1 1 gives an order preserving homeomorphism from C 1 to C Give an example of a measurable function and a continuous function Φ so that f Φ is non-measurable. [Hint: Let Φ : C 1 C 2 as in Exercise 34, with m(c 1 ) > 0 and m(c 2 ) = 0. Let N C 1 be non-measurable, and take f = χ Φ(N).] Use the construction in the hint to show that there exists a Lebesgue measurable set that is not a Borel set. Let s do as the hint commands. We know such N exists by Exercise 32(b). Since Φ(N) C 2 and m(c 2 ) = 0, we have m (Φ(N)) = 0 and so Φ(N) is a measurable set. Therefore f is a measurable function. However, (f Φ) 1 (1) = Φ 1 (f 1 ({1})) = Φ 1 (Φ(N)) = N is not measurable, hence f Φ is not a measurable function. Also the measurable set Φ(N) cannot be Borel because the inverse images of Borel sets under continuous functions are Borel, but although Φ is continuous, Φ 1 (Φ(N)) = N is not even measurable.

1. Prove that the empty set is a subset of every set.

1. Prove that the empty set is a subset of every set. 1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: b89902089@ntu.edu.tw Proof: For any element x of the empty set, x is also an element of every set since

More information

Metric Spaces Joseph Muscat 2003 (Last revised May 2009)

Metric Spaces Joseph Muscat 2003 (Last revised May 2009) 1 Distance J Muscat 1 Metric Spaces Joseph Muscat 2003 (Last revised May 2009) (A revised and expanded version of these notes are now published by Springer.) 1 Distance A metric space can be thought of

More information

SOLUTIONS TO ASSIGNMENT 1 MATH 576

SOLUTIONS TO ASSIGNMENT 1 MATH 576 SOLUTIONS TO ASSIGNMENT 1 MATH 576 SOLUTIONS BY OLIVIER MARTIN 13 #5. Let T be the topology generated by A on X. We want to show T = J B J where B is the set of all topologies J on X with A J. This amounts

More information

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties SOLUTIONS TO EXERCISES FOR MATHEMATICS 205A Part 3 Fall 2008 III. Spaces with special properties III.1 : Compact spaces I Problems from Munkres, 26, pp. 170 172 3. Show that a finite union of compact subspaces

More information

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 A. Miller 1. Introduction. The definitions of metric space and topological space were developed in the early 1900 s, largely

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES Contents 1. Random variables and measurable functions 2. Cumulative distribution functions 3. Discrete

More information

MA651 Topology. Lecture 6. Separation Axioms.

MA651 Topology. Lecture 6. Separation Axioms. MA651 Topology. Lecture 6. Separation Axioms. This text is based on the following books: Fundamental concepts of topology by Peter O Neil Elements of Mathematics: General Topology by Nicolas Bourbaki Counterexamples

More information

1 if 1 x 0 1 if 0 x 1

1 if 1 x 0 1 if 0 x 1 Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or

More information

9 More on differentiation

9 More on differentiation Tel Aviv University, 2013 Measure and category 75 9 More on differentiation 9a Finite Taylor expansion............... 75 9b Continuous and nowhere differentiable..... 78 9c Differentiable and nowhere monotone......

More information

Point Set Topology. A. Topological Spaces and Continuous Maps

Point Set Topology. A. Topological Spaces and Continuous Maps Point Set Topology A. Topological Spaces and Continuous Maps Definition 1.1 A topology on a set X is a collection T of subsets of X satisfying the following axioms: T 1.,X T. T2. {O α α I} T = α IO α T.

More information

Introduction to Topology

Introduction to Topology Introduction to Topology Tomoo Matsumura November 30, 2010 Contents 1 Topological spaces 3 1.1 Basis of a Topology......................................... 3 1.2 Comparing Topologies.......................................

More information

Lecture Notes on Measure Theory and Functional Analysis

Lecture Notes on Measure Theory and Functional Analysis Lecture Notes on Measure Theory and Functional Analysis P. Cannarsa & T. D Aprile Dipartimento di Matematica Università di Roma Tor Vergata cannarsa@mat.uniroma2.it daprile@mat.uniroma2.it aa 2006/07 Contents

More information

How To Find Out How To Calculate A Premeasure On A Set Of Two-Dimensional Algebra

How To Find Out How To Calculate A Premeasure On A Set Of Two-Dimensional Algebra 54 CHAPTER 5 Product Measures Given two measure spaces, we may construct a natural measure on their Cartesian product; the prototype is the construction of Lebesgue measure on R 2 as the product of Lebesgue

More information

An example of a computable

An example of a computable An example of a computable absolutely normal number Verónica Becher Santiago Figueira Abstract The first example of an absolutely normal number was given by Sierpinski in 96, twenty years before the concept

More information

Finite dimensional topological vector spaces

Finite dimensional topological vector spaces Chapter 3 Finite dimensional topological vector spaces 3.1 Finite dimensional Hausdorff t.v.s. Let X be a vector space over the field K of real or complex numbers. We know from linear algebra that the

More information

CHAPTER 1 BASIC TOPOLOGY

CHAPTER 1 BASIC TOPOLOGY CHAPTER 1 BASIC TOPOLOGY Topology, sometimes referred to as the mathematics of continuity, or rubber sheet geometry, or the theory of abstract topological spaces, is all of these, but, above all, it is

More information

Mathematical Methods of Engineering Analysis

Mathematical Methods of Engineering Analysis Mathematical Methods of Engineering Analysis Erhan Çinlar Robert J. Vanderbei February 2, 2000 Contents Sets and Functions 1 1 Sets................................... 1 Subsets.............................

More information

Mathematics for Econometrics, Fourth Edition

Mathematics for Econometrics, Fourth Edition Mathematics for Econometrics, Fourth Edition Phoebus J. Dhrymes 1 July 2012 1 c Phoebus J. Dhrymes, 2012. Preliminary material; not to be cited or disseminated without the author s permission. 2 Contents

More information

INTRODUCTORY SET THEORY

INTRODUCTORY SET THEORY M.Sc. program in mathematics INTRODUCTORY SET THEORY Katalin Károlyi Department of Applied Analysis, Eötvös Loránd University H-1088 Budapest, Múzeum krt. 6-8. CONTENTS 1. SETS Set, equal sets, subset,

More information

No: 10 04. Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics

No: 10 04. Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics No: 10 04 Bilkent University Monotonic Extension Farhad Husseinov Discussion Papers Department of Economics The Discussion Papers of the Department of Economics are intended to make the initial results

More information

Metric Spaces. Chapter 1

Metric Spaces. Chapter 1 Chapter 1 Metric Spaces Many of the arguments you have seen in several variable calculus are almost identical to the corresponding arguments in one variable calculus, especially arguments concerning convergence

More information

Cardinality. The set of all finite strings over the alphabet of lowercase letters is countable. The set of real numbers R is an uncountable set.

Cardinality. The set of all finite strings over the alphabet of lowercase letters is countable. The set of real numbers R is an uncountable set. Section 2.5 Cardinality (another) Definition: The cardinality of a set A is equal to the cardinality of a set B, denoted A = B, if and only if there is a bijection from A to B. If there is an injection

More information

LECTURE NOTES IN MEASURE THEORY. Christer Borell Matematik Chalmers och Göteborgs universitet 412 96 Göteborg (Version: January 12)

LECTURE NOTES IN MEASURE THEORY. Christer Borell Matematik Chalmers och Göteborgs universitet 412 96 Göteborg (Version: January 12) 1 LECTURE NOTES IN MEASURE THEORY Christer Borell Matematik Chalmers och Göteborgs universitet 412 96 Göteborg (Version: January 12) 2 PREFACE These are lecture notes on integration theory for a eight-week

More information

Mathematics for Computer Science/Software Engineering. Notes for the course MSM1F3 Dr. R. A. Wilson

Mathematics for Computer Science/Software Engineering. Notes for the course MSM1F3 Dr. R. A. Wilson Mathematics for Computer Science/Software Engineering Notes for the course MSM1F3 Dr. R. A. Wilson October 1996 Chapter 1 Logic Lecture no. 1. We introduce the concept of a proposition, which is a statement

More information

Math 104: Introduction to Analysis

Math 104: Introduction to Analysis Math 104: Introduction to Analysis Evan Chen UC Berkeley Notes for the course MATH 104, instructed by Charles Pugh. 1 1 August 29, 2013 Hard: #22 in Chapter 1. Consider a pile of sand principle. You wish

More information

INTRODUCTION TO DESCRIPTIVE SET THEORY

INTRODUCTION TO DESCRIPTIVE SET THEORY INTRODUCTION TO DESCRIPTIVE SET THEORY ANUSH TSERUNYAN Mathematicians in the early 20 th century discovered that the Axiom of Choice implied the existence of pathological subsets of the real line lacking

More information

INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS

INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS STEVEN P. LALLEY AND ANDREW NOBEL Abstract. It is shown that there are no consistent decision rules for the hypothesis testing problem

More information

Extension of measure

Extension of measure 1 Extension of measure Sayan Mukherjee Dynkin s π λ theorem We will soon need to define probability measures on infinite and possible uncountable sets, like the power set of the naturals. This is hard.

More information

DEGREES OF ORDERS ON TORSION-FREE ABELIAN GROUPS

DEGREES OF ORDERS ON TORSION-FREE ABELIAN GROUPS DEGREES OF ORDERS ON TORSION-FREE ABELIAN GROUPS ASHER M. KACH, KAREN LANGE, AND REED SOLOMON Abstract. We construct two computable presentations of computable torsion-free abelian groups, one of isomorphism

More information

Follow links for Class Use and other Permissions. For more information send email to: permissions@pupress.princeton.edu

Follow links for Class Use and other Permissions. For more information send email to: permissions@pupress.princeton.edu COPYRIGHT NOTICE: Ariel Rubinstein: Lecture Notes in Microeconomic Theory is published by Princeton University Press and copyrighted, c 2006, by Princeton University Press. All rights reserved. No part

More information

BANACH AND HILBERT SPACE REVIEW

BANACH AND HILBERT SPACE REVIEW BANACH AND HILBET SPACE EVIEW CHISTOPHE HEIL These notes will briefly review some basic concepts related to the theory of Banach and Hilbert spaces. We are not trying to give a complete development, but

More information

TOPOLOGY: THE JOURNEY INTO SEPARATION AXIOMS

TOPOLOGY: THE JOURNEY INTO SEPARATION AXIOMS TOPOLOGY: THE JOURNEY INTO SEPARATION AXIOMS VIPUL NAIK Abstract. In this journey, we are going to explore the so called separation axioms in greater detail. We shall try to understand how these axioms

More information

CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e.

CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e. CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e. This chapter contains the beginnings of the most important, and probably the most subtle, notion in mathematical analysis, i.e.,

More information

RANDOM INTERVAL HOMEOMORPHISMS. MICHA L MISIUREWICZ Indiana University Purdue University Indianapolis

RANDOM INTERVAL HOMEOMORPHISMS. MICHA L MISIUREWICZ Indiana University Purdue University Indianapolis RANDOM INTERVAL HOMEOMORPHISMS MICHA L MISIUREWICZ Indiana University Purdue University Indianapolis This is a joint work with Lluís Alsedà Motivation: A talk by Yulij Ilyashenko. Two interval maps, applied

More information

FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES

FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES CHRISTOPHER HEIL 1. Cosets and the Quotient Space Any vector space is an abelian group under the operation of vector addition. So, if you are have studied

More information

Mathematics Course 111: Algebra I Part IV: Vector Spaces

Mathematics Course 111: Algebra I Part IV: Vector Spaces Mathematics Course 111: Algebra I Part IV: Vector Spaces D. R. Wilkins Academic Year 1996-7 9 Vector Spaces A vector space over some field K is an algebraic structure consisting of a set V on which are

More information

Comments on Quotient Spaces and Quotient Maps

Comments on Quotient Spaces and Quotient Maps 22M:132 Fall 07 J. Simon Comments on Quotient Spaces and Quotient Maps There are many situations in topology where we build a topological space by starting with some (often simpler) space[s] and doing

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

NOTES ON LINEAR TRANSFORMATIONS

NOTES ON LINEAR TRANSFORMATIONS NOTES ON LINEAR TRANSFORMATIONS Definition 1. Let V and W be vector spaces. A function T : V W is a linear transformation from V to W if the following two properties hold. i T v + v = T v + T v for all

More information

This chapter is all about cardinality of sets. At first this looks like a

This chapter is all about cardinality of sets. At first this looks like a CHAPTER Cardinality of Sets This chapter is all about cardinality of sets At first this looks like a very simple concept To find the cardinality of a set, just count its elements If A = { a, b, c, d },

More information

Continued Fractions and the Euclidean Algorithm

Continued Fractions and the Euclidean Algorithm Continued Fractions and the Euclidean Algorithm Lecture notes prepared for MATH 326, Spring 997 Department of Mathematics and Statistics University at Albany William F Hammond Table of Contents Introduction

More information

FIBER PRODUCTS AND ZARISKI SHEAVES

FIBER PRODUCTS AND ZARISKI SHEAVES FIBER PRODUCTS AND ZARISKI SHEAVES BRIAN OSSERMAN 1. Fiber products and Zariski sheaves We recall the definition of a fiber product: Definition 1.1. Let C be a category, and X, Y, Z objects of C. Fix also

More information

A CONSTRUCTION OF THE UNIVERSAL COVER AS A FIBER BUNDLE

A CONSTRUCTION OF THE UNIVERSAL COVER AS A FIBER BUNDLE A CONSTRUCTION OF THE UNIVERSAL COVER AS A FIBER BUNDLE DANIEL A. RAMRAS In these notes we present a construction of the universal cover of a path connected, locally path connected, and semi-locally simply

More information

The sample space for a pair of die rolls is the set. The sample space for a random number between 0 and 1 is the interval [0, 1].

The sample space for a pair of die rolls is the set. The sample space for a random number between 0 and 1 is the interval [0, 1]. Probability Theory Probability Spaces and Events Consider a random experiment with several possible outcomes. For example, we might roll a pair of dice, flip a coin three times, or choose a random real

More information

INTRODUCTION TO TOPOLOGY

INTRODUCTION TO TOPOLOGY INTRODUCTION TO TOPOLOGY ALEX KÜRONYA In preparation January 24, 2010 Contents 1. Basic concepts 1 2. Constructing topologies 13 2.1. Subspace topology 13 2.2. Local properties 18 2.3. Product topology

More information

arxiv:math/0510680v3 [math.gn] 31 Oct 2010

arxiv:math/0510680v3 [math.gn] 31 Oct 2010 arxiv:math/0510680v3 [math.gn] 31 Oct 2010 MENGER S COVERING PROPERTY AND GROUPWISE DENSITY BOAZ TSABAN AND LYUBOMYR ZDOMSKYY Abstract. We establish a surprising connection between Menger s classical covering

More information

Lecture 16 : Relations and Functions DRAFT

Lecture 16 : Relations and Functions DRAFT CS/Math 240: Introduction to Discrete Mathematics 3/29/2011 Lecture 16 : Relations and Functions Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT In Lecture 3, we described a correspondence

More information

Degrees that are not degrees of categoricity

Degrees that are not degrees of categoricity Degrees that are not degrees of categoricity Bernard A. Anderson Department of Mathematics and Physical Sciences Gordon State College banderson@gordonstate.edu www.gordonstate.edu/faculty/banderson Barbara

More information

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics Undergraduate Notes in Mathematics Arkansas Tech University Department of Mathematics An Introductory Single Variable Real Analysis: A Learning Approach through Problem Solving Marcel B. Finan c All Rights

More information

and s n (x) f(x) for all x and s.t. s n is measurable if f is. REAL ANALYSIS Measures. A (positive) measure on a measurable space

and s n (x) f(x) for all x and s.t. s n is measurable if f is. REAL ANALYSIS Measures. A (positive) measure on a measurable space RAL ANALYSIS A survey of MA 641-643, UAB 1999-2000 M. Griesemer Throughout these notes m denotes Lebesgue measure. 1. Abstract Integration σ-algebras. A σ-algebra in X is a non-empty collection of subsets

More information

Lemma 5.2. Let S be a set. (1) Let f and g be two permutations of S. Then the composition of f and g is a permutation of S.

Lemma 5.2. Let S be a set. (1) Let f and g be two permutations of S. Then the composition of f and g is a permutation of S. Definition 51 Let S be a set bijection f : S S 5 Permutation groups A permutation of S is simply a Lemma 52 Let S be a set (1) Let f and g be two permutations of S Then the composition of f and g is a

More information

Notes on metric spaces

Notes on metric spaces Notes on metric spaces 1 Introduction The purpose of these notes is to quickly review some of the basic concepts from Real Analysis, Metric Spaces and some related results that will be used in this course.

More information

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)! Math 7 Fall 205 HOMEWORK 5 SOLUTIONS Problem. 2008 B2 Let F 0 x = ln x. For n 0 and x > 0, let F n+ x = 0 F ntdt. Evaluate n!f n lim n ln n. By directly computing F n x for small n s, we obtain the following

More information

Elements of probability theory

Elements of probability theory 2 Elements of probability theory Probability theory provides mathematical models for random phenomena, that is, phenomena which under repeated observations yield di erent outcomes that cannot be predicted

More information

University of Miskolc

University of Miskolc University of Miskolc The Faculty of Mechanical Engineering and Information Science The role of the maximum operator in the theory of measurability and some applications PhD Thesis by Nutefe Kwami Agbeko

More information

EMBEDDING COUNTABLE PARTIAL ORDERINGS IN THE DEGREES

EMBEDDING COUNTABLE PARTIAL ORDERINGS IN THE DEGREES EMBEDDING COUNTABLE PARTIAL ORDERINGS IN THE ENUMERATION DEGREES AND THE ω-enumeration DEGREES MARIYA I. SOSKOVA AND IVAN N. SOSKOV 1. Introduction One of the most basic measures of the complexity of a

More information

Lecture 2: Universality

Lecture 2: Universality CS 710: Complexity Theory 1/21/2010 Lecture 2: Universality Instructor: Dieter van Melkebeek Scribe: Tyson Williams In this lecture, we introduce the notion of a universal machine, develop efficient universal

More information

Metric Spaces. Chapter 7. 7.1. Metrics

Metric Spaces. Chapter 7. 7.1. Metrics Chapter 7 Metric Spaces A metric space is a set X that has a notion of the distance d(x, y) between every pair of points x, y X. The purpose of this chapter is to introduce metric spaces and give some

More information

The Graphical Method: An Example

The Graphical Method: An Example The Graphical Method: An Example Consider the following linear program: Maximize 4x 1 +3x 2 Subject to: 2x 1 +3x 2 6 (1) 3x 1 +2x 2 3 (2) 2x 2 5 (3) 2x 1 +x 2 4 (4) x 1, x 2 0, where, for ease of reference,

More information

O-MINIMALISM HANS SCHOUTENS

O-MINIMALISM HANS SCHOUTENS THE JOURNAL OF SYMBOLIC LOGIC Volume 00, Number 0, XXX 0000 O-MINIMALISM HANS SCHOUTENS Abstract. An ordered structure is called o-minimalistic if it has all the first-order features of an o-minimal structure.

More information

6.2 Permutations continued

6.2 Permutations continued 6.2 Permutations continued Theorem A permutation on a finite set A is either a cycle or can be expressed as a product (composition of disjoint cycles. Proof is by (strong induction on the number, r, of

More information

3. Mathematical Induction

3. Mathematical Induction 3. MATHEMATICAL INDUCTION 83 3. Mathematical Induction 3.1. First Principle of Mathematical Induction. Let P (n) be a predicate with domain of discourse (over) the natural numbers N = {0, 1,,...}. If (1)

More information

PSEUDOARCS, PSEUDOCIRCLES, LAKES OF WADA AND GENERIC MAPS ON S 2

PSEUDOARCS, PSEUDOCIRCLES, LAKES OF WADA AND GENERIC MAPS ON S 2 PSEUDOARCS, PSEUDOCIRCLES, LAKES OF WADA AND GENERIC MAPS ON S 2 Abstract. We prove a Bruckner-Garg type theorem for the fiber structure of a generic map from a continuum X into the unit interval I. We

More information

God created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886)

God created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886) Chapter 2 Numbers God created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886) God created the integers and the rest is the work

More information

MEASURE AND INTEGRATION. Dietmar A. Salamon ETH Zürich

MEASURE AND INTEGRATION. Dietmar A. Salamon ETH Zürich MEASURE AND INTEGRATION Dietmar A. Salamon ETH Zürich 12 May 2016 ii Preface This book is based on notes for the lecture course Measure and Integration held at ETH Zürich in the spring semester 2014. Prerequisites

More information

GENERIC COMPUTABILITY, TURING DEGREES, AND ASYMPTOTIC DENSITY

GENERIC COMPUTABILITY, TURING DEGREES, AND ASYMPTOTIC DENSITY GENERIC COMPUTABILITY, TURING DEGREES, AND ASYMPTOTIC DENSITY CARL G. JOCKUSCH, JR. AND PAUL E. SCHUPP Abstract. Generic decidability has been extensively studied in group theory, and we now study it in

More information

Lecture Notes on Topology for MAT3500/4500 following J. R. Munkres textbook. John Rognes

Lecture Notes on Topology for MAT3500/4500 following J. R. Munkres textbook. John Rognes Lecture Notes on Topology for MAT3500/4500 following J. R. Munkres textbook John Rognes November 29th 2010 Contents Introduction v 1 Set Theory and Logic 1 1.1 ( 1) Fundamental Concepts..............................

More information

Fixed Point Theorems in Topology and Geometry

Fixed Point Theorems in Topology and Geometry Fixed Point Theorems in Topology and Geometry A Senior Thesis Submitted to the Department of Mathematics In Partial Fulfillment of the Requirements for the Departmental Honors Baccalaureate By Morgan Schreffler

More information

Practice with Proofs

Practice with Proofs Practice with Proofs October 6, 2014 Recall the following Definition 0.1. A function f is increasing if for every x, y in the domain of f, x < y = f(x) < f(y) 1. Prove that h(x) = x 3 is increasing, using

More information

The Markov-Zariski topology of an infinite group

The Markov-Zariski topology of an infinite group Mimar Sinan Güzel Sanatlar Üniversitesi Istanbul January 23, 2014 joint work with Daniele Toller and Dmitri Shakhmatov 1. Markov s problem 1 and 2 2. The three topologies on an infinite group 3. Problem

More information

Matrix Representations of Linear Transformations and Changes of Coordinates

Matrix Representations of Linear Transformations and Changes of Coordinates Matrix Representations of Linear Transformations and Changes of Coordinates 01 Subspaces and Bases 011 Definitions A subspace V of R n is a subset of R n that contains the zero element and is closed under

More information

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES I GROUPS: BASIC DEFINITIONS AND EXAMPLES Definition 1: An operation on a set G is a function : G G G Definition 2: A group is a set G which is equipped with an operation and a special element e G, called

More information

DEFINABLE TYPES IN PRESBURGER ARITHMETIC

DEFINABLE TYPES IN PRESBURGER ARITHMETIC DEFINABLE TYPES IN PRESBURGER ARITHMETIC GABRIEL CONANT Abstract. We consider the first order theory of (Z, +,

More information

Notes on descriptive set theory and applications to Banach spaces. Th. Schlumprecht

Notes on descriptive set theory and applications to Banach spaces. Th. Schlumprecht Notes on descriptive set theory and applications to Banach spaces Th. Schlumprecht Contents Chapter 1. Notation 5 Chapter 2. Polish spaces 7 1. Introduction 7 2. Transfer Theorems 9 3. Spaces of compact

More information

Solutions to Math 51 First Exam January 29, 2015

Solutions to Math 51 First Exam January 29, 2015 Solutions to Math 5 First Exam January 29, 25. ( points) (a) Complete the following sentence: A set of vectors {v,..., v k } is defined to be linearly dependent if (2 points) there exist c,... c k R, not

More information

Descriptive Set Theory

Descriptive Set Theory Descriptive Set Theory David Marker Fall 2002 Contents I Classical Descriptive Set Theory 2 1 Polish Spaces 2 2 Borel Sets 14 3 Effective Descriptive Set Theory: The Arithmetic Hierarchy 27 4 Analytic

More information

SMALL SKEW FIELDS CÉDRIC MILLIET

SMALL SKEW FIELDS CÉDRIC MILLIET SMALL SKEW FIELDS CÉDRIC MILLIET Abstract A division ring of positive characteristic with countably many pure types is a field Wedderburn showed in 1905 that finite fields are commutative As for infinite

More information

The Banach-Tarski Paradox

The Banach-Tarski Paradox University of Oslo MAT2 Project The Banach-Tarski Paradox Author: Fredrik Meyer Supervisor: Nadia S. Larsen Abstract In its weak form, the Banach-Tarski paradox states that for any ball in R, it is possible

More information

Tree sums and maximal connected I-spaces

Tree sums and maximal connected I-spaces Tree sums and maximal connected I-spaces Adam Bartoš drekin@gmail.com Faculty of Mathematics and Physics Charles University in Prague Twelfth Symposium on General Topology Prague, July 2016 Maximal and

More information

FIBRATION SEQUENCES AND PULLBACK SQUARES. Contents. 2. Connectivity and fiber sequences. 3

FIBRATION SEQUENCES AND PULLBACK SQUARES. Contents. 2. Connectivity and fiber sequences. 3 FIRTION SEQUENES ND PULLK SQURES RY MLKIEWIH bstract. We lay out some foundational facts about fibration sequences and pullback squares of topological spaces. We pay careful attention to connectivity ranges

More information

A domain of spacetime intervals in general relativity

A domain of spacetime intervals in general relativity A domain of spacetime intervals in general relativity Keye Martin Department of Mathematics Tulane University New Orleans, LA 70118 United States of America martin@math.tulane.edu Prakash Panangaden School

More information

Lecture 17 : Equivalence and Order Relations DRAFT

Lecture 17 : Equivalence and Order Relations DRAFT CS/Math 240: Introduction to Discrete Mathematics 3/31/2011 Lecture 17 : Equivalence and Order Relations Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT Last lecture we introduced the notion

More information

1 Homework 1. [p 0 q i+j +... + p i 1 q j+1 ] + [p i q j ] + [p i+1 q j 1 +... + p i+j q 0 ]

1 Homework 1. [p 0 q i+j +... + p i 1 q j+1 ] + [p i q j ] + [p i+1 q j 1 +... + p i+j q 0 ] 1 Homework 1 (1) Prove the ideal (3,x) is a maximal ideal in Z[x]. SOLUTION: Suppose we expand this ideal by including another generator polynomial, P / (3, x). Write P = n + x Q with n an integer not

More information

CS 103X: Discrete Structures Homework Assignment 3 Solutions

CS 103X: Discrete Structures Homework Assignment 3 Solutions CS 103X: Discrete Structures Homework Assignment 3 s Exercise 1 (20 points). On well-ordering and induction: (a) Prove the induction principle from the well-ordering principle. (b) Prove the well-ordering

More information

Cartesian Products and Relations

Cartesian Products and Relations Cartesian Products and Relations Definition (Cartesian product) If A and B are sets, the Cartesian product of A and B is the set A B = {(a, b) :(a A) and (b B)}. The following points are worth special

More information

Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 2

Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 2 CS 70 Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 2 Proofs Intuitively, the concept of proof should already be familiar We all like to assert things, and few of us

More information

Duality of linear conic problems

Duality of linear conic problems Duality of linear conic problems Alexander Shapiro and Arkadi Nemirovski Abstract It is well known that the optimal values of a linear programming problem and its dual are equal to each other if at least

More information

How To Understand The Theory Of Hyperreals

How To Understand The Theory Of Hyperreals Ultraproducts and Applications I Brent Cody Virginia Commonwealth University September 2, 2013 Outline Background of the Hyperreals Filters and Ultrafilters Construction of the Hyperreals The Transfer

More information

THE BANACH CONTRACTION PRINCIPLE. Contents

THE BANACH CONTRACTION PRINCIPLE. Contents THE BANACH CONTRACTION PRINCIPLE ALEX PONIECKI Abstract. This paper will study contractions of metric spaces. To do this, we will mainly use tools from topology. We will give some examples of contractions,

More information

n k=1 k=0 1/k! = e. Example 6.4. The series 1/k 2 converges in R. Indeed, if s n = n then k=1 1/k, then s 2n s n = 1 n + 1 +...

n k=1 k=0 1/k! = e. Example 6.4. The series 1/k 2 converges in R. Indeed, if s n = n then k=1 1/k, then s 2n s n = 1 n + 1 +... 6 Series We call a normed space (X, ) a Banach space provided that every Cauchy sequence (x n ) in X converges. For example, R with the norm = is an example of Banach space. Now let (x n ) be a sequence

More information

8 Divisibility and prime numbers

8 Divisibility and prime numbers 8 Divisibility and prime numbers 8.1 Divisibility In this short section we extend the concept of a multiple from the natural numbers to the integers. We also summarize several other terms that express

More information

A Short Proof that Compact 2-Manifolds Can Be Triangulated

A Short Proof that Compact 2-Manifolds Can Be Triangulated Inventiones math. 5, 160--162 (1968) A Short Proof that Compact 2-Manifolds Can Be Triangulated P. H. DOYLE and D. A. MORAN* (East Lansing, Michigan) The result mentioned in the title of this paper was

More information

ON FIBER DIAMETERS OF CONTINUOUS MAPS

ON FIBER DIAMETERS OF CONTINUOUS MAPS ON FIBER DIAMETERS OF CONTINUOUS MAPS PETER S. LANDWEBER, EMANUEL A. LAZAR, AND NEEL PATEL Abstract. We present a surprisingly short proof that for any continuous map f : R n R m, if n > m, then there

More information

( ) which must be a vector

( ) which must be a vector MATH 37 Linear Transformations from Rn to Rm Dr. Neal, WKU Let T : R n R m be a function which maps vectors from R n to R m. Then T is called a linear transformation if the following two properties are

More information

Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products

Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products Chapter 3 Cartesian Products and Relations The material in this chapter is the first real encounter with abstraction. Relations are very general thing they are a special type of subset. After introducing

More information

So let us begin our quest to find the holy grail of real analysis.

So let us begin our quest to find the holy grail of real analysis. 1 Section 5.2 The Complete Ordered Field: Purpose of Section We present an axiomatic description of the real numbers as a complete ordered field. The axioms which describe the arithmetic of the real numbers

More information

This asserts two sets are equal iff they have the same elements, that is, a set is determined by its elements.

This asserts two sets are equal iff they have the same elements, that is, a set is determined by its elements. 3. Axioms of Set theory Before presenting the axioms of set theory, we first make a few basic comments about the relevant first order logic. We will give a somewhat more detailed discussion later, but

More information

GENTLY KILLING S SPACES TODD EISWORTH, PETER NYIKOS, AND SAHARON SHELAH

GENTLY KILLING S SPACES TODD EISWORTH, PETER NYIKOS, AND SAHARON SHELAH GENTLY KILLING S SPACES TODD EISWORTH, PETER NYIKOS, AND SAHARON SHELAH Abstract. We produce a model of ZFC in which there are no locally compact first countable S spaces, and in which 2 ℵ 0 < 2 ℵ 1. A

More information

Group Theory. Contents

Group Theory. Contents Group Theory Contents Chapter 1: Review... 2 Chapter 2: Permutation Groups and Group Actions... 3 Orbits and Transitivity... 6 Specific Actions The Right regular and coset actions... 8 The Conjugation

More information

ON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING. 0. Introduction

ON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING. 0. Introduction ON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING Abstract. In [1] there was proved a theorem concerning the continuity of the composition mapping, and there was announced a theorem on sequential continuity

More information