# INTRODUCTION TO TOPOLOGY

Save this PDF as:

Size: px
Start display at page:

## Transcription

1 INTRODUCTION TO TOPOLOGY ALEX KÜRONYA In preparation January 24, 2010 Contents 1. Basic concepts 1 2. Constructing topologies Subspace topology Local properties Product topology Gluing topologies Proper maps Connectedness Separation axioms and the Hausdorff property More on the Hausdorff property Compactness and its relatives Local compactness and paracompactness Compactness in metric spaces Quotient spaces Quotient topology Fibre products and amalgamated sums Group actions on topological spaces Homotopy The fundamental group and some applications Definition and basic properties Applications Covering spaces Classification of covering spaces 97 References Basic concepts Topology is the area of mathematics which investigates continuity and related concepts. Important fundamental notions soon to come are for example open and closed sets, continuity, homeomorphism. 1

2 2 ALEX KÜRONYA Originally coming from questions in analysis and differential geometry, by now topology permeates mostly every field of math including algebra, combinatorics, logic, and plays a fundamental role in algebraic/arithmetic geometry as we know it today. Definition 1.1. A topological space is an ordered pair (X, τ), where X is a set, τ a collection of subsets of X satisfying the following properties (1), X τ, (2) U, V τ implies U V, (3) {U α α I} implies α I U α τ. The collection τ is called a topology on X, the pair (X, τ) a topological space. The elements of τ are called open sets. A subset F X is called closed, if its complement X F is open. Although the official notation for a topological space includes the topology τ, this is often suppressed when the topology is clear from the context. Remark 1.2. A quick induction shows that any finite intersection U 1 U k of open sets is open. It is important to point out that it is in general not true that an arbitrary (infinite) union of open sets would be open, and it is often difficult to decide whether it is so. Remark 1.3. Being open and closed are not mutually exclusive. In fact, subsets that are both open and closed often exist, and play a special role. The collection of closed subsets in a topological space determines the topology uniquely, just as the totality of open sets does. Hence, to give a topology on a set, it is enough to provide a collection of subsets satisfying the properties in the exercise below. Exercise 1.4. Prove the following basic properties of closed sets. If (X, τ) is a topological space, then (1), X are closed sets, (2) if F, G X are closed, then so is F G, (3) if {F α α I} is a collection of closed subsets, then α I F α is closed as well. Example 1.5 (Discrete topological space). Let X be an arbitrary set, τ def = 2 X, that is, we declare every subset of X to be open. One checks quickly that (X, τ) is indeed a topological space. Example 1.6 (Trivial topology). Considering the other extreme, the pair (X, {, X}) is also a topological space, with and X being the only open subsets. The previous two examples are easy to understand, however not that important in practice. The primordial example of a very important topological space coming from analysis is the real line. In fact R 1 and its higher-dimensional analogues are the

3 INTRODUCTION TO TOPOLOGY 3 prime source of our topological intuition. However, since there are copious examples of important topological spaces very much unlike R 1, we should keep in mind that not all topological spaces look like subsets of Euclidean space. Example 1.7. Let X = R 1. We will define a topology on R 1 which coincides with our intuition about open sets. Consider the collection τ def = { U R 1 U is the union of open intervals } where an open interval is defined as (a, b) def = {x R 1 a < x < b} with a, b R 1. This topology is called the classical or Hausdorff or Euclidean topology on R 1. By definition open intervals are in fact open subsets of R 1. Other examples of open sets are (a, + ) def = {x R 1 a < x} as can be seen from the description (a, + ) = n N (a, n). On the other hand, one can see that closed intervals [a, b] def = {x R 1 a x b} are indeed closed subsets of R 1. Exercise 1.8. Decide if [0, 1] R 1 is an open subset in the classical topology. Example 1.9 (Euclidean spaces). This example generalizes the real line to higher dimensions. Let X = R n, where R n = {(x 1,..., x n ) x i R} is the set of vectors with n real coordinates. We define the open ball with center x R n and radius ɛ > 0 as B(x, ɛ) def = {y R n x y < ɛ}, where x def = n i=1 x2 i. The so-called Euclidean or classical or Hausdorff topology on R n is given by the collection of arbitrary unions of open balls. More formally, a subset U R n is open in the Euclidean topology if and only if there exists a collection of open balls {B(x α, ɛ α ) α I} such that U = α I {B(x α, ɛ α ) α I}. Exercise Verify that R n with the classical topology is indeed a topological space. In what follows, R n will always be considered with the classical topology unless otherwise mentioned. The above definition of open sets with balls prompts the following generalization for metric spaces, a concept somewhere halfway between Euclidean spaces and general topological spaces. First, a reminder. Definition A set X equipped with a function d : X X R 0 is called a metric space (and the function d a metric or distance function) provided the following holds.

4 4 ALEX KÜRONYA (1) For every x X we have d(x, x) = 0; if d(x, y) = 0 for x, y X then x = y. (2) (Symmetry) For every x, y X we have d(x, y) = d(y, x). (3) (Triangle inequality) If x, y, z X are arbitrary elements, then d(x, y) d(x, z) + d(z, y). Exercise Show that (R n, d) with d(x, y) = x y is metric space. Definition Let (X, d) be a metric space. The open ball in X with center x X and radius ɛ > 0 is B(x, ɛ) def = {y X d(y, x) < ɛ}. The topology τ d induced by d consists of arbitrary unions of open balls in X. Remark A subset U (X, d) is open if and only if for every y U there exists ɛ > 0 (depending on y) such that B(y, ɛ) U. Most of the examples of topological spaces we meet in everyday life are induced by metrics (such topological spaces are called metrizable); however, as we will see, not all topologies arise from metrics. Example Let (X, τ) be a discrete topological space. Consider the function { 0 if x = y d(x, y) = 1 if x y One can see quickly that (X, d) is a metric space, and the topology induced by d is exactly τ. Exercise Let (X, d) be a metric space, and define { d 1 (x, y) def d(x, y) if d(x, y) 1 = 1 if d(x, y) > 1. Show that (X, d ) is also a metric space, moreover d, d 1 induce the same topology on X (we could replace 1 by any positive real number). Example 1.17 (Finite complement topology). Let X be an arbitrary set. The finite complement topology on X has and all subsets with a finite complement as open sets. Alternatively, the closed subsets with respect to the finite complement topology are X and all finite subsets. For the next example, we will quickly review what a partially ordered set is. Let X be an arbitrary set, a relation on X (i.e. X X). The relation is called a partial order, and (X, ) a partially ordered set if is reflexive, antisymmetric, and transitive; that is (1) (Reflexivity) for every x X we have x x (2) (Antisymmetry) x y and y x implies x = y

5 INTRODUCTION TO TOPOLOGY 5 (3) (Transitivity) x y and y z implies x z. Example 1.18 (Order topology). Let (X, ) be a partially ordered set. For an element a X consider the one-sided intervals {b X a < b} and {b X b < a}. The order topology τ consists of all finite unions of such. We turn to a marvellous application of topology to elementary number theory. The example is taken from [Aigner Ziegler, p.5.]. Example 1.19 (There are infinitely many primes in Z). We will give an almost purely topological proof of the fact that there are infinitely many prime numbers in Z. However, the topology we will use is not the one coming from R, but something a lot more esoteric, coming from doubly infinite arithmetic progressions. Let a, b Z, b 0. Denote N a,b def = {a + bn n Z}. A non-empty subset U Z will be designated to be open, if it is a union of sets of the form N a,b. Necessarily, we declare the empty set to be open as well. We need to check that the collection of subsets arising this way indeed forms a topology. Obviously, Z is open, and an arbitrary union of open sets is open as well. We are left with showing that the intersection of two open sets U 1, U 2 Z is open as well. To this end, let a U 1 U 2 be arbitrary, let a N a,b1 U 1 and a N a,b2 U 2 be arithmetic progressions containing a. Then a N a,b1 b 2 N a,b1 N a,b2 U 1 U 2, hence U 1 U 2 is again a union of two-way arithmetic progressions. An immediate consequence of the definition is that a non-empty open subset must be infinite. Another quick spinoff is the fact that the sets N a,b are not only open, but closed as well: N a,b = Z \ b 1 i=1 N a+i,b. Since any integer c Z \ { 1, 1} has at least one prime divisor p, every such c is contained in some N 0,p. Therefore Z \ { 1, 1} = N 0,p. p prime Suppose there are only finitely many primes in Z. Then the right-hand side of the above equality is a finite union of closed subsets, hence itself closed in Z. This would imply that { 1, 1} Z is open, which is impossible, as it is finite. Let us now recall how continuity is defined in calculus. A function f : R R is called continuous if for every x R and every ɛ > 0 there exists δ > 0 such that x x < δ whenever f(x) f(x ) < ɛ

6 6 ALEX KÜRONYA for all x X. The naive idea behind this notion is the points that are close to each other get mapped to points that are close to each other as well in some sense. The definition generalizes to metric spaces with no change, however, to obtain a notion of continuity for topological spaces, we need a reformulation in terms of open sets only. To this end, we reconsider how continuity is defined for functions between metric spaces. Let f : (X, d) (Y, d ) be a function of metric spaces; fix x X arbitrary. Then f is called continuous at x if for every ɛ > 0 there exists δ > 0 such that for every x X one has d (f(x), f(x )) < ɛ whenever d(x, x ) < δ. To phrase this in the language of open balls, it is equivalent to require that for every ɛ > 0 there exists δ > 0 for which f(b X (x, δ)) B Y (f(x), ɛ). Proposition A function f : X Y between two metric spaces is continuous if and only if for every open set U Y the inverse image f 1 (U) X is open as well. Proof. Assume first that f : (X, d) (Y, d ) is continuous, that is, f is continuous at every x X. Choose an open set U Y (in the topology induced by d, of course), let x f 1 (U) be arbitrary. Since f(x) is contained in the open set U Y, there exists ɛ x > 0 such that B Y (f(x), ɛ x ) U. By the continuity of f at x, we can find δ x > 0 with the property that f(b X (x, δ x ) B Y (f(x), ɛ x ), and hence But then B X (x, δ x ) f 1 (U). f 1 (U) = x f 1 (U) B X (x, δ x ), and hence f 1 (U) X is open. Conversely, let us assume that the inverse image of every open subset of Y under f is open in X. Fix a point x X, and ɛ > 0. Then B Y (f(x), ɛ) Y is open, hence so is f 1 (B Y (f(x), ɛ)), which in addition contains x. This implies that f 1 (B Y (f(x), ɛ)) contains an open ball with center x and some radius, which we can take to be δ. The result above motivates the following fundamental definition. Definition 1.21 (Continuity). Let X,Y be topological spaces, f : X Y an arbitrary function. Then f is said to be continuous if the inverse image of every open set in Y is open in X. More formally, for every U Y open, f 1 (U) X is open as well. A map of topological spaces is a continuous function. As taking inverse images preserves complements (i.e. f 1 (Y Z) = X f 1 (Z)), the continuity of f can be characterized equally well in terms of closed subsets of X: a function f : X Y is continuous exactly if f 1 (F ) X is closed for every closed subset Z Y.

7 INTRODUCTION TO TOPOLOGY 7 Exercise Prove the following statements. (1) Constant functions (ie. f : X Y with f(x) consisting of exactly one element) are continuous. (2) The identity function f : (X, τ) (X, τ), x x is continuous for every topological space X. (3) Let X, Y, Z be topological spaces. If the functions f : X Y and g : Y Z are continuous, then so is the composition g f : X Z given by (g f)(x) def = g(f(x)). Exercise Show that every function from a discrete topological space is continuous. Analogously, verify that every function to a trivial topological space is continuous. Interestingly enough, our definition of continuity is global in the sense that no reference is made to individual points of the spaces X and Y. In fact, as opposed to the usual definition of continuity of functions on the real line, it is somewhat more delicate and is less important in general to define continuity at a given point of a topological space. In order to find the right notion first we need to pin down what it means to be close to a given point. Definition Let (X, τ) be a topological space, x X an arbitrary point. A subset N X is a neighbourhood of x if there exists an open set U x for which x U N. Remark The terminology in the literature is ambiguous; it is often required that neighbourhoods be open. We call such a neighbourhood an open neighbourhood. Remark The intersection of two neighbourhoods of a given point is also a neighbourhood. If U X is an open set, then it is a neighbourhood of any of its points. In particular, X is a neighbourhood of every x X. Remark In a metric space X, a subset N X is a neighbourhood of a point x X if and only if N contains an open ball centered at x. Definition Let (X, τ) be a topological space, x X. A collection B x P (X) of subsets all containing x is called a neighbourhood basis of x if (1) every element of B x is a neighbourhood of x; (2) every neighbourhood of x contains an element of B x as a subset. Example Let X = R 1 be the real line with the Euclidean topology, x = 0. Then {( 1 n, 1 ) } n N n and {[ 1 n, 1 ] } n N n

8 8 ALEX KÜRONYA are both neighbourhood bases of x. To put it in a more general context, let (X, d) be a metric space with the induced topology, x X arbitrary. Then the collection {B(x, 1n ) n N } forms again a neighbourhood basis of x X. Example 1.30 (Non-examples). Consider again the case X = R 1, x = 0. collections of subsets below are not neighbourhood bases of x: {[ 0, 1 ) } n N, {( 1, n) n N}. n The Beside their inherent usefulness neighbourhoods and neighbourhood bases serve the purpose letting us define the continuity of a function at a point. Definition 1.31 (Continuity of a function at a point). Let f : X Y be a function between topological spaces, x X. We say that f is continuous at the point x, if for every neighbourhood N of f(x) in Y there exists a neighbourhood M of x in X such that f(m) N. Remark It is enough to require the condition in the definition for the elements of a neighbourhood basis of f(x). To put it more clearly, let B f(x) be a neighbourhood basis of f(x) in Y. Then f as above is continuous at x if and only if for every N B f(x) there exists a neighbourhood M of x in X with f(m) N. Remark Observe that for an arbitrary map of sets f : X Y and a subset A Y we have f(f 1 (A)) = A f(x), hence f(f 1 (A)) A. Therefore, if f : X Y is a function between topological spaces, f is continuous at a point x if and only if for every neighbourhood N of f(x) in Y, f 1 (N) is a neighbourhood of x X. Combining this observation with Remark 1.32, f is continuous at x precisely if for any neighbourhood basis B f(x) of f(x) in Y, the collection { f 1 (N) N B f(x) } is a neighbourhood basis of x. The next result is our first theorem; note that as opposed to calculus, it is no longer the definition of continuity, but rather something we need to prove. Theorem Let f : X Y be a function between topological spaces. Then f is continuous if and only if it is continuous at x for every x X Proof. Assume first that f : X Y is continuous, that is, the inverse image of every open set in Y under f is open in X. Fix a point x X; we will show that f is continuous at x. Let N be a neighbourhood of f(x) Y ; this means that

9 INTRODUCTION TO TOPOLOGY 9 there exists an open set V Y for which f(x) V N. By the continuity of f, f 1 (V ) X is open, moreover x f 1 (V ) f 1 (N), hence f 1 (N) is a neighbourhood of x X, and we are done by Remark To prove the other implication, assume that f is continuous at every x X; let V Y be an arbitrary open set. For any x f 1 (V ), the set V is a neighbourhood of f(x), therefore f 1 (V ) is a neighbourhood of x since f is continuous at x. This means that for every x f 1 (V ) there exists an open subset U x X for which x U x f 1 (V ). But then f 1 (V ) X is open as f 1 (V ) = U x, x f 1 (V ) i.e. it can be written as a union of open sets. The definition below is fundamental for the whole of topology. Definition A function f : X Y between topological spaces is said to be a homeomorphism, if it is bijective, and both f and f 1 are continuous. Two topological spaces X and Y are called homeomorphic is there exists a homeomorphism from one to the other. This relation is denoted by X Y. Remark The identitiy map id : X X is a homeomorphism. If f : X Y is a homeomorphism then so is f 1 : Y X. If f : X Y and g : Y Z are homeomorphisms, then so is g f : X Z. This implies that the relation being homeomorphic is reflexive, symmetric, and transitive, hence an equivalence relation. Exercise Fill in the details in Remark Example Note that a bijective continuous function is not necessarily a homeomorphism. We will see many examples of this phenomenon later, here are two simple ones. First, one can quickly check that if X is a trivial topological space (i.e. the only open sets in X are and X itself) then every function from every topological space to X is continuous. Consider now a topological space (X, τ) where τ is not the trivial topology. Then the identity function id: (X, {, X}) (X, τ) is not continuous. An analogous construction follows from the fact that every function from a discrete topological space to an arbitrary topological space is continuous. If two topological spaces are homeomorphic, then not only their respective sets of points, but also their collections of open sets are in a one-to-one correspondence. Homeomorphisms show us when two topological spaces should be considered to be the same in the eye of topology. More precisely, we cannot distinguish homeomorphic topological spaces based on their topological structure.

10 10 ALEX KÜRONYA In general it is not easy to show that two topological spaces are homeomorphic to each other; however, it can be equally difficult to prove that two topological spaces are not homeomorphic. We will see various methods both simple and hard that help us with such questions. For now, let us get back to our investigation of open sets. As there can be many more open sets than we can easily handle in a random topological space, it is often very useful to come up with a small selection of open subsets that determine the whole topology. Definition Let (X, τ) be a topological space, B P (X). The collection B is called a basis for the topology τ, if the open sets in X are precisely the unions of sets in B. A collection S P (X) is called a subbasis for the topology τ if the set B(S) consisting of finite intersections of elements of S forms a basis for τ. As the exercise below shows, if X is an arbitrary set, then any collection of subsets S P (X) is a subbasis for some topology on X. Exercise Let S P (X) be an arbitrary set of subsets of X; define τ as the collection of arbitrary unions of finite intersections of elements of S. Prove that τ is a topology on X. Also, show that if τ is a topology on X such that S τ, then τ τ. The topology defined above is called the topology generated by S. It is the smallest (with respect to inclusion of subsets of P (X)) topology where the elements of S are open. Note that the topology generated by a collection S might contain many more open sets than the elements of S (in fact often it contains many more than one would expect). Example Let X = {1, 2, 3} be a set with just three elements. We will consider various sets of subsets, and calculate the corresponding generated topologies. First take S = {{1}}. Then the set of finite intersections is B(S) = {X, {1}}, hence the topology generated by S (that is, the collection of arbitrary unions of elements of B(S)) is {, X, {1}}. Next, choose S = {{1, 2}, {2, 3}}. Then the set of finite intersections is B(S) = {X, {1, 2}, {2, 3}, {2}}, hence the generated topology is {, X, {1, 2}, {2, 3}, {2}}. Exercise Show that S = {{x} x X} generates the discrete topology on an arbitrary set X. Exercise How many pairwise non-homeomorphic topologies are there on the set X = {1, 2, 3}? {( ) } Example Let X = R 1 p, and S = q s p, q, r, s Z, q, s 0. Prove that S generates the Euclidean topology on R 1.

11 INTRODUCTION TO TOPOLOGY 11 There are several ways to measure how large a topological space is. Here is a pair of notions based on the cardinality of sets. Definition A topological space (X, τ) is called first countable, if every point x X has a countable neighbourhood basis. The topological space (X, τ) is second countable, if τ has a countable basis. Exercise Is a discrete topological space first countable? Second countable? Exercise Does second countability imply first countability? Example Euclidean spaces are second countable. The following collection gives a countable basis { B(x, 1 } m ) x Qn, m N. Example As evidenced by the collection {B(x, 1m ) m N } every metric space is first countable. However, not every metric space is second countable. As an example we can take any uncountable set (X = R for instance) with the discrete topology. We have seen earlier that the discrete topology is induced by a metric. In this topology every singleton set {x} is open, hence they need to belong to any basis for the topology; however there are uncountably many such sets. The next two notions we will only need later; this is nevertheless a good place to introduce them. Definition Let f : X Y be a function between topological spaces; f is called open if for every open set U X the image f(u) Y is open as well. We can define closed functions in a completely analogous fashion. Remark Note that being open or closed is not the same as being continuous. It is true however that every homeomorphism is open and closed at the same time. Later we will see examples that show that an open map is not necessarily closed, and vice versa. Exercise Come up with a definition for convergence and Cauchy sequences in metric spaces. Exercise (i) Show that the functions s, p : R 2 R given by s(x, y) = x + y p(x, y) = xy

12 12 ALEX KÜRONYA are continuous. (ii) Let f, g : X R be continuous functions. Then all of f ±g, f g are continuous; if g(x) 0 for all x X, then f is continuous as well. g Exercise (i) Is the function f : R 2 {(0, 0)} R 2 ( x f(x, y) = x 2 + y, y ) 2 x 2 + y 2 continuous on R 2 {(0, 0)}? (ii) Is there a continuous function g : R 2 R 2 for which g R 2 {(0,0)} = f? Exercise Let α, β, γ be arbitrary real numbers. Then the so-called open halfspace H = { (x, y, z) R 3 αx + βy + γz > 0 } is indeed open. Exercise Prove that the set { (x, y) R 2 x 2 + y 2 10 } is closed. Exercise Is the set consisting of all point of the form 1, n a natural number, n open/closed in R? Exercise Give examples of infinitely many open sets in R, the intersection of which is (i) open (ii) closed (iii) neither open nor closed. Exercise Show that the closed ball is indeed a closed subset of R n. Exercise Prove that D(x.δ) = {y R n x y δ} d 1 (f, g) = [a,b] f g dx is a metric on C[a, b]. Is this still true if we replace continuous functions by Riemann integrable ones? Definition Let p Z be a fixed prime number. For an arbitrary nonzero integer x Z let while we define ord p (0) def =. ord p (x) def = the highest power of p which divides x,

13 If α = x y Q, then we set INTRODUCTION TO TOPOLOGY 13 ord p (α) = ord p ( x y ) def = ord p (x) ord p (y). Note that the ord p (α) does not depend on the choice of x and y. Exercise Show that for every x, y Q (1) ord p (xy) = ord p (x) + ord p (y) (2) ord p (x + y) min{ord p (x), ord p (y)} with equality if ord p (x) ord p (y). Compute the p-adic order of 5, 100, 24, 1, 12 for p = 2, 3, Definition With notation as so far, let α, β Q. Then we set { 0 if α = β, d p (α, β) def = 1 p ordp(α β) This is called the p-adic distance of α and β. otherwise. Exercise Prove that (Q, d p ) is a metric space, which is in addition nonarchimedean, that is, for every x, y, z Q one has d p (x, y) max{d p (x, z), d p (z, y)}. Conclude that in (Q, d p ) every triangle is isosceles. Exercise Let f : X Y be a continuous map. If X is first/second countable, then so is f(x). Exercise Let f : X Y be a function between topological spaces. Show that f is continuous if and only if f(a) f(a) for every subset A X. Exercise If f : X Y is a continuous surjective open map, then F Y is closed exactly if f 1 (F ) X is closed. 2. Constructing topologies 2.1. Subspace topology. In this section we will start manufacturing new topologies out of old ones. There are various ways to do this, first we discuss topologies induced on subsets. Definition 2.1. Let X be a topological space, A X an arbitrary subset. The relative or subspace topology on A is the collection of intersections with open sets in X. In other words, a subset U A is open in the subspace topology if and only if there exists an open subset V X such that U = V A.

14 14 ALEX KÜRONYA Notation 2.2. To facilitate discussion and formalize the above definition, we introduce some notation. Let (X, τ) be a topological space, A X a subset. We denote the subspace topology on A by τ A def = {A V V τ}. Remark 2.3. Here is another way of thinking about the subspace topology. Let (X, τ) be a topological space, A X a subset, i : A X the inclusion function. Then τ A is the smallest topology which makes i continuous. The following is a related notion, which will play an important role in later developments. Definition 2.4. A pair is an ordered pair (X, A), with X a topological space, and A X an arbitrary subset equipped with the subspace topology. A continuous map of pairs f : (X, A) (Y, B) is a continuous map f : X Y for which f(a) B. Example 2.5. Let [0, 1] R. Open subsets in R are unions of open intervals. Therefore elements of τ A are arbitrary unions of sets of the form [0, 1] (a, b) with a, b R. For example [0, 1) = [0, 1] ( 1, 2) is open in [0, 1]. 2 2 Remark 2.6. A subset U A X which is open in the subset topology in A will typically not be open in X. Exercise 2.7. Prove the following statements. (1) If f : X Y is a map, A X a subspace, then f A : A Y given by f A (x) = f(x) whenever x A, is a continuous function. (2) Let X, Y be topological space, Y 1 Y 2 Y subspaces, f : X Y 2 a continuous function. Then f as a function X Y is also continuous. If f(x) Y 1, then f as a function from X to Y 1 is continuous as well. Proposition 2.8. Let (X, τ), (Y, τ ) be topological spaces, A, B X closed subsets such that X = A B. Assume we are given continuous functions f : (A, τ A ) Y, g : (B, τ B ) Y such that f A B = g A B. Then there exists a unique continuous function h : X Y for which Proof. Set h A = f and h B = g. h(x) def = { f(x) if x A g(x) if x B. This gives a well-defined function h : X Y by assumption.

15 Let F Y be a closed subset. Observe that INTRODUCTION TO TOPOLOGY 15 h 1 (F ) = f 1 (F ) g 1 (F ). Because f is continuous, f 1 (F ) A is closed, but then f 1 (F ) X is also closed, since A was closed in X. By the same argument, g 1 (F ) X is closed, too. But then h 1 (F ) X is again closed. With the help of the subspace topology we will generalize the familiar notions of the interior, boundary, and closure of a subset. Proposition 2.9. Let (X, τ) be a topological space, A X an arbitrary subset. (1) there exists a largest (with respect to inclusion) open (in X) set U A. This is called the interior of A, and denoted by int X (A), int(a), or A. (2) There exists a smallest ( with respect to inclusion ) closed ( in X ) subset F A. This is called the closure of A, and denoted by A X or simply A. (3) If A Y X, then A Y = A X Y. If Y X is closed, then A Y = A X. Proof. (1) Consider the union of all subsets U A which are open in X. This is by construction the largest open (in X) subset contained in A, and is uniquely determined. (2) Analogously to the previous case, the closure of A is the intersection of all subsets F A that are closed in X. Again, by construction it is uniquely determined. (3) Based on the construction of the closure of A in X we have ( ) A X Y = F Y = = = A Y A F,X A τ A F,X A τ (F Y ) A F Y,Y F τ Y F Y due to the definition of the subspace topology on Y. If Y X is closed, then A X Y, hence the result. Exercise In the situation of the Proposition, show that a point x X lies in the closure of A if and only if every open neighbourhood of x in X intersects A.

16 16 ALEX KÜRONYA Remark Even if A X seems naively relatively large (think Q R for example) it can happen that int A =. In a similar vein, although Q R is in a way smaller, we have Q = R. Exercise Prove that A X = X int X (X A). Proposition With notation as above, let Y X, B a basis for the topology τ. Then def B Y = {B Y B B} is a basis of the subspace topology τ Y. In a similar fashion, if x Y X is an arbitrary point, B x τ a neighbourhood def basis of x, then (B x ) Y = {N Y N B x } is a neighbourhood basis of x in τ Y. Proof. Left as an exercise. Definition Let again be (X, τ) a topological space, A X a subset. The boundary of A denoted by A is defined as A def = A X A. Exercise Show that A = A int X A. Definition A subset A X of a topological space is called dense, if A = X. A subset A X is callled nowhere dense, if int A =. As immediate examples observe that Q R is dense, while Z R is nowhere dense. Another simple situation is of course the discrete topology: in this case no subset different from X is dense, and no non-empty subset is nowhere dense. Exercise Is there an uncountable nowhere dense set in [0, 1]? Definition 2.18 (Limit point). Let (X, τ) be a topological space, A X arbitrary. A point x X is a limit point or accumulation point or cluster point of A, if x A {x}. A point x A is an isolated point of A if there exists an open (in X) neighbourhood U of x for which U A =. A limit point x of A may or may not lie in A. Remark Note that a point x is a limit point of A if and only if every neighbourhood of x intersects A in a point different from x. Exercise List all limit points of the following sets: (0, 1] R, { 1 n n N} R,(0, 1) {3} R, Q R. It is intuitively plausible that there is a close relation between the closure of a subset and its limit points.

17 INTRODUCTION TO TOPOLOGY 17 Proposition Let (X, τ) be a topological space, A X a subset, denote A the set of limit points of A. Then A = A A. Proof. First we prove that A A A. The containment A A is definitional. Let x A. Then every neighbourhood of x intersects A, hence x A. For the other direction, let x A A. As x A, every open neighbourhood intersects A, as x A, the intersection point must be a point of A other than x. Therefore x A. Corollary A subset A X is closed if and only if A contains all of its limit points. A fundamental and closely related notion is the convergence of sequences. Since in general it behaves rather erraticly and certainly not according to our intuition trained in Euclidean spaces, it is rarely discussed in this generality, in spite of the fact that there is nothing complicated about it. Definition Let (X, τ) be a topological space, (x n ) a sequence of points in X, x X arbitrary. We say that the sequence x n converges to x if for every neighbourhood B of x there exists a natural number M B such that x n B whenever n M B. This fact is denoted by x n x. The limit point of a subset of a topological space and the limit of a convergent sequence are different (although admittedly closely related) notions, and one should exercise caution not to confuse them. It is routine to check using the neighbourhood basis of a point consisting of open balls that the above definition is equivalent to the usual one in a metric space. It is very important to point out that in a general topological space the limit of a convergent sequence is not unique. One reason for this is that if U X is a minimal open set (i.e. it contains no other non-empty open sets) and x U is the limit of a sequence (x n ), then so is any other element y U. In extreme cases a sequence may converge to all points of the given topological space X (this happens for example in a trivial topological space, where every sequence of points converges to every point). Worse, continuity can no longer be characterized with the help of convergent sequences. Example 2.24 (Non-uniqueness of limits of sequences). Let X = {1, 2, 3}, τ =, {1, 2}, X. It is easy to see using the definition that all sequences in X converge to 3, while sequences with eventually only 1 s and 2 s in them converge to 1,2, and 3. Exercise Let X be a second countable topological space, A X an uncountable set. Verify that uncountably many points of A are limit points of A. Exercise Prove that a subset U X is open if and only if U = U \ U.

18 18 ALEX KÜRONYA Exercise Prove that if a topological space X has a countable dense subset, then every collection of disjoint open subsets is countable. Exercise Let f : X Y be a homeomorphism, x k a sequence in X. Then x k is convergent in X if and only if f(x k ) is convergent in Y Local properties. As we have seen, forming the interior and/or closure behaves well with respect to taking complements. It can make life difficult, however, that the same cannot be said about taking intersections. Another problem one faces is that knowing the interior or the closure of subspace is not enough to reconstruct the subspace itself. There are plenty of subsets A R for example with empty interior and closure the whole of R. Proposition Let U X be an open subset, A R arbitrary. Then A U X U = A X U. Corollary A subset F U is closed in U if and only if U F U X = F U. Exercise Prove that if U X is the interior of a closed subset F X, then int(u) = U. Proof. We start with unwinding the definitions. On this note, observe that ( ) A X U = F U = F U, while F U X U = ( F A,F X closed F A U,F X closed What we need to prove now is that F U = F A,F X closed F ) U = F A,F X closed F A U,F X closed F A U,F X closed F U. F U Since all closed sets F that occur on the left-hand side show up on the right-hand side as well, (1) F U F U F A,F X closed F A U,F X closed is immediate. Suppose now that there exists an element x X such that x F U but x F A,F X closed F A U,F X closed F U.

19 INTRODUCTION TO TOPOLOGY 19 This means that there exists a closed subset F X with F A U such that x F. As x belongs to the left-hand side of (1), x U, hence x U (F U). Consider now the subset G def = (X U) (U F ) X. Being the complement of the open set U U F in X, G is closed, moreover x G. However, since A = (A U) (A U) (F U) (X U) = G, we have found a term on the left-hand side of (1) which does not contain x, a contradiction. Exercise Find examples of open subsets in R that are not the interiors of their closures. Taking this route a bit further, we arrive at the following result, which motivates the local study of topologies. A collection {U α α I} of open subsets of X whose union is X is called an open cover of X. Proposition Let X be a topological space, A X an arbitrary subspace, (U α α I) an open cover of X. Then A is closed in X if and only if A U α is open in U α for every α I. Proof. The set A is closed in X if and only if X A is open in A. Since all the U α s are open in X, X A is open in X if and only if U α (X A) is open in U α for every α I. We say that being closed is a local property, as it can be tested on some (any) open cover of X. Note that it is very important that we take a cover of X, and not one of A. Definition A subset A X is called locally closed in X, if every a A has an open neighbourhood U a X such that A U a is closed in U a. Example The subset ( 1, 1) {0} R 2 is locally closed. Note that every open set is locally closed in any topological space by definition. Luckily it turns out that the structure of locally closed subsets is actually simpler than one might guess. Proposition A subspace A X of a topological space is locally closed if and only if A = F U, where F X is closed, and U X is open. Proof. Assume first that A has the shape A = F U, with F closed, and U open in def X. Then we can verify that A is locally closed immediately by taking U a = U for all a A in the definition of local closedness. Conversely, let A be locally closed, and (U a a A) an collection of suitable open subsets of X. Set U def = a A U a. Then A U, and the fact that being closed is a local property does the trick. Proposition Let f : X Y be a function between topological spaces, U τ X a collection, such that the union of some of its elements equals X. Then f is continuous if and only if f Uα : U α Y is continuous for every U α U.

20 20 ALEX KÜRONYA Proof. To come Product topology. We are looking for a way to put a topology on the Cartesian product X Y of two sets that is in a way natural. The product of the two sets does not come alone, but with two projection functions π X : X Y X, π X (x, y) = x, and π Y : X Y Y, π Y (x, y) = y. X Y π X πy X Y We will require that both projection functions pr X and pr Y be continuous. As we will see, this defines a unique topology on the Cartesian product, the minimal (containing the least number of open sets) for which the continuity of the projections holds. Let us have a look, which open sets are needed. Let U X be an open set. Then π 1 X (U) = U Y X Y has to be open, and analogously for open subsets V Y. Moreover, since π 1 X (U) π 1(V ) = (U Y ) (X V ) = U V, Y all subsets of the form U V are open when U X and V Y are open. It is quickly checked that the intersection of such sets is again of the same form, and hence form the basis of a topology. Definition Let X, Y be topological spaces. The product topology on the set X Y consists of arbitrary unions of subsets of the form U V, with U X,V Y open. It is important to point out that not all subsets of the product topology are products of open sets. The same definition holds for the product of finitely many topological spaces. All our results for two topological spaces will hold for arbitrary finite products. However, we will mostly content ourselves with the case of two spaces for ease of notation. Remark We can define analogously the product of infinitely many topological spaces. If {X α α I} is a collection of topological spaces, then the product topology on α I X α is given by the basis of open sets α I U α where U α X α are open for all α I, and U α = X α for all but finitely many α s. Lemma Let (X, τ X ) and (Y, τ Y ) be topological spaces, U and V bases for τ X and τ Y, respectively. Then the collection of sets W def = {S T S U, T V}

21 forms a basis of the product topology on X Y. INTRODUCTION TO TOPOLOGY 21 Proof. Let U τ X, V τ Y be arbitrary open sets. It is then enough to prove that U V can be written as a union of elements of W. To this end, write U = α I U α, V = β J V β, where U α U, and V β V for every α I, β J. Then U V = U α V β, a union of elements of W. α I,β J Remark Observe whenever we have topological spaces (X, τ X ), (Y, τ Y ) and subsets A X, B Y, then there are two natural ways to put a topology on A B. Namely, we can first take the subspace topologies on A and B induced from that of X and Y, respectively, and then form the product space of A and B. Or, we can consider A B as a subset of X Y and equip it with the subspace topology coming from X Y. The way out of this apparently unfortunate situation is that these two constructions produce the same result. This can be seen as follows. We will denote the topology on A B by first taking subspaces and then products by τ 1, and the topology obtained by taking the product first and then the subspace topology by τ 2. Now we show that the collection U def = {(U A) (V B) U τ X, V τ Y } is a basis for both τ 1 and τ 2, hence τ 1 = τ 2. Let U X, V Y be open sets. Since such subsets form a basis for the topology of X Y, subsets of the form (U V ) (A B) will provide a basis of the subspace topology on A B inherited from X Y. However, (U V ) (A B) = (U A) (V B), thus proving that U is a basis for τ 1. On the other hand, {U A U τ X }, {V B V τ Y } are bases for (τ X ) A and (τ Y ) B, respectively. Since the products of two bases form a basis for the product topology, U is indeed a basis for τ 2. The following result characterizes products up to a unique homeomorphism. The proof works with minimal changes in the infinite case, but we will only deal with the finite case now. Proposition Let X and Y be topological spaces. Then the product space X Y has the following property: for every topological space Z with continuous

22 22 ALEX KÜRONYA maps f X : Z X and f Y : Z Y there exists a unique map g : Z X Y such that the following diagram commutes. Z g f Y f X X Y π Y Y π X X In addition, X Y equipped with the product topology is the only such space up to a unique homeomorphism. The commutativity of the diagram means that π X g = f X and π Y g = f Y. Remark By general algebra Proposition 2.42 implies that the product topology on X Y is in fact unique up to a unique homeomorphism. Proof of Proposition Let Z be a topological space as in the statement with maps f X and f Y. Then the continuity of the diagram determines uniquely the set-theoretic function g : Z X Y via g(z) = (f X (z), f Y (z)). We need to prove that g is continuous. To this end, fix an open set U X Y. Then n U = V i W i with V i X and W i Y being open sets for every 1 i n. Hence ( n ) g 1 (U) = g 1 V i W i = = = i=1 i=1 n g 1 (V i W i ) i=1 n i=1 n i=1 which shows that g 1 (U) Z is indeed open. ( g 1 (π 1 X (V i) π 1 Y (W i)) ) ( f 1 X (V i) f 1 Y (W i) ),

23 INTRODUCTION TO TOPOLOGY 23 Exercise 2.44 (Products of metric spaces). Let N : R m R be any norm with the property that it is monotonically increasing function in every coordinate while keeping all others fixed. Consider finitely many metric spaces (X 1, δ 1 ),..., (X m, d m ). Show that the function d N ((x 1,..., x m ), (y 1,..., y m )) def = N(d 1 (x 1, y 1 ),..., d m (x m, y m )) defines a metric on the Cartesian product set X 1 X m. Prove that all such metrics d N are bounded by above and below by a positive multiple of each other, and each one gives rise to the product of the metric topologies on X 1 X m. Theorem Let X,Y and Z be topological spaces, f : Z X Y be an arbitrary function. Let f X = π X f and f Y = π Y f ( we will call them coordinate functions ). For any point z Z, the function f is continuous at z if and only if both functions f X and f Y are continuous at z. Proof. If f is continuous, then so are f X = f π X and f Y = f π Y since they are both compositions of continuous functions. Assume now that f X and f Y are continuous. Then Proposition 2.42 implies the existence of a unique continuous map g : Z X Y whose compositions with the appropriate projection maps are f X and f Y. But this implies f = g, and hence f must be continuous. Exercise Show that the projection maps π X : X Y X and π Y : X Y are open maps. Exercise Let A X, B Y be subspaces of the indicated topological spaces. Verify that A B = A B inside X Y. Exercise Let f : X Y and g : W Z be open maps. Show that f g : X W Y Z is open as well Gluing topologies. It happens often that one tries to construct topological spaces from small pieces, that somehow match and can be used to glue things together. We take on this method now systematically. For starters, consider the following situation. Let X be a topological space, {U α i I} an open cover of X. For a subset U X to be open is a local property, that is, U is open in X if and only U U α is open in U α for every α I. We can play a similar game with morphisms: continuing from the previous paragaph, let f : X Y be a continuous map; by restricting to the elements of the open cover we obtain continuous maps f α : U α Y that agree on the intersections, i.e. f α Uα U β = f β Uα U β

24 24 ALEX KÜRONYA Conversely, assume we are given continuous maps f α : U α Y for every α I that agree on the overlaps, i.e. f α Uα Uβ = f β Uα Uβ, then they fit together to give a unique (set-theoretic) function f : X Y satisfying f Uα = f α for every α I; moreover this function f is continuous. To see why this is so, take any open set V Y. Then f 1 (V ) X is open, since f 1 (V ) U α = fα 1 (V ) U α is open, and openness is a local property. The moral of the story is that once there is an open cover {U α i I} of X given, one can view continuous maps f : X Y as collections of continuous maps f α : U α X that are compatible on the overlaps. Now we will run this procedure in reverse. Theorem Let X be an arbitrary set, {X α α I} a collection of subsets of X whose union is X. Assume that for each α I there is given a topology τ α on X α such that for every α, β I the subset X α X β is open in both X α and X β ; moreover, the induced topologies on X α X β from τ α and τ β coincide. Then there is a unique topology τ on X inducing upon each X α the topology τ α. Definition We say that the topology τ constructed in Theorem 2.49 is obtained by gluing the topologies on the X α s. Note that it is not in general clear what properties of the X α s get inherited by X. For example if we glue together a compatible collection of Hausdorff topological spaces, then the result will not be in general Hausdorff, as the following example shows. Example Let X be the real line with the origin counted twice, that is, X = (R 0) {0 1 } {0 2 }, X 1 = (R {0}) {0 1 }, X 2 = (R {0}) {0 2 }. Give both X i s the topology of the real line, and X the one obtained by gluing X 1 and X 2 along their common open subset R {0 i }. Then the images of the two origins in X are different points, it is not however possible to separate them with disjoint open sets (any open set containing one of these points will contain an open interval around it). Proof of Theorem We deal with uniqueness first. Let τ be a topology on X inducing the τ α s on the X α s, and making all X α X open. Since the X α s form an open cover of X, a subset U X is open if and only if U X α is open for the topology τ Xα for every α I, if and only if U X α is open in τ α for every α I. This last condition however only depends on the X α s, hence uniqueness. We will use the argument in reverse to construct τ. Define τ def = {U X U X α τ α α I}. First we show that τ is indeed a topology on X. Obviously, and X belong to τ. Let now {U j j J} be an arbitrary collection of elements of τ, we want to prove

25 INTRODUCTION TO TOPOLOGY 25 that their union U lies again in τ. Thus, we need that U X α X α is open. But ( U X α = {Uj j J}) X α = j J(U j X α ), hence U X α is open in X α, since all intersections U j X α are open in X α by choice, and τ α is a topology on X α. A completely analogous reasoning takes care of finite intersections. We are left with showing that τ indeed induces τ α on X α. Take a subset U X α ; we have to show that U is in τ α if and only if it is in τ Xα. Since X α is τ-open in X, it is enough to prove that U τ α if and only if U τ. By definition of τ, U τ if and only if U X β τ β for every β I, in particular U X α = U is τ α -open. To settle the other direction, we need to prove that U X β X β is τ β -open for all β I. We are assuming that X α X β inherits the same topology from both X α and X β, and it is open in each, therefore the subset U X β X α X β is open in X β if and only if it is open for τ β Xα Xβ. This latter topology is however the same as τ α Xα Xβ by the compatibility assumption on the τ a s, so since U X β = U X α X β, it follows that U (X α X β ) is indeed open in X α X β for the topology induced by τ β Proper maps. Proper maps are not particularly important in classical topology, but play a prominent role in modern algebraic geometry. Their significance stems from the following situation. Example Let f : X Y, f : X Y be closed maps (ie. continuous functions mapping closed subsets to closed subsets), then f f : X X Y Y is not in general a closed map. As a concrete example, take X, X, Y, Y = R, let f : R R be the constant map t 0, f : R R the identity. Both maps are easily seen to be closed. Then f f : R R R R (x, x ) (0, x) is not a closed map, since for example it takes the closed set {(x, x ) xx = 1} R R to {(0, x ) x 0} R R, which is not closed. The notion of properness is motivated by this phenomenon. Definition A continuous map f : X Y is called proper, if for every topological space Z, the map is a closed map. f id Z : X Z Y Z (x, z) (f(x), z)

26 26 ALEX KÜRONYA Remark The defining property of proper maps is sometimes called universally closed. Remark Note that a proper map is necessarily closed, as shown by the case when Z is the one-point space. The result below provides the first examples of proper maps. Proposition The following are equivalent for an injective map f : X Y : (1) f is proper; (2) f is closed; (3) f is a homeomorphism of X onto a closed subset of Y. Proof. We have already proved that properness implies closedness. If f is a closed injection, then f : X f(x) Y is a continuous bijection. Since f is closed, f(x) Y is a closed subset, therefore the map f : X f(x) is closed as well, hence a homeomorphism. Assume now that f : X f(x) Y is a homeomorphism where f(x) Y closed. Then f id Z : X Z Y Z is a homeomorphism of X Z onto a closed subspace of Y Z, hence it is closed, that is, f is proper. Definition Let f : A B be a function between sets, Y B an arbitrary subset. Then f Y denotes the function f Y : f 1 (Y ) Y x f(x). Proposition Let f : X Y be a continuous map, {Y α α I} be a collection of subsets of Y for which one of the following conditions holds (1) α I Y α = Y ; (2) {Y α α I} is a locally finite closed covering of Y. If f Yα is proper for every α I, then f is proper as well. 3. Connectedness Here we formulate the mathematical version of the naive notion that a space is connected. Definition 3.1. A topological space X is connected if it cannot be written as the union of two disjoint nonempty open sets. Otherwise X is called disconnected. A subset A X is called clopen if A is both open and closed. Remark 3.2. The complement of a clopen subset is also clopen. X is connected if and only if the only clopen subsets in X are the empty set and itself. Definition 3.3. A discrete-valued map is a map f : X D with D a discrete topological space.

### Course 221: Analysis Academic year , First Semester

Course 221: Analysis Academic year 2007-08, First Semester David R. Wilkins Copyright c David R. Wilkins 1989 2007 Contents 1 Basic Theorems of Real Analysis 1 1.1 The Least Upper Bound Principle................

### Course 421: Algebraic Topology Section 1: Topological Spaces

Course 421: Algebraic Topology Section 1: Topological Spaces David R. Wilkins Copyright c David R. Wilkins 1988 2008 Contents 1 Topological Spaces 1 1.1 Continuity and Topological Spaces...............

### 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

### 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

### 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.......................................

### MAT2400 Analysis I. A brief introduction to proofs, sets, and functions

MAT2400 Analysis I A brief introduction to proofs, sets, and functions In Analysis I there is a lot of manipulations with sets and functions. It is probably also the first course where you have to take

### 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

### Sets and functions. {x R : x > 0}.

Sets and functions 1 Sets The language of sets and functions pervades mathematics, and most of the important operations in mathematics turn out to be functions or to be expressible in terms of functions.

### Chapter 1. Metric Spaces. Metric Spaces. Examples. Normed linear spaces

Chapter 1. Metric Spaces Metric Spaces MA222 David Preiss d.preiss@warwick.ac.uk Warwick University, Spring 2008/2009 Definitions. A metric on a set M is a function d : M M R such that for all x, y, z

### Compactness in metric spaces

MATHEMATICS 3103 (Functional Analysis) YEAR 2012 2013, TERM 2 HANDOUT #2: COMPACTNESS OF METRIC SPACES Compactness in metric spaces The closed intervals [a, b] of the real line, and more generally the

### NOTES ON MEASURE THEORY. M. Papadimitrakis Department of Mathematics University of Crete. Autumn of 2004

NOTES ON MEASURE THEORY M. Papadimitrakis Department of Mathematics University of Crete Autumn of 2004 2 Contents 1 σ-algebras 7 1.1 σ-algebras............................... 7 1.2 Generated σ-algebras.........................

### 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

### 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

### 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

### Polish spaces and standard Borel spaces

APPENDIX A Polish spaces and standard Borel spaces We present here the basic theory of Polish spaces and standard Borel spaces. Standard references for this material are the books [143, 231]. A.1. Polish

### 6. Metric spaces. In this section we review the basic facts about metric spaces. d : X X [0, )

6. Metric spaces In this section we review the basic facts about metric spaces. Definitions. A metric on a non-empty set X is a map with the following properties: d : X X [0, ) (i) If x, y X are points

### 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

### 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

### Geometry 2: Remedial topology

Geometry 2: Remedial topology Rules: You may choose to solve only hard exercises (marked with!, * and **) or ordinary ones (marked with! or unmarked), or both, if you want to have extra problems. To have

### 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

### Structure of Measurable Sets

Structure of Measurable Sets In these notes we discuss the structure of Lebesgue measurable subsets of R from several different points of view. Along the way, we will see several alternative characterizations

### 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

### Sequences and Convergence in Metric Spaces

Sequences and Convergence in Metric Spaces Definition: A sequence in a set X (a sequence of elements of X) is a function s : N X. We usually denote s(n) by s n, called the n-th term of s, and write {s

### 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..............................

### 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,

### 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

### BOREL SETS, WELL-ORDERINGS OF R AND THE CONTINUUM HYPOTHESIS. Proof. We shall define inductively a decreasing sequence of infinite subsets of N

BOREL SETS, WELL-ORDERINGS OF R AND THE CONTINUUM HYPOTHESIS SIMON THOMAS 1. The Finite Basis Problem Definition 1.1. Let C be a class of structures. Then a basis for C is a collection B C such that for

### {f 1 (U), U F} is an open cover of A. Since A is compact there is a finite subcover of A, {f 1 (U 1 ),...,f 1 (U n )}, {U 1,...

44 CHAPTER 4. CONTINUOUS FUNCTIONS In Calculus we often use arithmetic operations to generate new continuous functions from old ones. In a general metric space we don t have arithmetic, but much of it

### Sets and Cardinality Notes for C. F. Miller

Sets and Cardinality Notes for 620-111 C. F. Miller Semester 1, 2000 Abstract These lecture notes were compiled in the Department of Mathematics and Statistics in the University of Melbourne for the use

### 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,

### REAL ANALYSIS I HOMEWORK 2

REAL ANALYSIS I HOMEWORK 2 CİHAN BAHRAN The questions are from Stein and Shakarchi s text, Chapter 1. 1. Prove that the Cantor set C constructed in the text is totally disconnected and perfect. In other

### 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

### Math212a1010 Lebesgue measure.

Math212a1010 Lebesgue measure. October 19, 2010 Today s lecture will be devoted to Lebesgue measure, a creation of Henri Lebesgue, in his thesis, one of the most famous theses in the history of mathematics.

### Elementary Number Theory We begin with a bit of elementary number theory, which is concerned

CONSTRUCTION OF THE FINITE FIELDS Z p S. R. DOTY Elementary Number Theory We begin with a bit of elementary number theory, which is concerned solely with questions about the set of integers Z = {0, ±1,

### 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.............................

### CARDINALITY, COUNTABLE AND UNCOUNTABLE SETS PART ONE

CARDINALITY, COUNTABLE AND UNCOUNTABLE SETS PART ONE With the notion of bijection at hand, it is easy to formalize the idea that two finite sets have the same number of elements: we just need to verify

### Problem Set. Problem Set #2. Math 5322, Fall December 3, 2001 ANSWERS

Problem Set Problem Set #2 Math 5322, Fall 2001 December 3, 2001 ANSWERS i Problem 1. [Problem 18, page 32] Let A P(X) be an algebra, A σ the collection of countable unions of sets in A, and A σδ the collection

### In mathematics you don t understand things. You just get used to them. (Attributed to John von Neumann)

Chapter 1 Sets and Functions We understand a set to be any collection M of certain distinct objects of our thought or intuition (called the elements of M) into a whole. (Georg Cantor, 1895) In 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

### Topology and Convergence by: Daniel Glasscock, May 2012

Topology and Convergence by: Daniel Glasscock, May 2012 These notes grew out of a talk I gave at The Ohio State University. The primary reference is [1]. A possible error in the proof of Theorem 1 in [1]

### This chapter describes set theory, a mathematical theory that underlies all of modern mathematics.

Appendix A Set Theory This chapter describes set theory, a mathematical theory that underlies all of modern mathematics. A.1 Basic Definitions Definition A.1.1. A set is an unordered collection of elements.

### 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

### POWER SETS AND RELATIONS

POWER SETS AND RELATIONS L. MARIZZA A. BAILEY 1. The Power Set Now that we have defined sets as best we can, we can consider a sets of sets. If we were to assume nothing, except the existence of the empty

### Classical Analysis I

Classical Analysis I 1 Sets, relations, functions A set is considered to be a collection of objects. The objects of a set A are called elements of A. If x is an element of a set A, we write x A, and if

### 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.

### Infinite product spaces

Chapter 7 Infinite product spaces So far we have talked a lot about infinite sequences of independent random variables but we have never shown how to construct such sequences within the framework of probability/measure

### S(A) X α for all α Λ. Consequently, S(A) X, by the definition of intersection. Therefore, X is inductive.

MA 274: Exam 2 Study Guide (1) Know the precise definitions of the terms requested for your journal. (2) Review proofs by induction. (3) Be able to prove that something is or isn t an equivalence relation.

### Finite Sets. Theorem 5.1. Two non-empty finite sets have the same cardinality if and only if they are equivalent.

MATH 337 Cardinality Dr. Neal, WKU We now shall prove that the rational numbers are a countable set while R is uncountable. This result shows that there are two different magnitudes of infinity. But we

### A Topology Primer. Preface. Lecture Notes 2001/2002. Klaus Wirthmüller. http://www.mathematik.uni-kl.de/ wirthm/de/top.html

A Topology Primer Lecture Notes 2001/2002 Klaus Wirthmüller http://www.mathematik.uni-kl.de/ wirthm/de/top.html Preface These lecture notes were written to accompany my introductory courses of topology

### Sets, Relations and Functions

Sets, Relations and Functions Eric Pacuit Department of Philosophy University of Maryland, College Park pacuit.org epacuit@umd.edu ugust 26, 2014 These notes provide a very brief background in discrete

### CHAPTER 5: MODULAR ARITHMETIC

CHAPTER 5: MODULAR ARITHMETIC LECTURE NOTES FOR MATH 378 (CSUSM, SPRING 2009). WAYNE AITKEN 1. Introduction In this chapter we will consider congruence modulo m, and explore the associated arithmetic called

### 3. Prime and maximal ideals. 3.1. Definitions and Examples.

COMMUTATIVE ALGEBRA 5 3.1. Definitions and Examples. 3. Prime and maximal ideals Definition. An ideal P in a ring A is called prime if P A and if for every pair x, y of elements in A\P we have xy P. Equivalently,

### Math 4310 Handout - Quotient Vector Spaces

Math 4310 Handout - Quotient Vector Spaces Dan Collins The textbook defines a subspace of a vector space in Chapter 4, but it avoids ever discussing the notion of a quotient space. This is understandable

### 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......

### 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

### Lecture 1-1,2. Definition. Sets A and B have the same cardinality if there is an invertible function f : A B.

Topology Summary This is a summary of the results discussed in lectures. These notes will be gradually growing as the time passes by. Most of the time proofs will not be given. You are supposed to be able

### Introducing Functions

Functions 1 Introducing Functions A function f from a set A to a set B, written f : A B, is a relation f A B such that every element of A is related to one element of B; in logical notation 1. (a, b 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

### Weak topologies. David Lecomte. May 23, 2006

Weak topologies David Lecomte May 3, 006 1 Preliminaries from general topology In this section, we are given a set X, a collection of topological spaces (Y i ) i I and a collection of maps (f i ) i I such

### INCIDENCE-BETWEENNESS GEOMETRY

INCIDENCE-BETWEENNESS GEOMETRY MATH 410, CSUSM. SPRING 2008. PROFESSOR AITKEN This document covers the geometry that can be developed with just the axioms related to incidence and betweenness. The full

### 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

### 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.

### Analytic Sets Vadim Kulikov Presentation 11 March 2008

Analytic Sets Vadim Kulikov Presentation 11 March 2008 Abstract. The continuous images of Borel sets are not usually Borel sets. However they are measurable and that is the main purpose of this lecture.

### Open and Closed Sets

Open and Closed Sets Definition: A subset S of a metric space (X, d) is open if it contains an open ball about each of its points i.e., if x S : ɛ > 0 : B(x, ɛ) S. (1) Theorem: (O1) and X are open sets.

### 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

### 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

### Math 225A, Differential Topology: Homework 3

Math 225A, Differential Topology: Homework 3 Ian Coley October 17, 2013 Problem 1.4.7. Suppose that y is a regular value of f : X Y, where X is compact and dim X = dim Y. Show that f 1 (y) is a finite

### 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

### Mathematics for Computer Science

Mathematics for Computer Science Lecture 2: Functions and equinumerous sets Areces, Blackburn and Figueira TALARIS team INRIA Nancy Grand Est Contact: patrick.blackburn@loria.fr Course website: http://www.loria.fr/~blackbur/courses/math

### 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

### 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

### (Basic definitions and properties; Separation theorems; Characterizations) 1.1 Definition, examples, inner description, algebraic properties

Lecture 1 Convex Sets (Basic definitions and properties; Separation theorems; Characterizations) 1.1 Definition, examples, inner description, algebraic properties 1.1.1 A convex set In the school geometry

### THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS

THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS KEITH CONRAD 1. Introduction The Fundamental Theorem of Algebra says every nonconstant polynomial with complex coefficients can be factored into linear

### Commutative Algebra seminar talk

Commutative Algebra seminar talk Reeve Garrett May 22, 2015 1 Ultrafilters Definition 1.1 Given an infinite set W, a collection U of subsets of W which does not contain the empty set and is closed under

### 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

### Review for Final Exam

Review for Final Exam Note: Warning, this is probably not exhaustive and probably does contain typos (which I d like to hear about), but represents a review of most of the material covered in Chapters

### 3. Equivalence Relations. Discussion

3. EQUIVALENCE RELATIONS 33 3. Equivalence Relations 3.1. Definition of an Equivalence Relations. Definition 3.1.1. A relation R on a set A is an equivalence relation if and only if R is reflexive, symmetric,

### 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

### 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

### 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)

### 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

### MODULAR ARITHMETIC. a smallest member. It is equivalent to the Principle of Mathematical Induction.

MODULAR ARITHMETIC 1 Working With Integers The usual arithmetic operations of addition, subtraction and multiplication can be performed on integers, and the result is always another integer Division, on

### Quotient Rings and Field Extensions

Chapter 5 Quotient Rings and Field Extensions In this chapter we describe a method for producing field extension of a given field. If F is a field, then a field extension is a field K that contains F.

### 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 },

### Domain representations of topological spaces

Theoretical Computer Science 247 (2000) 229 255 www.elsevier.com/locate/tcs Domain representations of topological spaces Jens Blanck University of Gavle, SE-801 76 Gavle, Sweden Received October 1997;

### 3 σ-algebras. Solutions to Problems

3 σ-algebras. Solutions to Problems 3.1 3.12 Problem 3.1 (i It is clearly enough to show that A, B A = A B A, because the case of N sets follows from this by induction, the induction step being A 1...

### Foundations of Mathematics I Set Theory (only a draft)

Foundations of Mathematics I Set Theory (only a draft) Ali Nesin Mathematics Department Istanbul Bilgi University Kuştepe Şişli Istanbul Turkey anesin@bilgi.edu.tr February 12, 2004 2 Contents I Naive

### 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

### Making New Spaces from Old Ones - Part 2

Making New Spaces from Old Ones - Part 2 Renzo s math 570 1 The torus A torus is (informally) the topological space corresponding to the surface of a bagel, with topology induced by the euclidean topology.

### MATH 289 PROBLEM SET 1: INDUCTION. 1. The induction Principle The following property of the natural numbers is intuitively clear:

MATH 89 PROBLEM SET : INDUCTION The induction Principle The following property of the natural numbers is intuitively clear: Axiom Every nonempty subset of the set of nonnegative integers Z 0 = {0,,, 3,

### Measure Theory. 1 Measurable Spaces

1 Measurable Spaces Measure Theory A measurable space is a set S, together with a nonempty collection, S, of subsets of S, satisfying the following two conditions: 1. For any A, B in the collection S,

### 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

### Continuous first-order model theory for metric structures Lecture 2 (of 3)

Continuous first-order model theory for metric structures Lecture 2 (of 3) C. Ward Henson University of Illinois Visiting Scholar at UC Berkeley October 21, 2013 Hausdorff Institute for Mathematics, Bonn

### Chap2: The Real Number System (See Royden pp40)

Chap2: The Real Number System (See Royden pp40) 1 Open and Closed Sets of Real Numbers The simplest sets of real numbers are the intervals. We define the open interval (a, b) to be the set (a, b) = {x

### 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

### MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets.

MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets. Norm The notion of norm generalizes the notion of length of a vector in R n. Definition. Let V be a vector space. A function α

### 4. Expanding dynamical systems

4.1. Metric definition. 4. Expanding dynamical systems Definition 4.1. Let X be a compact metric space. A map f : X X is said to be expanding if there exist ɛ > 0 and L > 1 such that d(f(x), f(y)) Ld(x,

### 13 Infinite Sets. 13.1 Injections, Surjections, and Bijections. mcs-ftl 2010/9/8 0:40 page 379 #385

mcs-ftl 2010/9/8 0:40 page 379 #385 13 Infinite Sets So you might be wondering how much is there to say about an infinite set other than, well, it has an infinite number of elements. Of course, an infinite