Lecture 5: closed sets, and an introduction to continuous functions

Similar documents
Lecture 3: the classification of equivalence relations and the definition of a topological space

Sequence convergence, the weak T-axioms, and first countability

Building Infinite Processes from Finite-Dimensional Distributions

Today s Topics. Methods of proof Relationships to logical equivalences. Important definitions Relationships to sets, relations Special functions

2 Metric Spaces Definitions Exotic Examples... 3

Filters in Analysis and Topology

2. Introduction to commutative rings (continued)

Metric spaces and metrizability

Topology, Math 581, Fall 2017 last updated: November 24, Topology 1, Math 581, Fall 2017: Notes and homework Krzysztof Chris Ciesielski

Stat 451: Solutions to Assignment #1

Cosets and Lagrange s theorem

MAT137 - Term 2, Week 2

Math General Topology Fall 2012 Homework 1 Solutions

3. The Sheaf of Regular Functions

18.175: Lecture 2 Extension theorems, random variables, distributions

Countability. 1 Motivation. 2 Counting

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

ALGEBRAIC GEOMETRY COURSE NOTES, LECTURE 9: SCHEMES AND THEIR MODULES.

Notes on the Point-Set Topology of R Northwestern University, Fall 2014

MA554 Assessment 1 Cosets and Lagrange s theorem

Introduction to Topology

Consequences of Continuity

ON SPACE-FILLING CURVES AND THE HAHN-MAZURKIEWICZ THEOREM

University of Sheffield. School of Mathematics and Statistics. Metric Spaces MAS331/6352

Basic Definitions: Indexed Collections and Random Functions

T (s, xa) = T (T (s, x), a). The language recognized by M, denoted L(M), is the set of strings accepted by M. That is,

Exercise: Consider the poset of subsets of {0, 1, 2} ordered under inclusion: Date: July 15, 2015.

POL502: Foundations. Kosuke Imai Department of Politics, Princeton University. October 10, 2005

ABSTRACT ALGEBRA 1, LECTURE NOTES 4: DEFINITIONS AND EXAMPLES OF MONOIDS AND GROUPS.

Some Background Material

2.23 Theorem. Let A and B be sets in a metric space. If A B, then L(A) L(B).

We will begin our study of topology from a set-theoretic point of view. As the subject

Theorem. For every positive integer n, the sum of the positive integers from 1 to n is n(n+1)

This chapter contains a very bare summary of some basic facts from topology.

Math 101: Course Summary

15. LECTURE 15. I can calculate the dot product of two vectors and interpret its meaning. I can find the projection of one vector onto another one.

FOUNDATIONS OF ALGEBRAIC GEOMETRY CLASS 26

Real Analysis on Metric Spaces

Course 212: Academic Year Section 1: Metric Spaces

AN EXPLORATION OF THE METRIZABILITY OF TOPOLOGICAL SPACES

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

FOUNDATIONS OF ALGEBRAIC GEOMETRY CLASS 2

274 Microlocal Geometry, Lecture 2. David Nadler Notes by Qiaochu Yuan

Guide to Proofs on Sets

Math 541 Fall 2008 Connectivity Transition from Math 453/503 to Math 541 Ross E. Staffeldt-August 2008

Math 300 Introduction to Mathematical Reasoning Autumn 2017 Inverse Functions

3. Abstract Boolean Algebras

Supplementary Material for MTH 299 Online Edition

5 Set Operations, Functions, and Counting

WHY POLYNOMIALS? PART 1

Scott Taylor 1. EQUIVALENCE RELATIONS. Definition 1.1. Let A be a set. An equivalence relation on A is a relation such that:

Set theory and topology

CSE 20 DISCRETE MATH WINTER

MODULI TOPOLOGY. 1. Grothendieck Topology

FOUNDATIONS OF ALGEBRAIC GEOMETRY CLASS 24

CSE 20 DISCRETE MATH SPRING

Finite Math Section 6_1 Solutions and Hints

Algebraic Geometry

CHAPTER 3: THE INTEGERS Z

Math 31 Lesson Plan. Day 2: Sets; Binary Operations. Elizabeth Gillaspy. September 23, 2011

MATH 115, SUMMER 2012 LECTURE 4 THURSDAY, JUNE 21ST

22 Approximations - the method of least squares (1)

Equational Logic and Term Rewriting: Lecture I

EXAMPLES AND EXERCISES IN BASIC CATEGORY THEORY

Linear Independence Reading: Lay 1.7

Algebraic Topology M3P solutions 1

ALGEBRAIC GROUPS. Disclaimer: There are millions of errors in these notes!

The integers. Chapter 3

Consequences of Continuity

Math 40510, Algebraic Geometry

Computability Crib Sheet

Measures. Chapter Some prerequisites. 1.2 Introduction

2. Two binary operations (addition, denoted + and multiplication, denoted

The Lebesgue Integral

1 The Cantor Set and the Devil s Staircase

Lecture 10: Powers of Matrices, Difference Equations

Lecture 1. Renzo Cavalieri

are Banach algebras. f(x)g(x) max Example 7.4. Similarly, A = L and A = l with the pointwise multiplication

Sets and Functions. (As we will see, in describing a set the order in which elements are listed is irrelevant).

TOPOLOGY TAKE-HOME CLAY SHONKWILER

HW 4 SOLUTIONS. , x + x x 1 ) 2

Sets and Functions. MATH 464/506, Real Analysis. J. Robert Buchanan. Summer Department of Mathematics. J. Robert Buchanan Sets and Functions

CIS 2033 Lecture 5, Fall

CMPSCI 250: Introduction to Computation. Lecture #29: Proving Regular Language Identities David Mix Barrington 6 April 2012

/633 Introduction to Algorithms Lecturer: Michael Dinitz Topic: Matroids and Greedy Algorithms Date: 10/31/16

The cardinal comparison of sets

Lecture 11: Extrema. Nathan Pflueger. 2 October 2013

Final Review Sheet. B = (1, 1 + 3x, 1 + x 2 ) then 2 + 3x + 6x 2

Nondeterministic finite automata

2 Systems of Linear Equations

Spectral Graph Theory Lecture 2. The Laplacian. Daniel A. Spielman September 4, x T M x. ψ i = arg min

Lebesgue measure and integration

1 Topology Definition of a topology Basis (Base) of a topology The subspace topology & the product topology on X Y 3

TOPOLOGY HW 2. x x ± y

Math 31 Lesson Plan. Day 5: Intro to Groups. Elizabeth Gillaspy. September 28, 2011

Lecture 3: Sizes of Infinity

An Introduction to Non-Standard Analysis and its Applications

Sheaf theory August 23, 2016

Writing proofs for MATH 51H Section 2: Set theory, proofs of existential statements, proofs of uniqueness statements, proof by cases

UMASS AMHERST MATH 300 SP 05, F. HAJIR HOMEWORK 8: (EQUIVALENCE) RELATIONS AND PARTITIONS

Transcription:

Lecture 5: closed sets, and an introduction to continuous functions Saul Glasman September 16, 2016 Clarification on URL. To warm up today, let s talk about one more example of a topology. Definition 1. Let X be a set. The cofinite topology T fc on X is the following class of subsets: U T fc if and only if U = or X \ U is finite. In order to prove that T fc is a topology, it ll be convenient to introduce closed sets in a topological space. The definition is simple: Definition 2. Let X be a topological space. A set Z X is called closed if its complement Z \ X is open. We ll talk a lot more about closed sets later, but for now you should think of closed sets as sets which are in sharp focus : they have no fuzzy edges. Let s have some examples of closed sets. Example 3. Since X \ = X and X \ X =, and X are always closed. Example 4. In R, the closed interval [a, b] = {r R a r b} is a closed set. To show this, we need to show that the complement R \ [a, b] = (, a) (b, ) = {r R r < a or r > b} is open. But I can write this as a union of open intervals: (, a) = n N(a n, a) and similarly for (b, ). In particular, we can take a = b. Then the closed interval [a, a] is the single point {a}, and so {a} is a closed subset of R. This is very typical behavior: for many nice topological spaces, it s the case that single points are closed subsets. 1

Let s now recall an extra bit of set theory. Lemma 5. Taking complements turns intersections into unions and unions into intersections: Let X be a set and let (U i ) i I be a collection of subsets of X. Then X \ ( U i ) = \ U i ) i I i I(X and X \ ( i I U i ) = i I(X \ U i ). These two statements are known as demorgan s laws. If they re not immediately obvious to you, I recommend you try to prove them at home as an exercise. The upshot is that we can define a topology just as well with closed sets as with open sets: Lemma 6. Let X be a set and let T be a collection of subsets of X. Let T c = {X \ U U T } be the set of complements of elements of T. Then T is a topology if and only if T c satisfies the following conditions: 1. T c. 2. X T c. 3. An arbitrary intersection of elements of T c is in T c. 4. A finite union of elements of T c is in T c. Of course, if you know what the closed sets are, you also know what the open sets are: X \ (X \ U) = U, so (T c ) c = T. The point I want to make right now is that in some cases, such as the cofinite topology, it s easier to check the topology axioms with closed sets than with open sets. Indeed, a subset Z X is closed in the cofinite topology if and only if it s finite or equal to X. But 1. the empty set is finite; 2. X is equal to X; 3. an arbitrary intersection of finite sets is finite; 4. a finite union of finite sets is finite. 2

Although the indiscrete topology is pretty useless, the cofinite topology actually shows up in the wild (for example, in algebraic geometry). It s the coarsest topology which satisfies the reasonable condition that one-point sets are closed. Now let s learn how to relate topological spaces to one another: the study of continuous functions between topological spaces. Show of hands on who s encountered the ɛ δ definition of continuity before. Judging by prerequisites, it should be everyone. To give a brief reminder: a function f : R R is continuous if, informally, when x changes a small amount, f(x) only changes a small amount. This rules out functions with jumps, or crazy functions like { 1 x Q χ Q (x) = 0 x / Q. The actual definition is as follows: Definition 7. f is continuous at x R if for every ɛ > 0, there is some δ > 0 such that f((x δ, x + δ)) (f(x) ɛ, f(x) + ɛ). In other words, if x x < δ, then f(x) f(x ) < ɛ. f is continuous if it s continuous at x for every x R. Our goal for the moment is to rephrase this in a way that makes sense for any function between two topological spaces. Let s start by noting that we can be more flexible with the nature of our intervals: Lemma 8. f is continuous at x if and only if for every open interval set I containing f(x), there s an open interval J containing x such that f(j) I. Proof. Suppose f is continuous. Let I be an open interval with f(x) I. Then there s some ɛ > 0 such that (f(x) ɛ, f(x) + ɛ) I. Then for the corresponding δ whose existence is guaranteed by continuity, we can take J = (x δ, x + δ). Then f(j) I. Conversely, suppose f satisfies our condition. Take ɛ > 0, and let I = (f(x) ɛ, f(x)+ɛ). Then there s some open interval J with x J and f(j) I. There is some δ such that (x δ, x + δ) J. So f is continuous. With this lemma, we ve not only given ourselves more wiggle room and made the definition (I think) much prettier, we ve almost banished the real numbers from the definition statement - it s now a statement solely about open sets and open intervals. Let s make this definition even snappier with the aid of a little piece of language. Definition 9. Let X and Y be sets and f : X Y be a function. If U is a subset of Y, then the preimage of U under f is f 1 (U) = {x X f(x) U}. 3

Don t confuse this notation with the function f 1, the inverse of f when f is bijective! Preimages make perfect sense even if f is not bijective. If f is bijective, then the preimage of U is also the image of U under f 1, so there s no notational ambiguity. Here are some facts about preimages that I ll leave as an exercise: Lemma 10. Let f : X Y be a function. Then If (U i ) i I is a family of subsets of Y, then ( ) f 1 U i = f 1 (U i ). i I i I Similarly, f 1 ( i I U i ) = i I f 1 (U i ). If U, V Y, then f 1 (U \ V ) = f 1 (U) \ f 1 (V ). With this, we can reformulate the definition of continuity in a way that will generalize to topological spaces: Lemma 11. f : R R is continuous if and only if the preimage under f of any open set is open. Proof. To rephrase our previous lemma: f is continuous if and only if for every open set I and every x with f(x) I, there s an open interval J with x J and f(j) I. Rephrasing some more, this is the same as saying: for every x f 1 (I), there s an open interval J with x J and J f 1 (I). But this is the same as saying that f 1 (I) is open. Definition 12. Let X and Y be topological spaces. A function f : X Y is called continuous if the preimage under f of any open subset of Y is an open subset of X. A continuous function is often called a continuous map, or just a map. Remark 13. Since f 1 (Y \ U) = X \ f 1 (U), f is continuous if and only if the preimages under f of closed subsets are closed. It s time for some trivial examples. Example 14. The identity function is always continuous, of course, since id 1 (U) = U. 4

Example 15. Suppose that f : X Y and g : Y Z are continuous functions. Then g f is continuous: indeed, for U Z, (g f) 1 (U) = f 1 (g 1 (U)). But g 1 (U) is open since g is continuous, and so (g f) 1 (U) is open, since f is continuous. Example 16. Let X and X be two topological spaces with the same underlying set. Then id : X X is continuous if and only if the topology on X is at least as fine as the topology on X. Example 17. Suppose X has the discrete topology. Then for any space Y, any function f : X Y is continuous. This makes intuitive sense if you regard the discrete topology as making X into a bunch of loose points. Example 18. Suppose Y has the indiscrete topology. Then for any space X, any function f : X Y is continuous. Example 19. This one isn t quite as immediate as the others, but it s still very easy, and I ll leave the proof as an exercise: if Y has the cofinite topology, then f : X Y is continuous if and only if f 1 {y} is closed for each y Y. 5