Axioms for Set Theory

Similar documents
Chapter 1. Sets and Mappings

5 Set Operations, Functions, and Counting

ADVANCED CALCULUS - MTH433 LECTURE 4 - FINITE AND INFINITE SETS

Chapter 1 : The language of mathematics.

MATH 13 SAMPLE FINAL EXAM SOLUTIONS

MATH 220 (all sections) Homework #12 not to be turned in posted Friday, November 24, 2017

Math 4603: Advanced Calculus I, Summer 2016 University of Minnesota Notes on Cardinality of Sets

In N we can do addition, but in order to do subtraction we need to extend N to the integers

6 CARDINALITY OF SETS

Foundations of Mathematics MATH 220 FALL 2017 Lecture Notes

A BRIEF INTRODUCTION TO ZFC. Contents. 1. Motivation and Russel s Paradox

Handout 2 (Correction of Handout 1 plus continued discussion/hw) Comments and Homework in Chapter 1

In N we can do addition, but in order to do subtraction we need to extend N to the integers

The integers. Chapter 3

MATH 3300 Test 1. Name: Student Id:

1.4 Cardinality. Tom Lewis. Fall Term Tom Lewis () 1.4 Cardinality Fall Term / 9

Reverse Mathematics of Topology

Short notes on Axioms of set theory, Well orderings and Ordinal Numbers

Math 455 Some notes on Cardinality and Transfinite Induction

NOTES ON WELL ORDERING AND ORDINAL NUMBERS. 1. Logic and Notation Any formula in Mathematics can be stated using the symbols

Functions and cardinality (solutions) sections A and F TA: Clive Newstead 6 th May 2014

20 Ordinals. Definition A set α is an ordinal iff: (i) α is transitive; and. (ii) α is linearly ordered by. Example 20.2.

Section 2: Classes of Sets

Lecture Notes 1 Basic Concepts of Mathematics MATH 352

MAT115A-21 COMPLETE LECTURE NOTES

AN EXPLORATION OF THE METRIZABILITY OF TOPOLOGICAL SPACES

0 Sets and Induction. Sets

Math Fall 2014 Final Exam Solutions

Informal Statement Calculus

Mathematics Course 111: Algebra I Part I: Algebraic Structures, Sets and Permutations

Well Ordered Sets (continued)

This section will take the very naive point of view that a set is a collection of objects, the collection being regarded as a single object.

Notes on ordinals and cardinals

Finite and Infinite Sets

Solutions to Homework Set 1

Exercises for Unit VI (Infinite constructions in set theory)

Jónsson posets and unary Jónsson algebras

DO FIVE OUT OF SIX ON EACH SET PROBLEM SET

Sets, Structures, Numbers

Economics 204 Fall 2011 Problem Set 1 Suggested Solutions

SETS AND FUNCTIONS JOSHUA BALLEW

MATH FINAL EXAM REVIEW HINTS

Chapter 1. Sets and Numbers

Meta-logic derivation rules

Topology. Xiaolong Han. Department of Mathematics, California State University, Northridge, CA 91330, USA address:

S. Mrówka introduced a topological space ψ whose underlying set is the. natural numbers together with an infinite maximal almost disjoint family(madf)

Peter Kahn. Spring 2007

Numbers, sets, and functions

Lecture Notes on Discrete Mathematics. October 15, 2018 DRAFT

4 Countability axioms

REVIEW FOR THIRD 3200 MIDTERM

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

Part II. Logic and Set Theory. Year

Introduction to Proofs

3 COUNTABILITY AND CONNECTEDNESS AXIOMS

Cardinality and ordinal numbers

S15 MA 274: Exam 3 Study Questions

3. Only sequences that were formed by using finitely many applications of rules 1 and 2, are propositional formulas.

Principles of Real Analysis I Fall I. The Real Number System

Section 7.5: Cardinality

A Short Review of Cardinality

Chapter 2 Axiomatic Set Theory

Propositional Logic, Predicates, and Equivalence

Logical Connectives and Quantifiers

Let us first solve the midterm problem 4 before we bring up the related issues.

Homework 5. Solutions

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

Sets are one of the basic building blocks for the types of objects considered in discrete mathematics.

Copyright c 2007 Jason Underdown Some rights reserved. statement. sentential connectives. negation. conjunction. disjunction

2.1 Sets. Definition 1 A set is an unordered collection of objects. Important sets: N, Z, Z +, Q, R.

Foundations of Mathematics

Initial Ordinals. Proposition 57 For every ordinal α there is an initial ordinal κ such that κ α and α κ.

Math 3T03 - Topology

Introduction to Proofs in Analysis. updated December 5, By Edoh Y. Amiran Following the outline of notes by Donald Chalice INTRODUCTION

MATH 13 FINAL EXAM SOLUTIONS

MATH31011/MATH41011/MATH61011: FOURIER ANALYSIS AND LEBESGUE INTEGRATION. Chapter 2: Countability and Cantor Sets

Part II Logic and Set Theory

Mathematics 220 Workshop Cardinality. Some harder problems on cardinality.

Prof. Ila Varma HW 8 Solutions MATH 109. A B, h(i) := g(i n) if i > n. h : Z + f((i + 1)/2) if i is odd, g(i/2) if i is even.

A Logician s Toolbox

Sets, Models and Proofs. I. Moerdijk and J. van Oosten Department of Mathematics Utrecht University

Lebesgue measure on R is just one of many important measures in mathematics. In these notes we introduce the general framework for measures.

MATH 101: ALGEBRA I WORKSHEET, DAY #1. We review the prerequisites for the course in set theory and beginning a first pass on group. 1.

Final Exam Review. 2. Let A = {, { }}. What is the cardinality of A? Is

06 Recursive Definition and Inductive Proof

Tutorial on Axiomatic Set Theory. Javier R. Movellan

CMSC 27130: Honors Discrete Mathematics

MATH 215 Sets (S) Definition 1 A set is a collection of objects. The objects in a set X are called elements of X.

Selected problems from past exams

Definition: Let S and T be sets. A binary relation on SxT is any subset of SxT. A binary relation on S is any subset of SxS.

Infinite constructions in set theory

1. Propositional Calculus

Clearly C B, for every C Q. Suppose that we may find v 1, v 2,..., v n

MATH 102 INTRODUCTION TO MATHEMATICAL ANALYSIS. 1. Some Fundamentals

Week Some Warm-up Questions

Math 109 September 1, 2016

Math 280A Fall Axioms of Set Theory

Contribution of Problems

Souslin s Hypothesis

Slow P -point Ultrafilters

Transcription:

Axioms for Set Theory The following is a subset of the Zermelo-Fraenkel axioms for set theory. In this setting, all objects are sets which are denoted by letters, e.g. x, y, X, Y. Equality is logical identity: sets X, Y are equal (X = Y ) if and only if the letters X, Y denote the same set. There is a primitive notion of membership between sets (x X) which is read x is a member of X. 1. Equality Axiom: Sets X, Y are equal if they have the same members. ( X)( Y )(X = Y ( x)(x X x Y )) The set X is said to be a subset of Y every element of X is an element of Y. This statement is denoted by X Y. 2. Empty Set Axiom: There is a set with no elements. This set Z is denoted by {} or. ( Z)( x)x / Z 3. Doubleton Axiom: For any sets x, y there is a set whose elements are x, y. ( x)( y)( Z)(z Z (z = x z = y)) This set Z is denoted by {x, y}. The singleton set {x} is defined to be {x, x}. 4. Set Union Axiom: For any set X there is a set whose elements are the elements of the sets in the set X. ( X)( Z)(( z)(z Z ( Y )(Y X z Y ))) This set is denoted by X. If A, B are sets the union of A and B is defined to be {A, B}. This set is denoted by A B. We have x A B (x A x B). 5. Power Set Axiom: For any set X there is a set whose elements are the subsets of X. ( X)( Z)(z X z X) This set Z is called the power set of X and is denoted by P (X). 6. Set Formation Axiom: For any set A and any statement P (x) involving a variable set x there is a subset of A consisting of those elements x in A for which P (x) is true. ( X)( x)(x X (x A P (x))) This set is denoted by {x x A P (x)} or {x A P (x)}. This axiom is actually actually an axiom scheme; one axiom for each P (x). If C is a non-empty set, say C 1 C then ( C)(C C x C) x C 1 ( C)(C C = x C) so that the set C = {x ( C)(C C x C) exists by Axiom 6. The set C consists of those elements which lie in every set in the collection C. If C = {A, B} then C = {x x A x B} which is by definition A B, the intersection of the sets A and B. 1

7. Infinity Axiom: ( Z)( Z (z Z z {z} Z)) A set Z is called an inductive set if Z and z Z z {z} Z. The infinity axiom simply states that there is an inductive set. Theorem 1. If C is a non-empty collection of inductive sets then C is inductive. Proof. Let D = C. We have D since every set C C is inductive and hence C. Let x D. Then for every set C C we have x C which implies x {x} C since C is inductive. Thus x {x} D and D is inductive. Theorem 2. Let Z be an inductive set and let N be the intersection of the inductive subsets of Z. If D is any inductive set then N D. Proof. Since D Z is an inductive subset of Z we have N D Z and so N D. Definition 1. The set N of natural numbers is the smallest inductive set (with respect to the inclusion relation). The existence and uniqueness of N follows immediately from Theorem 2. If we define x + 1 to be x {x} and 0 =, 1 = 0 + 1 = {0}, 2 = 1 + 1 = {0, 1}, 3 = 2 + 1 = {0, 1, 2}, 4 = 3 + 1 = {0, 1, 2, 3},... then 0, 1, 2, 3, 4,... N. We now establish the elementary properties of the natural numbers. The first property which follows immediately from the fact that set N is the contained in every inductive set is the so-called Principle of Induction. If S is a subset of N which satisfies (a) 0 S (b) n S = n + 1 S then S = N. Proposition 1. ( n N)( m N)(m n = m n) Proof. Let S = {n N ( m N)(m n = m n)}. By the Principle of Induction is suffices to prove that S is inductive. We have 0 S since ( m N)(m 0 = m 0) is vacuously true as 0 = implies that m 0 is false for all m N. Now suppose that n S and that m n + 1. Then m n or m = n. If m n we have by our inductive hypothesis n S that m n which is also true if m = n. Since n n + 1 we obtain m n + 1 and hence that n + 1 S. Hence S is inductive. Corollary 1. ( m N)( n N)(m + 1 = n + 1 = m = n) Proof. If m + 1 = n + 1 then m n + 1 which implies m n or m = n and hence that m n by Proposition 1. Similarly n m + 1 implies n m. Hence m = n. Definition 2. The mapping σ : N N defined by σ(n) = n + 1 is called the successor mapping. We also denote σ(n) by n+. Theorem 3. The successor mapping is injective with image N {0}. 2

Proof. The injectivity follows from Corollary 1. The mapping σ is not surjective since 0 n + 1 for any n N. Now let S = {0} σ(n). It suffices to show that S = N. Since 0 we only have to show that n S = n + 1 S in order to prove that S is inductive. But n + 1 = σ(n) S for any n N so n + 1 S for any n S. Corollary 2. If n N and n 0 there is a unique m N with n = m + 1. This natural number m is denoted by n 1 or n and is called the immediate predecessor of n. Proposition 2. ( n N)n / n Proof. Let S = {n n / n}. Then 0 S since 0 / 0 =. Suppose that n S. Then n / n. We want to show that n + 1 / n + 1. Suppose to the contrary that n + 1 n + 1 = n {n}. Then n + 1 n or n + 1 = n which implies n + 1 n by Proposition 1. But then n n + 1 implies that n n which is a contradiction. Hence n + 1 S and S is inductive. Corollary 3. ( n N)( m N)(m n = m n) Proposition 3. ( n N)( m N)(m n m n) Proof. By Corollary 3 we only have to prove ( n N)( m N)(m n = m n. Let S = {n N ( m N)(m n = m n)}. Then 0 S since m 0 = is false for all m. Let n S and suppose that m n + 1 = n {n}. Then m n or n m. If m n then m = n or m n by the inductive hypothesis. In either case m n + 1. If n m then n m n + 1, which is not possible. Hence n + 1 S and S is inductive. Proposition 4. ( n N)( m N)(m n n m) Proof. By induction on n. Let S = {n N ( m N)(m n or n m)}. Then 0 S since 0 = m for any m. Let n S and let m N. Then m n or n m. But m n implies that m n + 1 and n m implies n m and hence n + 1 = n {n} m. Hence n + 1 S and S is inductive. Corollary 4. N is linearly ordered under inclusion. If m, n N we also denote m n by m n. Definition 3. For n N we let [0, n) denote the set {m N 0 m < n}. Note that by the definition of N we have [0, n) = n for any n N. Definition 4. Let X be a set. An infinite sequence of elements of X is a function with domain N and range a subset of X. If a is an infinite sequence it is denoted by (a n ) = (a 0, a 1,..., a n,...) where a n = a(n) = (n + 1) st term of a. A finite sequence of elements of X of length n is a function a with domain [0, n) and range a subset of X. If n = 0 the domain of the finite sequence is and the sequence is called the empty sequence. A finite sequence a of length n is usually denoted by (a 0, a 1,..., a n 1 ) with the convention that this denotes the empty sequence () when n = 0. An important method for constructing sequences is called recursion or definition by induction. The following theorem is an important special case called simple recursion. We will treat the general case later. 3

Theorem 3. Let X be a set, let x 0 X and let φ be a mapping of X into itself. Then there is a unique infinite sequence (a n ) such that a 0 = x 0 and a n+1 = φ(a n ) for n 0. Proof. We only give the main steps of the proof. The details of the proof are left to the reader. First one shows that for any n 1 there is a unique finite sequence a of length n such a 0 = x 0 and a m+1 = φ(a m ) for 0 m < n. Then, if a and b are two such finite sequences with a of length n and b of length p > n, one shows that a b, i.e. that a m = b m for m < n. If F is the collection of all such functions a of length 1 then F is the required infinite sequence. We now introduce the operations of addition and multiplication of natural numbers. For n N we define σ n : N N inductively by σ 0 = 1 N (the identity mapping on N), σ n+1 = σ σ n. We can similarly define f n for any mapping f : X X where X is any set. Proposition 4. ( n N)σ n (0) = n Proof. By induction on n. The proposition is true for n = 0 since σ 0 (0) = 1 N (0) = 0. If σ n (0) = n for some n N then σ n+1 (0) = σ(σ n (0)) = σ(n) = n + 1. Definition 3. Let m, n N. Then m + n = σ n (m) = σ n σ m (0), mn = (σ m ) n (0). We have m + 1 = σ(m), m + 0 = 0 + m = m, m 1 = 1 m = m, m 0 = 0 m = 0 and Theorem 4. Let m, n, p N. Then m + (n + 1) = (m + n) + 1, m(n + 1) = mn + m. (a) (m + n) + p = m + (n + p), (mn)p = m(np) (Associative Laws) (b) m + n = n + m, mn = nm (Commutative Laws) (c) m(n + p) = mn + mp, (m + n)p = mp + np (Distributive Laws) (d) m n ( p N)m = n + p (We denote p by m n.) Proof. (1) We first prove (m + n) + p = m + (n + p), the associative law for addition, by induction on p. Since (m + n) + 0 = m + n = m + (n + 0), it is true for p = 0. If it is true for some p then (m + n) + (p + 1) = ((m + n) + p) + 1 = (m + (n + p)) + 1 = m + ((n + p) + 1) = m + (n + (p + 1). Hence by induction it is true for all p. (2) We now prove m + n = n + m, the commutative law for addition, by induction. For n = 0 we have m + 0 = m = 0 + m. The proof of our inductive step will require the following auxiliary result. Lemma 1. ( n N)1 + n = n + 1 4

Proof of Lemma. We proceed by induction on n. For n = 0 we have 1 + 0 = 0 = 1 + 0 and if 1 + n = n + 1 for some n we have 1 + (n + 1) = (1 + n) + 1 = (n + 1) + 1. Resuming our inductive proof of the commutative law for addition, assume that m + n = n + m for some n. Then m + (n + 1) = (m + n) + 1 = (n + m) + 1 = 1 + (n + m) = (1 + n) + m = (n + 1) + m which completes the proof of the inductive step. (3) We now prove the distributive laws by induction on p. For p = 0 we have m(n + 0) = mn = mn + 0 = mn + m 0, (m + n) 0 = 0 = 0 + 0 = m 0 + n 0. If we assume that m(n + p) = mn + mp and (m + n)p = mp + np for some p then m(n+(p+1)) = m((n+p)+1) = m(n+p)+1 = (mn+mp)+1 = mn+(mp+m) = mn+m(p+1) and (m + n)(p + 1) = (m + n)p + (m + n) = ((mp + np) + m) + n = (m + (mp + np)) + n = ((m + mp) + np) + n = (mp + m) + (np + n) = m(p + 1) + n(p + 1). (4) We leave the proofs of the associative and commutative laws for multiplication as well as (d) to the reader. Definition 5. A set X is said to be finite if there is a bijection f : [0, n) X for some n N and infinite otherwise. If f : [0, n) X and g : [0, n) X are bijections then h = g 1 f : [0, n) [0, m) is a bijection. The following theorem shows that m = n so that the natural number n in Definition 4 is uniquely determined by the finite set X. This number is called the cardinality of X and is denoted by X. Theorem 5. If h : [0, n) [0, m) is a bijection then n = m. Proof. By induction on n. If n = 0 then [0, n) = so [0, m) = and m = 0. Assume that for some natural number n h : [0, n) [0, m) bijective = n = m and let g : [0, n + 1) [0, m) be a bijection. Then m > 0 and we set p = m. Let q = g(n) and let f : [0, m) [0, m) be the bijection defined by f(p) = q, f(q) = p, and f(x) = x otherwise. Then h = f g : [0, n + 1) [0, m) is bijective and h(n) = p. It follows that the restriction of h to [0, n) is a bijection of [0, n) with [0, p). By our inductive hypothesis this gives n = p so that n + 1 = p + 1 = m. Theorem 6. If X is a finite set and Y X then Y is finite and Y X. If X = 0 then X = and so Y =, a finite set with Y = 0 = X. Suppose for some n N the statement is true for any finite set X with X = n. Let X be a finite set with X = n + 1, let 5

f : [0, n + 1) X be a bijection, let c = f(n) and let X = X {c}. Then g : [0, n) X defined by g(i) = f(i) is a bijection which shows that X is finite with X = n. Now Y = Y {c} X implies by the inductive hypothesis that Y finite with Y X. Since Y Y + 1 X + 1 = X we are done. Theorem 7. If X, Y are disjoint finite sets then X Y is finite and X Y = X + Y. Proof. Let f : [0, m) and g : [0, n) [0, n) be bijections. Then the mapping h : [0, m + n) X Y defined by { f(i) if 0 i < m, h(i) = g(i m) if m i < n is bijective since X Y =. Corollary 5. If X, Y are finite and f : X Y is injective then X Y with equality if and only if f is surjective. Proof. We have Y = f(x) + Y f(x) with f(x) = X. Corollary 6. N is an infinite set. Proof. σ : N N is injective but not surjective. Corollary 7. If X 1, X 2,..., X n are pairwise disjoint finite sets then X 1 X 1 X n is finite and X 1 X 1 X n = X 1 + X 2 + + X n. Proof. The proof is by induction on n. The details are left to the reader. Note that n i=1 a i = a 1 + + a n is defined inductively by 0 a i = 0 (the empty sum is zero), i=1 n+1 n a i = ( a i ) + a n+1. i=1 i=1 Theorem 8. If X, Y are finite then X Y, X Y are finite and X Y + X Y = X + Y. Proof. The set X Y is the union of the pairwise disjoint sets X X Y, Y X Y, X Y so that X Y = X X Y + Y X Y + X Y. Hence X Y + X Y = X X Y + X Y + Y X = X + Y. Theorem 9. If X, Y are finite then X Y is finite and X Y = X Y. Proof. The proof is by induction on Y. The inductive step follows from the fact that if c / Y then X (Y {c}) is the union of the disjoint sets X Y and X {c} and the fact that X {c} = X. The details are left to the reader. Theorem 10. A set X is infinite if and only if there is an injective mapping f : N X. Proof. The proof requires the following additional axiom 6

Axiom of Choice. If C is a collection of non-empty subsets of a set X then there is a function φ with domain C such that φ(c) C for any C C. We apply this axiom in the case C is the set of non-empty subsets of the infinite set X. We then define an injective function f : N X inductively by f(n) = φ(x f([0, n)). This is a stronger form of recursion in which the value of the function at n depends on the values f(m) for m < n. That such a function exists can be proven by a variant of the proof given for simple recursion. The details are left to the reader. Definition 6. An infinite set X is said to be countable if there is a bijection f : N X and uncountable otherwise. Theorem 11. P (N) is uncountable. Proof. P (N) is infinite since n {n} defines an injective mapping of N into P (N). If f is a mapping of N into P (N) let A be the set of those n N with n / f(n). If A = f(m) for some m N then m A implies m / f(m) by definition of A which implies m / A, a contradiction. On the other hand m / A implies m / f(m) which implies m A, again a contradiction. We are thus led to conclude that the hypothesis A = f(m) for some m is false which implies that f is not surjective. Hence there is no surjective mapping and hence no bijective mapping from N to X. Definition 7. If m, n N then m n N is defined inductively by m 0 = 1, m n+1 = m n m. Theorem 12. If X, Y are finite sets then the set X Y of all mappings of Y into X is finite of cardinality X Y. Proof. The proof is by induction on Y. The inductive step uses the fact that if c / Y the mapping of X Y {c} into X Y X, defined by f (f Y, f(c)), is bijective. Here f Y denotes the restriction of f to Y ; for y Y, we have f Y (y) = f(y). The details are left to the reader. Corollary 8. The number of finite sequences (a 0, a 1,..., a n 1 ) of length n where the terms a i lie in a finite set of cardinality m is m n. Corollary 9. P ([0, n)) = 2 n Proof. This follows from the fact that there is a bijection between P (X) and 2 X where 2 = {0, 1}. Theorem 13. Let X, Y be finite sets with X = m Y = n. Then the number of injections of X into Y is n(n 1)... (n m + 1). Proof. The proof is by induction on m. The inductive step uses the fact that if a / X, the set of injective mappings of X {a} into Y is in one-to-one correspondence with the set S of pairs (f, b) where f : X Y is injective and b Y f(x). One proves that if T is the set of injective mappings of X into Y then S = T (n m). To do this we partition S as follows. For each f T let S f be the set of those pairs (f, b) with b / f(x). Then S f = Y f(x) = (n m) which implies the result. Corollary 10. If X is a finite set then the number of bijections of X with itself is n(n 1) 1 = n!. 7

Corollary 11. Let X be a set with X = n. If C n,m denotes the number of Y subsets of X with Y = m then m!c m,n = n(n 1) (n m + 1). Proof. For any subset Y of X with Y = m the number of injective mappings f : [0, m) X with f([0, m)) = Y is m!. If m, n N with n = mk for some k N we say that m divides n in N and denote it by m n. If m 0 then k is unique and is denoted by n m or n/m. Thus the number of m element subsets of an n element set is n(n 1) (n m + 1) n! C n,m = = m! m!(n m)!. Theorem 14. Every non-empty set of natural numbers has a smallest element. i.e. the natural numbers are well-ordered. Proof.. Let S be a nonempty set of natural numbers and let m S. If m is the smallest element of S we are done otherwise there is an element p of S with p < m. Thus we are reduced to showing that the finite set S [0, m) has a smallest element. We leave to the reader of proving by induction that any finite non-empty set of natural numbers has a smallest element. Strong Induction. ( n N)(( m N)(m < n = P (m)) = P (n)) = ( n N)P (n) Proof. If ( n N)P (n) is false let n be the smallest natural number for which P (n) is false. Then ( m N)(m < n = P (m)) is true. But this implies P (n) true by hypothesis which is a contradiction. Hence P (n) is true for all n. It would seem that in the strong form of induction you don t have to prove P (0) is true. But you do since ( m N)(m < 0 = P (m)) = P (0) is true if and only iff P (0) is true. More generally, we have P (n) true for all n k if P (k) is true and for all n > k the truth of P (n) follows from the truth of P (m) for k m < n. The proof of this fact is left to the reader. 8