In words: Let be the relation on Z given by a b if a b. (Note that we use language like in definitions, where if actually means if and only if.

Similar documents
Review: set theoretic definition of the numbers. Natural numbers:

Functions. Ex. f : R 0 Ñ R 0 defined by x fiñ x 2.

9 < Ways to place n distinguishable objects= S(n, k) = into k indistinguishable boxes so that no box is left empty We stated in section 6.

Lecture 3: Equivalence Relations

ad = cb (1) cf = ed (2) adf = cbf (3) cf b = edb (4)

Math 4310 Solutions to homework 1 Due 9/1/16

20 MATHEMATICS POLYNOMIALS

Theoretical foundations of Gaussian quadrature

MATH 101A: ALGEBRA I PART B: RINGS AND MODULES 35

Theory of the Integral

Strong Bisimulation. Overview. References. Actions Labeled transition system Transition semantics Simulation Bisimulation

Natural examples of rings are the ring of integers, a ring of polynomials in one variable, the ring

set is not closed under matrix [ multiplication, ] and does not form a group.

378 Relations Solutions for Chapter 16. Section 16.1 Exercises. 3. Let A = {0,1,2,3,4,5}. Write out the relation R that expresses on A.

p-adic Egyptian Fractions

MTH 505: Number Theory Spring 2017

Lecture 2: Fields, Formally

The Regulated and Riemann Integrals

Introduction to Group Theory

Handout: Natural deduction for first order logic

Is there an easy way to find examples of such triples? Why yes! Just look at an ordinary multiplication table to find them!

CM10196 Topic 4: Functions and Relations

Coalgebra, Lecture 15: Equations for Deterministic Automata

MAT 215: Analysis in a single variable Course notes, Fall Michael Damron

Infinite Geometric Series

MathCity.org Merging man and maths

Math 104: Introduction to Analysis

Chapter 1: Fundamentals

CSCI FOUNDATIONS OF COMPUTER SCIENCE

Theory of Computation Regular Languages. (NTU EE) Regular Languages Fall / 38

Math Solutions to homework 1

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac

Finite Automata Theory and Formal Languages TMV027/DIT321 LP4 2018

8. Complex Numbers. We can combine the real numbers with this new imaginary number to form the complex numbers.

Theory of Computation Regular Languages

Linear Algebra 1A - solutions of ex.4

M A T H F A L L CORRECTION. Algebra I 2 1 / 0 9 / U N I V E R S I T Y O F T O R O N T O

Math 61CM - Solutions to homework 9

38 Riemann sums and existence of the definite integral.

Homework 4. 0 ε 0. (00) ε 0 ε 0 (00) (11) CS 341: Foundations of Computer Science II Prof. Marvin Nakayama

Chapter 14. Matrix Representations of Linear Transformations

Minimal DFA. minimal DFA for L starting from any other

Semigroup of generalized inverses of matrices

Linearly Similar Polynomials

The Banach algebra of functions of bounded variation and the pointwise Helly selection theorem

Math 360: A primitive integral and elementary functions

Intuitionistic Fuzzy Lattices and Intuitionistic Fuzzy Boolean Algebras

Multidimensional. MOD Planes. W. B. Vasantha Kandasamy Ilanthenral K Florentin Smarandache

Results on Planar Near Rings

Boolean Algebra. Boolean Algebras

1 Structural induction

Finite-State Automata: Recap

MORE FUNCTION GRAPHING; OPTIMIZATION. (Last edited October 28, 2013 at 11:09pm.)

a,b a 1 a 2 a 3 a,b 1 a,b a,b 2 3 a,b a,b a 2 a,b CS Determinisitic Finite Automata 1

Finite Automata. Informatics 2A: Lecture 3. John Longley. 22 September School of Informatics University of Edinburgh

CS 301. Lecture 04 Regular Expressions. Stephen Checkoway. January 29, 2018

Parse trees, ambiguity, and Chomsky normal form

f(x)dx . Show that there 1, 0 < x 1 does not exist a differentiable function g : [ 1, 1] R such that g (x) = f(x) for all

1 Probability Density Functions

Advanced Calculus I (Math 4209) Martin Bohner

Quadratic Forms. Quadratic Forms

Lecture 3 ( ) (translated and slightly adapted from lecture notes by Martin Klazar)

Bernoulli Numbers Jeff Morton

The Henstock-Kurzweil integral

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique?

Properties of the Riemann Integral

Finite Field Arithmetic and Implementations. Xinmiao Zhang Case Western Reserve University

CMPSCI 250: Introduction to Computation. Lecture #31: What DFA s Can and Can t Do David Mix Barrington 9 April 2014

Math 231E, Lecture 33. Parametric Calculus

W. We shall do so one by one, starting with I 1, and we shall do it greedily, trying

308K. 1 Section 3.2. Zelaya Eufemia. 1. Example 1: Multiplication of Matrices: X Y Z R S R S X Y Z. By associativity we have to choices:

Math Lecture 23

CS 373, Spring Solutions to Mock midterm 1 (Based on first midterm in CS 273, Fall 2008.)

Homework 3 Solutions

Absolute values of real numbers. Rational Numbers vs Real Numbers. 1. Definition. Absolute value α of a real

Lecture 1: Introduction to integration theory and bounded variation

Here we study square linear systems and properties of their coefficient matrices as they relate to the solution set of the linear system.

In this skill we review equations that involve percents. review the meaning of proportion.

Lecture 3. Limits of Functions and Continuity

Graph Theory. Dr. Saad El-Zanati, Faculty Mentor Ryan Bunge Graduate Assistant Illinois State University REU. Graph Theory

Lecture 3. In this lecture, we will discuss algorithms for solving systems of linear equations.

CBSE-XII-2015 EXAMINATION. Section A. 1. Find the sum of the order and the degree of the following differential equation : = 0

CH 9 INTRO TO EQUATIONS

Presentation Problems 5

More on automata. Michael George. March 24 April 7, 2014

Fundamentals of Computer Science

Closure Properties of Regular Languages

Recursively Enumerable and Recursive. Languages

FORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY. FLAC (15-453) - Spring L. Blum

Read section 3.3, 3.4 Announcements:

Recitation 3: More Applications of the Derivative

arxiv: v1 [math.ra] 1 Nov 2014

PARTIAL FRACTION DECOMPOSITION

STRUCTURE OF CONCURRENCY Ryszard Janicki. Department of Computing and Software McMaster University Hamilton, ON, L8S 4K1 Canada

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides.

SUMMER KNOWHOW STUDY AND LEARNING CENTRE

CS375: Logic and Theory of Computing

THE QUADRATIC RECIPROCITY LAW OF DUKE-HOPKINS. Circa 1870, G. Zolotarev observed that the Legendre symbol ( a p

Riemann is the Mann! (But Lebesgue may besgue to differ.)

1 Structural induction, finite automata, regular expressions

Transcription:

Reltions A binry reltion on set A is subset R Ñ A ˆ A, where elements p, bq re written s b. Exmple: A Z nd R t b bu. In words: Let be the reltion on Z given by b if b. (Note tht we use lnguge like in definitions, where if ctully mens if nd only if.) Exmple: A R nd R t b bu. In words: Let be the reltion on R given by b if b. Exmple: A Z nd R t b b pmod 3qu. In words: Let be the reltion on Z given by b if b pmod 3q. More exmples of (binry) reltions: 1. For A numbersystem,let b if b. R, S, T 2. For A numbersystem,let b if b. not R, not S, T 3. For A R, let b if b 0. not R, S, not T 4. For A set of people, let b if is (full) sibling of b. not R, S, T 5. For A set of people, let b if nd b spek common lnguge. R, S, not T A binry reltion on set A is... (R) reflexive if for ll P A; (S) symmetric if b implies b ; (T) trnsitive if b nd b c implies c, i.e. p b ^ b cq ñ c An equivlence reltion on set A is binry reltion tht is reflexive, symmetric, nd trnsitive. (Only #1)

Fix n P Z 0 nd define the reltion on Z given by Is is n equivlence reltion? b if b pmod nq. Check: we hve b pmod nq if nd only if b kn for some k P Z. reflexivity: symmetry: trnsitivity: 0 0 n X If b kn, thenb kn p kqn. X If b kn nd b c `n, then c p bq`pb cq kn ` `n pk ` `qn.x Yes! This is n equivlence reltion! Let A be set. Consider the reltion on PpAq by Is is n equivlence reltion? S T if S Ñ T Check: This is reflexive nd trnsitive, but not symmetric. So no, it is not n equivlence reltion. Is S T if S Ñ T or S Ñ T n equivlence reltion on PpAq? Check: This is reflexive nd symmetric, but not trnsitive. So still no, it is not n equivlence reltion. Is S T if S T n equivlence reltion on PpAq? Red: Why reflexivity doesn t follow from symmetry nd trnsitivity.

Let be n equivlence reltion on set A, ndlet P A. The set of ll elements b P A such tht b is clled the equivlence clss of, denoted by rs. Exmple: Consider the equivlence reltion on A t, b, cu given by Then, b b, c c, c, nd c. rs t, cu rcs, nd rbs tbu re the two equivlence clsses in A (with respect to this reltion). (We sy there re two, not three, since the equivlence clsses refers to the sets themselves, not to the elements tht generte them.) Let be n equivlence reltion on set A, ndlet P A. The set of ll elements b P A such tht b is clled the equivlence clss of, denoted by rs. Exmple: We showed tht b if b pmod 5q is n equivlence reltion on Z. Then r0s t5n n P Zu 5Z r1s t5n ` 1 n P Zu 5Z ` 1 r2s t5n ` 2 n P Zu 5Z ` 2 r3s t5n ` 3 n P Zu 5Z ` 3 r4s t5n ` 4 n P Zu 5Z ` 4 r5s t5n ` 5 n P Zu t5m m P Zu r0s r 5s r10s r6s t5n ` 6 n P Zu t5m ` 1 m P Zu r1s r 4s r11s. In generl, if x Prys, thtmensy x. So x y. So y Prxs. Clim: x Prys if nd only if rxs rys. We cll ny element of clss C representtive of C (since we cn write C rs for ny P C).

Theorem. The equivlence clsses of A prtition A into subsets, mening 1. the equivlence clsses re subsets of A: rs Ñ A for ll P A; 2. ny two equivlence clsses re either equl or disjoint: for ll, b P A, eitherrs rbs or rsxrbs H; nd 3. the union of ll the equivlence clsses is ll of A: A PArs. We sy tht A is the disjoint union of equivlency clsses, written A ß PArs, L A TEX: \bigsqcup, \sqcup For exmple, in our lst exmple, there re exctly 5 equivlence clsses: r0s, r1s, r2s, r3s, nd r4s. Any other seemingly di erent clss is ctully one of these (for exmple, r5s r0s). And r0syr1syr2syr3syr4s Z. So Z r0s\r1s\r2s\r3s\r4s. Ok, so wht re numbers, nywy? Recll from the homework, the Zermelo-Frenkel xioms of set theory, which tells us how to compre sets, put sets in other sets, nd to tke unions, intersection, nd power sets of sets. X Set theoretic definition of the nturl numbers. (Z 0 ) Let 0 H. Given n, definethesuccessor to n s Spnq n Ytnu. (By successor to n we bsiclly men n ` 1.) Let N be the set of ll sets generted by 0 nd S. For exmple, 1 0 Yt0u HYtHu thu, 2 1 Yt1u thuytthuu th, thuu, 3 2 Yt2u th, thuu Y tth, thuuu th, thu, th, thuuu, nd so on. (Note tht we identified n with n.) Compute 4. Think: Given n, m P N, ren Y m nd/or n X m elements of N? If so, wht elements re they?

Set theoretic definition of the nturl numbers. (Z 0 ) Let 0 H. Given n, definethesuccessor to n s Spnq n Ytnu. LetN be the set of ll sets generted by 0 nd S. For exmple, 1 thu, 2 th, thuu, 3 th, thu, th, thuuu, 4 th, thu, th, thuu, th, thu, th, thuuuu, nd so on. (Note tht we identified n with n.) Addition: Define ` : N ˆ N Ñ N by, for ll, b P N, 1. ` 0 ; nd 2. ` Spbq Sp ` bq. For exmple, ` 1 ` Sp0q Sp ` 0q Spq; ` 2 ` Sp1q Sp ` 1q SpSpqq. Check tht ` 3 SpSpSpqqq S 3 pq. Think: ` b S b pq. Given n, definethesuccessor to n s Spnq n Ytnu. LetN be the set of ll sets generted by 0 nd S. For exmple, 1 thu, 2 th, thuu, 3 th, thu, th, thuuu, 4 th, thu, th, thuu, th, thu, th, thuuuu, nd so on. (Note tht we identified n with n.) Addition: Define ` : N ˆ N Ñ N by, for ll, b P N, 1. ` 0 ; nd 2. ` Spbq Sp ` bq. Think: ` b S b pq S `b p0q. Multipliction: Define : N ˆ N Ñ N by, for ll, b P N, 1. n 0 0; nd 2. Spbq p bq`. For exmple, 1 Sp0q 0 ` 0 ` ; Check tht ` 3 ` `. 2 Sp1q 1 ` `. Think: b S b p0q.

Addition: Define ` : N ˆ N Ñ N by, for ll, b P N, 1. ` 0 ; nd 2. ` Spbq Sp ` bq. Think: ` b S b pq S `b p0q. Multipliction: Define : N ˆ N Ñ N by, for ll, b P N, Properties: 1. n 0 0; nd 2. Spbq p bq`. Think: b S b p0q. 1. Addition is commuttive, i.e. ` b b ` for ll, b P N. 2. Addition is ssocitive, i.e. `pb ` cq p ` bq`c for ll, b, c P N. 3. Multipliction is commuttive, i.e. b b for ll, b P N. 4. Multipliction is ssocitive, i.e. pb cq p bq c for ll, b, c P N. 5. Multipliction is distributive cross ddition, i.e. pb ` cq p bq`p cq for ll, b, c P N. (These ll follow from the definitions, but we ll skip proofs for the ske of time.) Peno xioms The nturl numbers N re defined by the following xioms. 1. We hve 0 P N. (techniclly, 0 H) 2. There exists n successor function S : N Ñ N (nmely, if n P Z, thenspnq PN) stisfying (i) 0 R SpNq; (ii) S is injective (if Spnq Spmq, thenn m); nd (iii) if X Ñ N stisfies n 0 P X nd SpXq Ñ X, wehvex N. Note: () We hve not ssumed tht 0 is the only element tht is no one s successor (but it follows, in prt from 1(iii)). (b) By chnging 0 out for something else (like 1), or chnging Spnq to something else (like n 1), we cn generte other sets tht re bsiclly the nturl numbers ll over gin. This is why we re not fussy bout whether N is Z 0 or Z 0. (c) The lst xiom (1(iii)) is the bsis of proof by induction.

The nturl numbers N re defined by the following xioms. 1. We hve 0 P N. 2. There exists n successor function S : N Ñ N (nmely, if n P Z, thenspnq PN) stisfying (i) 0 R SpNq; (ii) S is injective (if Spnq Spmq, thenn m); nd (iii) if X Ñ N stisfies n 0 P X nd SpXq Ñ X, wehvex N. Order on N. For, b P N, wesy b if b SpSp Spq qq. Properties: (i) For ll, b P N, wehve b or b. (ii) If b nd b, then b. (iii) If b nd b c, then c. (iv) If b then ` c b ` c. (v) If b then c bc. (These ll follow from the xioms, but we ll skip proofs for the ske of time.) Integers Now tht we hve N, we cn define Z by formlly letting N t n n P Nu, where 0 0; nd Z N Y N. Extend S : Z Ñ Z by defining Sp q for ny P N t0u s Sp q b, where Spbq. We cn define the predecessor function P : Z Ñ Z by P pxq y whenever Spyq x. Letting p xq x, thissystht Spxq y if nd only if P pyq x. We cn lso extend our definitions of ` nd to Z. Properties: 1. Addition nd multipliction still stisfy commuttivity, ssocitivity, nd distributivity. 2. We still hve ` 0 (dditive identity) nd 1 (multiplictive identity) forll P Z. 3. We lso hve tht `p q 0 (prove). (dditive inverses) We cll ny number system tht hs n ddition nd multipliction tht stisfy ll these properties ring (modern lgebr).

Integers Now tht we hve N, wecndefinez by formlly letting N t n n P Nu, where 0 0; nd Z N Y N. ExtendS : Z Ñ Z by defining Sp q for ny P N t0u s Sp q b, where Spbq. We cn define the predecessor function P : Z Ñ Z by P pxq y whenever Spyq x. Letting p xq x, thissystht Spxq y if nd only if P pyq x. We cn lso extend our definition of order to Z. The only modifiction is: (i) For ll, b P N, wehve b or b. (ii) If b nd b, then b. (iii) If b nd b c, then c. (iv) If b then ` c b ` c. (v) If b nd c P N, then c bc. These properties mke Z n ordered ring. Rtionl numbers Let Q Z ˆpZ t0uq, nd define n equivlence reltion on Q by p, bq px, x bq for ll x P Z t0u. Under this equivlence reltion, write rp, bqs. b Then rtionl numbers re! ) Q ˇ, b P Z,b 0. b (Note tht we get lzy, nd write 1.) Define ` : Q ˆ Q Ñ Q nd : Q ˆ Q Ñ Q by b ` c d d ` b c nd b d b c d c b d.

Let Q Z ˆpZ t0uq nd define n equivlence reltion on Q by p, bq px, x bq for ll x P Z t0u. Under this equivlence reltion, write b rp, bqs (writing 1 ). Then rtionl numbers re! ) Q ˇ, b P Z,b 0. b Define ` : Q ˆ Q Ñ Q nd : Q ˆ Q Ñ Q by b ` c d d ` b c nd b d b c d c b d. Agin... 1. Addition nd multipliction still stisfy commuttivity, ssocitivity, nd distributivity. 2. We still hve x ` 0 x (dditive identity) ndx 1 x (multiplictive identity) forllx P Q. 3. We lso hve tht x `p xq 0. (dditive inverses) So Q is lso ring. In ddition, for ll {b P Q, b b 1 (multiplictive inverses). This mkes Q field (gin, modern lgebr). Order on Q Define b b (you cn show b á b ). We define on Q by the following: for, b, c, d P N, wehve 1. b c d 2. b c d ;nd whenever d b c; 3. b c d whenever c d b. Then, gin, (i) For ll, b P N, wehve b or b. (ii) If b nd b, then b. (iii) If b nd b c, then c. (iv) If b then ` c b ` c. (v) If b nd 0 c, thenc bc. This mkes Q into n ordered field.