# 2. THE EUCLIDEAN ALGORITHM More ring essentials

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1 2. THE EUCLIDEAN ALGORITHM More ring essentials In this chapter: rings R commutative with 1. An element b R divides a R, or b is a divisor of a, or a is divisible by b, or a is a multiple of b, if there exists c R such that a = b c. Elements a and b in R are associates if there exists a unit u R such that a = u b (so a is a multiple of b and b is a multiple of a). The element b is a proper divisor of a R if b is neither a unit nor an associate of a. An element is irreducible in R if it has no proper divisors in R; other wise it is reducible. Note that units are irreducible. The zero element is irreducible if and only if R is a domain. 29

2 Primes A prime element is a non-unit π R with the property that if π divides a b then π divides a or b. Lemma If R is a domain then: π R prime implies π is irreducible in R. For, if π = α β, with α, β non-units, then π divides α β, but if π divides α then α β γ = α for some γ, so β γ 1 = 0, contrary to β being non-unit. Converse is false in general (z in C[x, y, z]/(z 2 xy), or 2 in Z[ 5]). 30

3 Unique factorization domains A unique factorization domain (UFD) is a domain in which every non-zero non-unit can be written as a product of irreducible non-units in a way that is unique up to order and associates. Lemma If R is a UFD then every irreducible element α in R is prime. For, if α divides a b but neither a nor b (nonunits), then a b would have two factorizations into irreducibles, one containing (an associate of) α, the other not. Examples of unique factorization domains: (i) Z (ii) any field F (iii) any principal ideal domain (iv) D[x] for any UFD D, hence D[x 1, x 2,..., x n ] 31

4 Common divisors A greatest common divisor g = gcd(s) of a finite set S of elements in a domain R is an element g that divides every element of S and has the property that if c also divides every element of S then c divides g. Two elements a, b are called relatively prime (or coprime) if gcd(a, b) = 1. In a UFD every finite set S has a greatest common divisor. Not true in general (6 and in Z[ 5] have no gcd), and not necessarily unique. 32

5 Euclidean domains A domain R is called Euclidean if there exists a Euclidean function φ : R \ {0} N such that for all a, b R with b 0 (i) φ(a) φ(a b) and (ii) there exist q, r R (quotient and remainder) such that a = q b+r, with either r = 0 or φ(r) < φ(b). Proposition Every Euclidean domain is a principal ideal domain Given an ideal I, choose an element x in it minimizing φ(x). Then x I. But if a I then a = q x + r with r = 0 by minimality of φ(x), since r = a q x I. Hence a x. Converse not true (Z[ ]). 33

6 Examples (i) Z, with φ(n) = n ; (ii) F[x] for any field F, with φ(f) = deg f. (iii) Z[ 1], with φ(u + v 1) = u 2 + v 2. 34

7 Euclidean algorithm An efficient procedure for finding greatest common divisors is Euclid s famous algorithm. Input: a, b 0 Output: d = gcd(a, b) while b 0: r := a q b; a := b; b := r; return a; Correctness: if a = q b + r, then gcd(a, b) = gcd(b, r). Termination: 0 φ(r) = φ(a q b) < φ(b), so φ(b) decreases. 35

8 Extended Euclidean algorithm With a little more bookkeeping it is possible to obtain multipliers. Input: a, b 0 Output: d = gcd(a, b), and multipliers s, t such that d = s a + t b s 1 := 1; t 1 := 0; s 2 := 0; t 2 := 1; while b 0: s 0 := s 1 ; t 0 := t 1 ; s 1 := s 2 ; t 1 := t 2 ; r := a q b; a := b; b := r; s 2 := s 0 q s 1 ; t 2 := t 0 q t 1 ; return a, s 1, t 1 ; Termination and correctness as before. At the beginning of the while loop: s 1 a+t 1 b = a. 36

9 Application: modular inverses Proposition Let R be a Euclidean domain, S = R/mR. Then ā S is a unit if and only if gcd(a, m) = 1, and extended Euclidean algorithm produces ā 1. ā is unit there exists s R with a s 1 mod m there exist s, t R with a s + m t = 1 gcd(a, m) = 1 and s = ā 1. Hence inverses in (i) Z/mZ (ii) finite fields F p = Z/pZ (iii) finite fields F p k = F p [x]/ff p [x] (iv) number fields Q[x]/gQ[x]. 37

10 Continued fractions The Euclidean algorithm is closely related to the continued fraction expansion of rational numbers. If we let a and b be positive integers with a > b, the Euclidean algorithm determines positive integers q i, r i with a = q 0 b + r 0, b = q 1 r 0 + r 1, r 0 = q 2 r 1 + r 2,. r k 2 = q k r k 1, so r k = 0. But then a b = q 0 + r 0 b = q b r 0 = q q 1 + r = 1 r 0 = q 0 + q q q k 1. 38

11 An expansion of the kind on the right is called a (finite) regular continued fraction, and is usually denoted by [q 0 ; q 1,... q k ]. The positive integers q i are called partial quotients; note that q k > 1. Conversely, it is clear that every such continued fraction determines a rational number. The main importance of finite continued fractions lies in the possibility to generalize to expansions of arbitrary real numbers, by allowing infinite expansions [q 0 ; q 1,...]. Such an infinite expansion can be obtained from a positive real x by setting x 0 = x and q i = x i, where x i+1 = 1/(x i q i ), for i 1. It can be shown that the rational numbers c k = [q 0 ; q 1,..., q k ] form a sequence of increasingly good rational approximations to x, converging to x; the c k are called the convergents to x. Right now we will only use infinite continued fraction in a worst case analysis of Euclid s algorithm, for which purpose it suffices to look at one special case. 39

12 Lemma Let φ be the positive real root of f = x 2 x 1, so φ = Then φ = [1;1,1,...] and the convergents to φ are the rational numbers c k = F k+1 /F k, where F k is the k-th Fibonacci number, given by F 0 = F 1 = 1, and F j = F j 1 + F j 2 for j 2. Moreover F k = 1 5 (φ k+1 φ k+1 ), where φ = is the conjugate of φ. Proof Since φ is a root of x 2 x 1, we have φ (φ 1) = 1, hence (φ 1) 1 = φ. But since f(1) = 1 < 0 < 1 = f(2) we see that 1 < φ < 2, so for the continued fraction development we find x 0 = φ, q 0 = 1 and x 1 = 1/(x 0 1) = x 0. That proves the first part. For the second assertion one proceeds by induction: clearly c 0 = 1, c 1 = 2 and c i+1 = 1+ 1 c i = 1+ F k 1 F k = F k + F k 1 F k = F k+1 F k. The final statement follows easily by induction, using that φ and φ satisfy x n = x n 1 + x n 2. 40

13 Theorem The Euclidean algorithm on input a, b less than N takes at most log φ ( 5N) 2 division steps. Proof The maximum number of division steps occurs when a = F n and b = F n+1 with n maximal such that F n+1 < N. The result follows from the expression for F k in the Lemma, using that φ < 1. 41

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