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In mathematics, the greatest common divisor (gcd), also known as the greatest common denominator, greatest common factor (gcf), or highest common factor (hcf), of two or more non-zero integers, is the largest positive integer that divides the numbers without a remainder. For example, the GCD of 8 and 12 is 4.

This notion can be extended to polynomials.

Overview

The greatest common divisor is useful for reducing fractions to be in lowest terms. For example, gcd(42, 56) = 14, therefore,

The greatest common divisor of a and b is written as gcd(a, b), or sometimes simply as (a, b). For example, gcd(12, 18) = 6, gcd(−4, 14) = 2. Two numbers are called coprime or relatively prime if their greatest common divisor equals 1. For example, 9 and 28 are relatively prime.

Calculating the gcd

Using prime factorizations

Greatest common divisors can in principle be computed by determining the prime factorizations of the two numbers and comparing factors, as in the following example: to compute gcd(18, 84), we find the prime factorizations 18 = 2 · 32 and 84 = 22 · 3 · 7 and notice that the "overlap" of the two expressions is 2 · 3; so gcd(18, 84) = 6. In practice, this method is only feasible for small numbers; computing prime factorizations in general takes far too long.

Here is another concrete example, illustrated by a Venn diagram. Suppose it is desired to find the greatest common divisor of 48 and 180. First, find the prime factorizations of the two numbers:

48 = 2 × 2 × 2 × 2 × 3,
180 = 2 × 2 × 3 × 3 × 5.

What they share in common is two "2"s and a "3":

[1]
Least common multiple = 2 × 2 × ( 2 × 2 × 3 ) × 3 × 5 = 720
Greatest common divisor = 2 × 2 × 3 = 12.


Using Euclid's algorithm

A much more efficient method is the Euclidean algorithm, which uses the division algorithm in combination with the observation that the gcd of two numbers also divides their difference: divide 48 by 18 to get a quotient of 2 and a remainder of 12. Then divide 18 by 12 to get a quotient of 1 and a remainder of 6. Then divide 12 by 6 to get a remainder of 0, which means that 6 is the gcd. Formally, it can be described as:

Which also could be written as

The series of quotients generated by the Euclidean algorithm composes a continued fraction.

Other methods

If a and b are not both zero, the greatest common divisor of a and b can be computed by using least common multiple (lcm) of a and b:

Keith Slavin has shown that for odd a ≥ 1:

which is a function that can be evaluated for complex b [2] and Wolfgang Schramm has shown that

is an entire function in the variable b for all positive integers a where cd(k) is Ramanujan's sum.[3] Marcelo Polezzi has shown that:

for positive integers a and b.[4] Donald Knuth proved the following reduction:

for non-negative integers a and b, where a and b are not both zero.[5]

Complexity

The existence of the Euclidean algorithm places the (decision problem version of) the greatest common divisor problem in P, the class of problems solvable in polynomial time. The GCD problem is not known to be in NC, and so there is no known way to parallelize its computation across many processors; nor is it known to be P-complete, which would imply that it is unlikely to be possible to parallelize GCD computation. In this sense the GCD problem is analogous to e.g. the integer factorization problem, which has no known polynomial-time algorithm, but is not known to be NP-complete. Shallcross et al. showed that a related problem (EUGCD, determining the remainder sequence arising during the Euclidean algorithm) is NC-equivalent to the problem of integer linear programming with two variables; if either problem is in NC or is P-complete, the other is as well.[6] Since NC contains NL, it is also unknown whether a space-efficient algorithm for computing the GCD exists, even for nondeterministic Turing machines.

Although the problem is not known to be in NC, parallel algorithms with time superior to the Euclidean algorithm exist; the best known deterministic algorithm is by Chor and Goldreich, which (in the CRCW-PRAM model) can solve the problem in O(n/log n) time with n1+ε processors.[7] Randomized algorithms can solve the problem in O((log n)2) time on processors (note this is superpolynomial).[8]

Properties

  • Every common divisor of a and b is a divisor of gcd(a, b).
  • gcd(a, b), where a and b are not both zero, may be defined alternatively and equivalently as the smallest positive integer d which can be written in the form d = a·p + b·q where p and q are integers. This expression is called Bézout's identity. Numbers p and q like this can be computed with the extended Euclidean algorithm.
  • gcd(a, 0) = |a|, for a ≠ 0, since any number is a divisor of 0, and the greatest divisor of a is |a|. This is usually used as the base case in the Euclidean algorithm.
  • If a divides the product b·c, and gcd(a, b) = d, then a/d divides c.
  • If m is a non-negative integer, then gcd(m·a, m·b) = m·gcd(a, b).
  • If m is any integer, then gcd(a + m·b, b) = gcd(a, b).
  • If m is a nonzero common divisor of a and b, then gcd(a/m, b/m) = gcd(a, b)/m.
  • The gcd is a multiplicative function in the following sense: if a1 and a2 are relatively prime, then gcd(a1·a2, b) = gcd(a1, b)·gcd(a2, b).
  • The gcd is a commutative function: gcd(a, b) = gcd(b, a).
  • The gcd is an associative function: gcd(a, gcd(b, c)) = gcd(gcd(a, b), c).
  • The gcd of three numbers can be computed as gcd(a, b, c) = gcd(gcd(a, b), c), or in some different way by applying commutativity and associativity. This can be extended to any number of numbers.
  • gcd(a, b) is closely related to the least common multiple lcm(a, b): we have
gcd(a, b)·lcm(a, b) = a·b.
This formula is often used to compute least common multiples: one first computes the gcd with Euclid's algorithm and then divides the product of the given numbers by their gcd. The following versions of distributivity hold true:
gcd(a, lcm(b, c)) = lcm(gcd(a, b), gcd(a, c))
lcm(a, gcd(b, c)) = gcd(lcm(a, b), lcm(a, c)).
  • It is useful to define gcd(0, 0) = 0 and lcm(0, 0) = 0 because then the natural numbers become a complete distributive lattice with gcd as meet and lcm as join operation. This extension of the definition is also compatible with the generalization for commutative rings given below.
  • In a Cartesian coordinate system, gcd(a, b) can be interpreted as the number of points with integral coordinates on the straight line joining the points (0, 0) and (a, b), excluding (0, 0).

Probabilities and expected value

In 1972, J. E. Nymann showed that the probability that k independently chosen integers are coprime is 1/ζ(k).[9] (See coprime for a derivation.) This result was extended in 1987 to show that the probability that k random integers has greatest common divisor d is d-k/ζ(k).[10]

Using this information, the expected value of the greatest common divisor function can be seen (informally) to not exist when k = 2. In this case the probability that the gcd equals d is d−2/ζ(2), and since ζ(2) = π2/6 we have

This last summation is the harmonic series, which diverges. However, when k ≥ 3, the expected value is well-defined, and by the above argument, it is

For k = 3, this is approximately equal to 1.3684. For k = 4, it is approximately 1.1106.

The gcd in commutative rings

The greatest common divisor can more generally be defined for elements of an arbitrary commutative ring.

If R is a commutative ring, and a and b are in R, then an element d of R is called a common divisor of a and b if it divides both a and b (that is, if there are elements x and y in R such that d·x = a and d·y = b). If d is a common divisor of a and b, and every common divisor of a and b divides d, then d is called a greatest common divisor of a and b.

Note that with this definition, two elements a and b may very well have several greatest common divisors, or none at all. But if R is an integral domain then any two gcd's of a and b must be associate elements. Also, if R is a unique factorization domain, then any two elements have a gcd. If R is a Euclidean domain then a form of the Euclidean algorithm can be used to compute greatest common divisors.

The following is an example of an integral domain with two elements that do not have a gcd:

The elements 2 and 1 + √(−3) are two "maximal common divisors" (i.e. any common divisor which is a multiple of 2 is associated to 2, the same holds for 1 + √(−3)), but they are not associated, so there is no greatest common divisor of a and b.

Corresponding to the Bezout property we may, in any commutative ring, consider the collection of elements of the form pa + qb, where p and q range over the ring. This is the ideal generated by a and b, and is denoted simply (a, b). In a ring all of whose ideals are principal (a principal ideal domain or PID), this ideal will be identical with the set of multiples of some ring element d; then this d is a greatest common divisor of a and b. But the ideal (a, b) can be useful even when there is no greatest common divisor of a and b. (Indeed, Ernst Kummer used this ideal as a replacement for a gcd in his treatment of Fermat's Last Theorem, although he envisioned it as the set of multiples of some hypothetical, or ideal, ring element d, whence the ring-theoretic term.)

Notes

  1. ↑ Gustavo Delfino, "Understanding the Least Common Multiple and Greatest Common Divisor", Wolfram Demonstrations Project, Published: February 1, 2013.
  2. ↑ Slavin, Keith R. (2008). "Q-Binomials and the Greatest Common Divisor". Integers Electronic Journal of Combinatorial Number Theory (University of West Georgia, Charles University in Prague) 8: A5. http://www.integers-ejcnt.org/vol8.html. Retrieved 2008-05-26.
  3. ↑ Schramm, Wolfgang (2008). "The Fourier transform of functions of the greatest common divisor". Integers Electronic Journal of Combinatorial Number Theory (University of West Georgia, Charles University in Prague) 8: A50. http://www.integers-ejcnt.org/vol8.html. Retrieved 2008-11-25.
  4. ↑ Polezzi, Marcelo (1997). "A Geometrical Method for Finding an Explicit Formula for the Greatest Common Divisor". Amer. Math. Monthly (Mathematical Association of America) 104 (5): 445–446. doi:10.2307/2974739. http://www.jstor.org/pss/2974739.
  5. ↑ Knuth, Donald E.; R. L. Graham, O. Patashnik (March 1994). Concrete Mathematics: A Foundation for Computer Science. Addison-Wesley. ISBN 0-201-55802-5.
  6. ↑ D. Shallcross, V. Pan, and Y. Lin-Kriz. The NC equivalence of planar integer linear programming and Euclidean GCD. 34th IEEE Symp. Foundations of Computer Science, 1993, pp. 557-564. (PDF of technical report)
  7. ↑ B. Chor and O. Goldreich. An improved parallel algorithm for integer GCD. Algorithmica, 5:1–10, 1990.
  8. ↑ L. M. Adleman and K. Kompella. Using smoothness to achieve parallelism. In 20th Annual ACM Symposium on Theory of Computing, pages 528–538, 1988.
  9. ↑ J. E. Nymann, On the probability that k positive integers are relatively prime. Journal of Number Theory, 4:469–473, 1972.
  10. ↑ J. Chidambaraswamy and R. Sitarmachandrarao. On the probability that the values of m polynomials have a given g.c.d. Journal of Number Theory, 26:237–245, 1987.

Further reading

  • Donald Knuth. The Art of Computer Programming, Volume 2: Seminumerical Algorithms, Third Edition. Addison-Wesley, 1997. ISBN 0-201-89684-2. Section 4.5.2: The Greatest Common Divisor, pp. 333–356.
  • Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms, Second Edition. MIT Press and McGraw-Hill, 2001. ISBN 0-262-03293-7. Section 31.2: Greatest common divisor, pp. 856–862.
  • Saunders MacLane and Garrett Birkhoff. A Survey of Modern Algebra, Fourth Edition. MacMillan Publishing Co., 1977. ISBN 0-02-310070-2. 1–7: "The Euclidean Algorithm."
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