# Pollard's rho algorithm

Pollard's rho algorithm is a special-purpose integer factorization algorithm. It was invented by John Pollard in 1975.[1] It is particularly effective for a composite number having a small prime factor.

## Core ideas

The ρ algorithm is based on Floyd's cycle-finding algorithm and on the observation that (as in the birthday problem) t random numbers x1, x2, ... , xt in the range [1, n] will contain a repetition with probability P > 0.5 if t > 1.177n1/2. The constant 1.177 comes from the more general result that if P is the probability that t random numbers in the range [1, n] contain a repetition, then P > 1 - exp{ - t2/2n }. Thus P > 0.5 provided 1/2 < exp{ - t2/2n }, or t2 > 2nln 2, or t2 > 2n ln 2, or t > (2ln 2)1/2n1/2 = 1.177n1/2.

The ρ algorithm uses g(x). a polynomial modulo n as a generator of a pseudo-random sequence. (The most commonly used function is g(x) = x2 mod n.) Let's assume n = pq. The algorithm generates the sequence x1 = g(2), x2 = g(g(2)), x3 = g(g(g(2))), and so on. Two different sequences will in effect be running at the same time--the sequence {xk} and the sequence {xk mod p}. Since p < n1/2, the latter sequence is likely to repeat earlier than the former sequence. The repetition of the mod p sequence will be detected by the fact that gcd(xk mod p - xm mod p, n) = p, where k < m. Once a repetition occurs, the sequence will cycle, because each term depends only on the previous one. The name ρ algorithm derives from the similarity in appearance between the Greek letter ρ and the directed graph formed by the values in the sequence and their successors. Once it is cycling, Floyd's cycle-finding algorithm will eventually detect a repetition. The algorithm succeeds whenever the sequence {xk mod p} repeats before the sequence {xk}. The randomizing function g(x) must be a polynomial modulo n, so that it will work both modulo p and modulo n. That is, so that g(x mod p) ≡ g(x) (mod p).

## Algorithm

The algorithm takes as its inputs n, the integer to be factored; and g(x), a polynomial p(x) computed modulo n. This will ensure that if p|n, and x ≡ y mod p, then g(x) ≡ g(y) mod p. In the original algorithm, g(x) = x2 - 1 mod n, but nowadays it is more common to use g(x) = x2 + 1 mod n. The output is either a non-trivial factor of n, or failure. It performs the following steps:[2]

1. x ← 2; y ← 2; d ← 1;
2. While d = 1:
1. x ← g(x)
2. y ← g(g(y))
3. d ← gcd(|x - y|, n)
3. If d = n, return failure.
4. Else, return d.

Note that this algorithm may fail to find a nontrivial factor even when n is composite. In that case, you can try again, using a starting value other than 2 or a different g(x). The name ρ algorithm comes from the fact that the values of x (mod d) eventually repeat with period d, resulting in a ρ shape when you graph the values.

## Variants

In 1980, Richard Brent published a faster variant of the rho algorithm. He used the same core ideas as Pollard but a different method of cycle detection, replacing Floyd's cycle-finding algorithm with the related Brent's cycle finding method.[3]

A further improvement was made by Pollard and Brent. They observed that if $\gcd (a,n) >1$, then also $\gcd (ab,n)>1$ for any positive integer b. In particular, instead of computing $\gcd (|x-y|,n)$ at every step, it suffices to define z as the product of 100 consecutive $|x-y|$ terms modulo n, and then compute a single $\gcd (z,n)$. A major speed up results as 100 gcd steps are replaced with 99 multiplications modulo n and a single gcd. Occasionally it may cause the algorithm to fail by introducing a repeated factor, for instance when n is a square. But it then suffices to go back to the previous gcd term, where $\gcd(z,n)=1$, and use the regular ρ algorithm from there.

## Application

The algorithm is very fast for numbers with small factors, but slower in cases where all factors are large. The ρ algorithm's most remarkable success was the factorization of the eighth Fermat number, F8 = 1238926361552897 * 93461639715357977769163558199606896584051237541638188580280321. The ρ algorithm was a good choice for F8 because the prime factor p = 12389263661552897 is much smaller than the other factor. The factorization took 2 hours on a UNIVAC 1100/42.

## Example factorization

Let n = 8051 and g(x) = (x2 + 1) mod 8051.

i xi yi GCD(|xiyi|, 8051)
1 5 26 1
2 26 7474 1
3 677 871 97

97 is a non-trivial factor of 8051. Starting values other than x = y = 2 may give the cofactor (83) instead of 97.

## The Example n = 10403 = 101 . 103

Here we introduce another variant, where only a single sequence is computed, and the gcd is computed inside the loop that detects the cycle.

### C++ Pseudo code

The following pseudo code finds the factor 101 of 10403 with a starting value of x = 2.

int gcd( int a, int b) {
int remainder;
while (b != 0) {
remainder = a % b;
a = b;
b = remainder;
}
return a;
}

int main () {

int number = 10403,x_fixed = 2,cycle_size = 2,x = 2,factor = 1;

while (factor == 1) {

for (int count=1;count <= cycle_size && factor == 1;count++) {
x = (x*x+1)%number;
factor = gcd(x - x_fixed, number);
}

cycle_size *= 2;
x_fixed = x;
}
cout << "\nThe factor is  " << factor;
}


### The Results

In the following table the second and fourth columns contain secret information not known to the person trying to factor pq = 10403. They are included to show how the algorithm works. If we start with x = 2 and follow the algorithm, we get the following numbers:

x xfixed x mod 101 xfixed mod 101 step
2 2 2 2 0
5 2 5 2 1
26 2 26 2 2
677 26 71 26 3
598 26 93 26 4
3903 26 65 26 5
3418 26 85 26 6
156 3418 55 85 7
3531 3418 97<-- 85 8
5168 3418 17 85 9
3724 3418 88 85 10
978 3418 69 85 11
9812 3418 15 85 12
5983 3418 24 85 13
9970 3418 72 85 14
236 9970 34 72 15
3682 9970 46 72 16
2016 9970 97<-- 72 17
10289 9970 88 72 18
2594 9970 69 72 19
8499 9970 15 72 20
4973 9970 24 72 21
2799 9970 72<-- 72 22

The first repetition modulo 101 is 97 which occurs in step 17. The repetition is not detected until step 22, when x = xfixed (mod 101). This causes gcd(x - x_fixed, n) = gcd(2799 - 9970, n) to be p = 101, and a factor is found.

## Complexity

If the pseudo random number x = g(x) occurring in the Pollard ρ algorithm were an actual random number, it would follow that success would be achieved half the time, by the Birthday paradox in $O(\sqrt p)\le O(n^{1/4})$ iterations. It is believed that the same analysis applies as well to the actual rho algorithm, but this is a heuristic claim, and rigorous analysis of the algorithm remains open.[4]

## References

1. ^ Pollard, J. M. (1975), "A Monte Carlo method for factorization", BIT Numerical Mathematics 15 (3): 331–334, doi:10.1007/bf01933667
2. ^ Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L. & Stein, Clifford (2001), "Section 31.9: Integer factorization", Introduction to Algorithms (Second ed.), Cambridge, MA: MIT Press, pp. 896–901, ISBN 0-262-03293-7 (this section discusses only Pollard's rho algorithm).
3. ^ Brent, Richard P. (1980), "An Improved Monte Carlo Factorization Algorithm", BIT 20: 176–184, doi:10.1007/BF01933190
4. ^ Galbraith, Steven D. (2012), "14.2.5 Towards a rigorous analysis of Pollard rho", Mathematics of Public Key Cryptography, Cambridge University Press, pp. 272–273, ISBN 9781107013926.