Dixon's factorization method

In number theory, Dixon's factorization method (also Dixon's random squares method^[1] or Dixon's algorithm) is a general-purpose integer factorization algorithm; it is the prototypical factor base method. Unlike for other factor base methods, its run-time bound comes with a rigorous proof that does not rely on conjectures about the smoothness properties of the values taken by a polynomial.

The algorithm was designed by John D. Dixon, a mathematician at Carleton University, and was published in 1981.^[2]

Basic idea

Dixon's method is based on finding a congruence of squares modulo the integer N which is intended to factor. Fermat's factorization method finds such a congruence by selecting random or pseudo-random x values and hoping that the integer x² mod N is a perfect square (in the integers):

${\displaystyle x^{2}\equiv y^{2}\quad ({\hbox{mod }}N),\qquad x\not \equiv \pm y\quad ({\hbox{mod }}N).}$

For example, if N = 84923, (by starting at 292, the first number greater than √N and counting up) the 505² mod 84923 is 256, the square of 16. So (505 − 16)(505 + 16) = 0 mod 84923. Computing the greatest common divisor of 505 − 16 and N using Euclid's algorithm gives 163, which is a factor of N.

In practice, selecting random x values will take an impractically long time to find a congruence of squares, since there are only √N squares less than N.

Dixon's method replaces the condition "is the square of an integer" with the much weaker one "has only small prime factors"; for example, there are 292 squares smaller than 84923; 662 numbers smaller than 84923 whose prime factors are only 2,3,5 or 7; and 4767 whose prime factors are all less than 30. (Such numbers are called B-smooth with respect to some bound B.)

If there are many numbers ${\displaystyle a_{1}\ldots a_{n}}$ whose squares can be factorized as ${\displaystyle a_{i}^{2}\mod N=\prod _{j=1}^{m}b_{j}^{e_{ij}}}$ for a fixed set ${\displaystyle b_{1}\ldots b_{m}}$ of small primes, linear algebra modulo 2 on the matrix ${\displaystyle e_{ij}}$ will give a subset of the ${\displaystyle a_{i}}$ whose squares combine to a product of small primes to an even power — that is, a subset of the ${\displaystyle a_{i}}$ whose squares multiply to the square of a (hopefully different) number mod N.

Method

Suppose the composite number N is being factored. Bound B is chosen, and the factor base is identified (which is called P), the set of all primes less than or equal to B. Next, positive integers z are sought such that z² mod N is B-smooth. Therefore we can write, for suitable exponents a_i,

${\displaystyle z^{2}{\text{ mod }}N=\prod _{p_{i}\in P}p_{i}^{a_{i}}}$

When enough of these relations have been generated (it is generally sufficient that the number of relations be a few more than the size of P), the methods of linear algebra, such as Gaussian elimination, can be used to multiply together these various relations in such a way that the exponents of the primes on the right-hand side are all even:

${\displaystyle {z_{1}^{2}z_{2}^{2}\cdots z_{k}^{2}\equiv \prod _{p_{i}\in P}p_{i}^{a_{i,1}+a_{i,2}+\cdots +a_{i,k}}\ {\pmod {N}}\quad ({\text{where }}a_{i,1}+a_{i,2}+\cdots +a_{i,k}\equiv 0{\pmod {2}})}}$

This yields a congruence of squares of the form a² ≡ b² (mod N), which can be turned into a factorization of N, N = gcd(a + b, N) × (N/gcd(a + b, N)). This factorization might turn out to be trivial (i.e. N = N × 1), which can only happen if a ≡ ±b (mod N), in which case another try must be made with a different combination of relations; but if a nontrivial pair of factors of N is reached, the algorithm terminates.

Pseudocode

This section is taken directly from Dixon(1981).

Dixon's Algorithm

Initialization. Let L be a list of integers in the range [1, n], and let P = {p₁, ..., pₕ} be the list of the h primes ≤ v. Let B and Z be initially empty lists (Z will be indexed by B).

Step 1. If L is empty, exit (algorithm unsuccessful). Otherwise, take the first term z from L, remove it from L, and proceed to Step 2.

Step 2. Compute w as the least positive remainder of z² mod n. Factor w as:

${\displaystyle w=w'\prod _{i}p_{i}^{a_{i}}}$

where w′ has no factor in P. If w′ = 1, proceed to Step 3; otherwise, return to Step 1.

Step 3. Let a ← (a₁, ..., aₕ). Add a to B and z to Z. If B has at most h elements, return to Step 1; otherwise, proceed to Step 4.

Step 4. Find the first vector c in B that is linearly dependent (mod 2) on earlier vectors in B. Remove c from B and ${\displaystyle z_{c}}$ from Z. Compute coefficients ${\displaystyle f_{b}}$ such that:

${\displaystyle \mathbf {c} \equiv \sum _{b\in B}f_{b}\mathbf {b} {\pmod {2}}}$

Define:

${\displaystyle \mathbf {d} =(d_{1},\dots ,d_{n})\gets {\frac {1}{2}}\left(\mathbf {c} +\sum f_{b}\mathbf {b} \right)}$

Proceed to Step 5.

Step 5. Compute:

${\displaystyle x\gets z_{c}\prod _{b}z_{b}^{f_{b}},\quad y\gets \prod _{i}p_{i}^{d_{i}}}$

so that:

${\displaystyle x^{2}\equiv \prod _{i}p_{i}^{2d_{i}}=y^{2}\mod n.}$

If ${\displaystyle x\equiv y}$ or ${\displaystyle x\equiv -y{\pmod {n}}}$, return to Step 1. Otherwise, return:

${\displaystyle \gcd(n,x+y)}$

which provides a nontrivial factor of n, and terminate successfully.

Step-by-step example : factorizing ( n = 84923) using Dixon’s Algorithm

This example is lifted directly from the LeetArxiv substack.^[3] Credit is given to the original author.

• Initialization:
  • Define a list of numbers L, ranging from 1 to 84923:

${\displaystyle L=\{1,\dots ,84923\}}$

• Define a value v, which is the smoothness factor:

${\displaystyle v=7}$

• Define a list P containing all the prime numbers less than or equal to v:

${\displaystyle P={2,3,5,7}}$

• Define B and Z, two empty lists. B is a list of powers, while Z is a list of accepted integers:

${\displaystyle B=[]}$

${\displaystyle Z=[]}$

• Step 1: Iterating ${\displaystyle z}$ values
  • Write a for loop that indexes the list ${\displaystyle L}$. Each element in ${\displaystyle L}$ is indexed as ${\displaystyle z}$. The for loop exits at the end of the list.

int n = 84923;
for(int i = 1; i <= n; i++)
{
    int z = i;
}

• Step 2: Computing ${\displaystyle z^{2}\mod n}$ and v-smooth Prime Factorization
  • To proceed, compute ${\displaystyle z^{2}\mod 84923}$ for each z, then express the result as a prime factorization.

${\displaystyle 1^{2}\mod 84923\equiv 1\mod 84923=2^{0}\cdot 3^{0}\cdot 5^{0}\cdot 7^{0}\mod 84923}$

${\displaystyle \vdots }$

${\displaystyle 513^{2}\mod 84923=8400\mod 84923=2^{4}\cdot 3^{1}\cdot 5^{2}\cdot 7^{1}\mod 84923}$

${\displaystyle \vdots }$

${\displaystyle 537^{2}\mod 84923=33600\mod 84923=2^{6}\cdot 3^{1}\cdot 5^{2}\cdot 7^{1}\mod 84923}$

${\displaystyle 538^{2}\mod 84923=34675\mod 84923=5^{2}\cdot 19^{1}\cdot 73^{1}\mod 84923}$

This step continues for all values of z in the range.

• Step 3: If ${\displaystyle z^{2}\mod 84923}$ is 7-smooth, then append its powers to list ${\displaystyle B}$ and append ${\displaystyle z}$ to list ${\displaystyle Z}$.

${\displaystyle Z=\{1,513,537\}}$

${\displaystyle B=\{[0,0,0,0],[4,1,2,1],[6,1,2,1]\}}$

• Step 4: This step is split into two parts.

Part 1: Find ${\displaystyle B}$ modulo 2.

${\displaystyle B={\begin{pmatrix}0&0&0&0\\4&1&2&1\\6&1&2&1\end{pmatrix}}\mod 2\equiv B={\begin{pmatrix}0&0&0&0\\0&1&0&1\\0&1&0&1\end{pmatrix}}}$

Part 2: Check if any row combinations of ${\displaystyle B}$ sum to even numbers

For example, summing Row ${\displaystyle 2}$ and Row ${\displaystyle 3}$ gives us a vector of even numbers.

${\displaystyle R_{2}=\{0,1,0,1\}}$ and ${\displaystyle R_{3}=\{0,1,0,1\}}$

then

${\displaystyle R_{2}+R_{3}=\{0,1,0,1\}+\{0,1,0,1\}}$

${\displaystyle R_{2}+R_{3}=\{0,2,0,2\}}$.

• Step 5 : This step is split into four parts.
  • Part 1. (Finding x): Multiply the corresponding ${\displaystyle z}$ values for the rows found in Step 4. Then find the square root. This gives us ${\displaystyle x}$.
    • For Row 2, we had ${\displaystyle 2^{4}*3^{1}*5^{2}*7^{1}}$.
    • For Row 3, we had ${\displaystyle 2^{6}*3^{1}*5^{2}*7^{1}}$.
    • Thus, we find ${\displaystyle x}$ :

${\displaystyle {\begin{array}{ll}(513\cdot 537)^{2}\mod 84923=y^{2}\\\\{\text{where}}\quad x^{2}\mod 84923=(513\cdot 537)^{2}\mod 84923\\\\{\text{thus}}\quad x=(513\cdot 537)\mod 84923\\\\{\text{so}}\quad x=275481\mod 84923\\\\{\text{Finally}}\quad x=20712\mod 84923\\\end{array}}}$

• Part 2. (Finding y): Multiply the corresponding smooth factorizations for the rows found in Step 4. Then find the square root. This gives us ${\displaystyle y}$.

${\displaystyle {\begin{array}{ll}y^{2}=(2^{4}\cdot 3^{1}\cdot 5^{2}\cdot 7^{1})\times (2^{6}\cdot 3^{1}\cdot 5^{2}\cdot 7^{1})\\\\{\text{By the multiplication law of exponents,}}\\y^{2}=2^{(4+6)}\cdot 3^{(1+1)}\cdot 5^{(2+2)}\cdot 7^{(1+1)}\\\\{\text{Thus,}}\\y^{2}=2^{10}\cdot 3^{2}\cdot 5^{4}\cdot 7^{2}\\\\{\text{Taking square roots on both sides gives}}\\y=2^{5}\cdot 3^{1}\cdot 5^{2}\cdot 7^{1}\\\\{\text{Therefore,}}\\y=32\times 3\times 25\times 7\\\\{\text{Finally,}}\\y=16800\end{array}}}$

• Part 3. (Find x + y and x - y) where x = 20712 and y = 16800.

${\displaystyle x+y=20712+16800=37512}$

${\displaystyle x-y=20712-16800=3912}$

• Part 4. Compute GCD(x+y, n) and GCD(x-y, n), where n = 84923, x+y = 292281 and x-y = 258681

${\displaystyle {\begin{array}{ll}\gcd(37512,84923)=521\\\gcd(3912,84923)=163\end{array}}}$

Quick check shows ${\displaystyle 84923=521\times 163}$.

Optimizations

The quadratic sieve is an optimization of Dixon's method. It selects values of x close to the square root of N such that x² modulo N is small, thereby largely increasing the chance of obtaining a smooth number.

Other ways to optimize Dixon's method include using a better algorithm to solve the matrix equation, taking advantage of the sparsity of the matrix: a number z cannot have more than ${\displaystyle \log _{2}z}$ factors, so each row of the matrix is almost all zeros. In practice, the block Lanczos algorithm is often used. Also, the size of the factor base must be chosen carefully: if it is too small, it will be difficult to find numbers that factorize completely over it, and if it is too large, more relations will have to be collected.

A more sophisticated analysis, using the approximation that a number has all its prime factors less than ${\displaystyle N^{1/a}}$ with probability about ${\displaystyle a^{-a}}$ (an approximation to the Dickman–de Bruijn function), indicates that choosing too small a factor base is much worse than too large, and that the ideal factor base size is some power of ${\displaystyle \exp \left({\sqrt {\log N\log \log N}}\right)}$.

The optimal complexity of Dixon's method is

${\displaystyle O\left(\exp \left(2{\sqrt {2}}{\sqrt {\log n\log \log n}}\right)\right)}$

in big-O notation, or

${\displaystyle L_{n}[1/2,2{\sqrt {2}}]}$

in L-notation.

References

1. Kleinjung, Thorsten; et al. (2010). "Factorization of a 768-Bit RSA Modulus". Advances in Cryptology – CRYPTO 2010. Lecture Notes in Computer Science. Vol. 6223. pp. 333–350. doi:10.1007/978-3-642-14623-7_18. ISBN 978-3-642-14622-0. S2CID 11556080.
2. Dixon, J. D. (1981). "Asymptotically fast factorization of integers" (PDF). Math. Comp. 36 (153): 255–260. doi:10.1090/S0025-5718-1981-0595059-1. JSTOR 2007743.
3. Kibicho, Murage (2025). Hand-Written Paper Implementation: Asymptotically Fast Factorization of Integers.