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ArticlePublished 7 Aug 20262 min readBy Kevin JoginBerlekampfinite fieldkernelFrobenius
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Polynomial Factorisation

The Berlekamp Factorisation Algorithm

Berlekamp's linear algebra approach to factoring over a finite field, the Berlekamp subalgebra, and when it outperforms the GCD pipeline.

Engineering / MathematicsPolynomial Factorisation2 min readKV-MATH-0566

Berlekamp's algorithm factors a polynomial over a finite field by linear algebra rather than by GCD computations. It computes the number of irreducible factors before finding any of them, which the GCD pipeline cannot do.

The Berlekamp subalgebra

Consider the quotient ring by the input polynomial. Elements fixed by Frobenius form a subalgebra, and its dimension equals the number of distinct irreducible factors.

B = { a in F_q[X]/(f) : a^q = a } = kernel of (Frobenius - I)The dimension of B equals the number of irreducible factors.

Key point

This is the algorithm's distinguishing feature: the factor count falls out of a rank computation, before any factor is produced. It also gives an immediate irreducibility test — dimension one means irreducible.

The algorithm

Berlekamp's algorithm

  1. Ensure squarefreeRun squarefree factorisation first.
  2. Build the Frobenius matrixCompute X to the q times i modulo f for each basis index, giving the matrix of the Frobenius map.
  3. Subtract the identityForm the matrix of Frobenius minus the identity.
  4. Compute the kernelBy elimination over the field. Its dimension is the factor count.
  5. SplitFor each non-constant kernel element, take GCDs of f with that element minus each field constant.

The splitting step

A non-constant element of the Berlekamp subalgebra takes a constant value in each component of the quotient ring. Taking the GCD of the input with that element minus each constant separates the factors according to those values.

Pitfall

The splitting loop runs over all elements of the prime field, so its cost is proportional to the field size. For a large field this is prohibitive, and a probabilistic splitting step in the style of Cantor-Zassenhaus must be substituted.

Choosing between Berlekamp and the GCD pipeline

Berlekamp versus the GCD pipeline
ConditionPreferred method
Small field, moderate degreeBerlekamp — deterministic and fast
Large fieldGCD pipeline; Berlekamp's splitting scales badly
High degreeGCD pipeline; the matrix is degree by degree
Factor count wanted without factorsBerlekamp
Irreducibility test onlyDistinct degree is cheaper

Cost

Berlekamp builds a matrix of size the degree squared and eliminates it, costing the cube of the degree. The GCD pipeline avoids matrices entirely. At high degree the pipeline wins decisively.

Beyond polynomials

The same kernel construction splits more general algebras over finite fields, which is precisely how algebra splitting is performed inside Buchmann-Lenstra prime decomposition.

Source. Henri Cohen, A Course in Computational Algebraic Number Theory, Springer GTM 138 — 3.4.5. Structural reference unverified: the source file was not available during authoring; chapter and section numbers are taken from the published edition and have not been checked against a physical copy.

Related pages

  • Finite Field Arithmetic in Practice
  • Gaussian Elimination over Finite Fields
  • Splitting Separable Algebras over Finite Fields
  • Cantor-Zassenhaus Equal Degree Splitting
  • Mignotte Bounds on Polynomial Factors

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