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{{Short description|Method in computational algebra}}
{{for|the algorithm dealing with LFSRs|Berlekamp–Massey algorithm}}
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==Overview==
Berlekamp's algorithm takes as input a [[square-free polynomial]] <math>f(x)</math> (i.e. one with no repeated factors) of degree <math>n</math> with coefficients in a finite field <math>\mathbb{F}_q</math> and gives as output a polynomial <math>g(x)</math> with coefficients in the same field such that <math>g(x)</math> divides <math>f(x)</math>. The algorithm may then be applied recursively to these and subsequent divisors, until we find the decomposition of <math>f(x)</math> into powers of [[irreducible polynomial]]s (recalling that the [[ring (mathematics)|ring]] of polynomials over a finite field is a [[unique factorization ___domain]]).
All possible factors of <math>f(x)</math> are contained within the [[factor ring]]
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The algorithm focuses on polynomials <math>g(x) \in R</math> which satisfy the congruence:
:<math>g(x)^q \equiv g(x) \pmod{f(x)}.\,</math>
These polynomials form a [[subalgebra]] of R (which can be considered as an <math>n</math>-dimensional vector space over <math>\mathbb{F}_q</math>), called the ''Berlekamp subalgebra''. The Berlekamp subalgebra is of interest because the polynomials <math>g(x)</math> it contains satisfy
:<math>f(x) = \prod_{s \in \mathbb{F}_q} \gcd(f(x),g(x)-s).</math>
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:<math>g = (g_0, g_1, \ldots, g_{n-1}).\,</math>
It is relatively straightforward to see that the row vector <math>g\mathcal{Q}</math> corresponds, in the same way, to the reduction of <math>g(x)^q</math> modulo <math>f(x)</math>. Consequently, a polynomial <math>g(x) \in R</math> is in the Berlekamp subalgebra if and only if <math>g(\mathcal{Q}-I)=0</math> (where <math>I</math> is the <math>n \times n</math> [[identity matrix]]), i.e. if and only if it is in the null space of <math>\mathcal{Q}-I</math>.
By computing the matrix <math>\mathcal{Q}-I</math> and reducing it to [[reduced row echelon form]] and then easily reading off a basis for the null space, we may find a basis for the Berlekamp subalgebra and hence construct polynomials <math>g(x)</math> in it. We then need to successively compute GCDs of the form above until we find a non-trivial factor. Since the ring of polynomials over a field is a [[Euclidean ___domain]], we may compute these GCDs using the [[Euclidean algorithm]].
==Conceptual algebraic explanation==
With some abstract algebra, the idea behind Berlekamp's algorithm becomes conceptually clear. We represent a finite field <math display = "inline"> \mathbb{F}_q </math>, where <math display="inline"> q = p^m </math> for some prime <math display="inline">p</math>, as <math display = "inline"> \mathbb{F}_p[y]/(g(y)) </math>. We can assume that <math display = "inline"> f(x) \in \mathbb{F}_q[x] </math> is square free, by taking all possible pth roots and then computing the gcd with its derivative.
Now, suppose that <math display = "inline"> f(x) = f_1(x) \ldots f_n(x) </math> is the factorization into irreducibles. Then we have a ring isomorphism, <math display = "inline"> \sigma: \mathbb{F}_q[x]/(f(x)) \to \prod_i \mathbb{F}_q[x]/(f_i(x)) </math>, given by the Chinese remainder theorem. The crucial observation is that the Frobenius automorphism <math display = "inline"> x \to x^p </math> commutes with <math display = "inline"> \sigma </math>, so that if we denote <math display = "inline"> \text{Fix}_p(R) = \{ f \in R : f^p = f \} </math>, then <math display = "inline"> \sigma </math> restricts to an isomorphism <math display = "inline"> \text{Fix}_p( \mathbb{F}_q[x]/(f(x)) ) \to \prod_{i = 1}^n \text{Fix}_p( \mathbb{F}_q[x]/(f_i(x)) ) </math>. By finite field theory, <math display = "inline"> \text{Fix}_p( \mathbb{F}_q[x]/(f_i(x)) )</math> is always the prime subfield of that field extension. Thus, <math display = "inline"> \text{Fix}_p( \mathbb{F}_q[x]/(f(x)) ) </math> has <math display = "inline"> p </math> elements if and only if <math display = "inline"> f(x) </math> is irreducible.
Moreover, we can use the fact that the Frobenius automorphism is <math display = "inline"> \mathbb{F}_p </math>-linear to calculate the fixed set. That is, we note that <math display = "inline"> \text{Fix}_p( \mathbb{F}_q[x]/(f(x)) ) </math> is a <math display = "inline"> \mathbb{F}_p </math>-subspace, and an explicit basis for it can be calculated in the polynomial ring <math display = "inline"> \mathbb{F}_p[x,y]/(f,g) </math> by computing <math display = "inline"> (x^i y^j)^p </math> and establishing the linear equations on the coefficients of <math display = "inline"> x,y </math> polynomials that are satisfied iff it is fixed by Frobenius. We note that at this point we have an efficiently computable irreducibility criterion, and the remaining analysis shows how to use this to find factors.
The algorithm now breaks down into two cases:
* In the case of small <math display = "inline"> p </math> we can construct any <math display = "inline"> g \in \text{Fix}_p( \mathbb{F}_q[x]/(f(x)) ) \setminus \mathbb{F}_p </math>, and then observe that for some <math display = "inline"> a \in \mathbb{F}_p </math> there are <math display = "inline"> i,j </math> so that <math display = "inline"> g - a = 0 \mod f_i</math> and <math display = "inline"> g - a \not = 0 \mod f_j </math>. Such a <math display = "inline"> g - a </math> has a nontrivial factor in common with <math display = "inline"> f(x) </math>, which can be computed via the gcd. As <math display = "inline"> p </math> is small, we can cycle through all possible <math display = "inline"> a </math>.
* For the case of large primes, which are necessarily odd, one can exploit the fact that a random nonzero element of <math display = "inline"> \mathbb{F}_p^* </math> is a square with probability <math display = "inline"> 1/2 </math>, and that the map <math display = "inline"> x \to x^{ \frac{ p -1}{2}} </math> maps the set of non-zero squares to <math display = "inline"> 1 </math>, and the set of non-squares to <math display = "inline"> -1 </math>. Thus, if we take a random element <math display = "inline"> g \in \text{Fix}_p( \mathbb{F}_q[x]/f(x)) </math>, then with good probability <math display = "inline"> g^{ \frac{ p - 1}{2}} - 1 </math> will have a non-trivial factor in common with <math display = "inline"> f(x) </math>.
For further details one can consult.<ref name="Springer">{{cite book | title=Theory of Computation - Dexter Kozen | publisher=Springer | url=https://www.springer.com/gp/book/9781846282973 | access-date=2020-09-19}}</ref>
==Applications==
One important application of Berlekamp's algorithm is in computing [[discrete logarithm]]s over finite fields <math>\mathbb{F}_{p^n}</math>, where <math>p</math> is prime and <math>n\geq 2</math>. Computing discrete logarithms is an important problem in [[public key cryptography]] and [[Error detection and correction|error-control coding]]. For a finite field, the fastest known method is the [[index calculus|index calculus method]], which involves the factorisation of field elements. If we represent the field <math>\mathbb{F}_{p^n}</math> in the usual way - that is, as polynomials over the base field <math>\mathbb{F}_{p}</math>, reduced modulo an irreducible polynomial of degree <math>n</math> - then this is simply polynomial factorisation, as provided by Berlekamp's algorithm.
==Implementation in
Berlekamp's algorithm may be accessed in the PARI/GP package using the [http://pari.math.u-bordeaux.fr/dochtml/html
==See also==
*[[Polynomial factorization|Polynomial factorisation]]
*[[Factorization of polynomials over a finite field and irreducibility tests]]
*[[
==References==
{{Reflist}}
*{{Cite journal
|first=Elwyn R.
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|journal=[[Bell System Technical Journal]]
|volume=46
|issue= ▼
|pages=1853–1859
|year=1967
▲|issue=8
|mr=0219231
|doi=10.1002/j.1538-7305.1967.tb03174.x}} [http://www.alcatel-lucent.com/bstj/vol46-1967/articles/bstj46-8-1853.pdf BSTJ] Later republished in: {{Cite book |first=Elwyn R. |last=Berlekamp |title=Algebraic Coding Theory
*{{cite book
|author=
|author-link=Donald E. Knuth
|chapter=4.6.2 Factorization of Polynomials
|title=Seminumerical Algorithms
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[[Category:Computer algebra]]
[[Category:Finite fields]]
[[Category:Polynomial factorization algorithms]]
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