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In mathematics, polynomial identity testing (PIT) is the problem of efficiently determining whether two multivariate polynomials are identical. More formally, a PIT algorithm is given an arithmetic circuit that computes a polynomial p in a field, and decides whether p is the zero polynomial.
In mathematics and computer science, Horner's method (or Horner's scheme) is an algorithm for polynomial evaluation.Although named after William George Horner, this method is much older, as it has been attributed to Joseph-Louis Lagrange by Horner himself, and can be traced back many hundreds of years to Chinese and Persian mathematicians. [1]
Horner's method evaluates a polynomial using repeated bracketing: + + + + + = + (+ (+ (+ + (+)))). This method reduces the number of multiplications and additions to just Horner's method is so common that a computer instruction "multiply–accumulate operation" has been added to many computer processors, which allow doing the addition and multiplication operations in one combined step.
The multilinear polynomials in variables form a -dimensional vector space, which is also the basis used in the Fourier analysis of (pseudo-)Boolean functions. Every ( pseudo- ) Boolean function can be uniquely expressed as a multilinear polynomial (up to a choice of domain and codomain).
This factorization is also unique up to the choice of a sign. For example, + + + = + + + is a factorization into content and primitive part. Gauss proved that the product of two primitive polynomials is also primitive (Gauss's lemma). This implies that a primitive polynomial is irreducible over the rationals if and only if it is irreducible ...
If F is a field and f and g are polynomials in F[x] with g ≠ 0, then there exist unique polynomials q and r in F[x] with = + and such that the degree of r is smaller than the degree of g (using the convention that the polynomial 0 has a negative degree). The polynomials q and r are uniquely determined by f and g.
The usual way of representing the solutions is through zero-dimensional regular chains. Such a chain consists of a sequence of polynomials f 1 (x 1), f 2 (x 1, x 2), ..., f n (x 1, ..., x n) such that, for every i such that 1 ≤ i ≤ n. f i is a polynomial in x 1, ..., x i only, which has a degree d i > 0 in x i;
The choice of the S-polynomials to reduce and of the polynomials used for reducing them is devoted to heuristics. As in many computational problems, heuristics cannot detect most hidden simplifications, and if heuristic choices are avoided, one may get a dramatic improvement of the algorithm efficiency.