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In mathematics, factorization (or factorisation, see English spelling differences) or factoring consists of writing a number or another mathematical object as a product of several factors, usually smaller or simpler objects of the same kind. For example, 3 × 5 is an integer factorization of 15, and (x – 2)(x + 2) is a polynomial ...
The first polynomial factorization algorithm was published by Theodor von Schubert in 1793. [1] Leopold Kronecker rediscovered Schubert's algorithm in 1882 and extended it to multivariate polynomials and coefficients in an algebraic extension. But most of the knowledge on this topic is not older than circa 1965 and the first computer algebra ...
The polynomial P = x 4 + 1 is irreducible over Q but not over any finite field. On any field extension of F 2, P = (x + 1) 4. On every other finite field, at least one of −1, 2 and −2 is a square, because the product of two non-squares is a square and so we have; If =, then = (+) ().
If it does not exist, gcd(n,b) is a non-trivial factor of n. First we compute 2P. We have s(P) = s(1,1) = 4, so the coordinates of 2P = (x ′, y ′) are x ′ = s 2 – 2x = 14 and y ′ = s(x – x ′) – y = 4(1 – 14) – 1 = –53, all numbers understood (mod n). Just to check that this 2P is indeed on the curve: (–53) 2 = 2809 = 14 ...
The entry 4+2i = −i(1+i) 2 (2+i), for example, could also be written as 4+2i= (1+i) 2 (1−2i). The entries in the table resolve this ambiguity by the following convention: the factors are primes in the right complex half plane with absolute value of the real part larger than or equal to the absolute value of the imaginary part.
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In mathematics, Sophie Germain's identity is a polynomial factorization named after Sophie Germain stating that + = ((+) +) (() +) = (+ +) (+). Beyond its use in elementary algebra, it can also be used in number theory to factorize integers of the special form +, and it frequently forms the basis of problems in mathematics competitions.
In mathematics, a matrix factorization of a polynomial is a technique for factoring irreducible polynomials with matrices. David Eisenbud proved that every multivariate real-valued polynomial p without linear terms can be written as AB = pI, where A and B are square matrices and I is the identity matrix. [1]