En matemáticas, la factorización es una técnica que consiste en la descomposición de una expresión matemática (que puede ser un número, una suma o resta, una matriz, un polinomio, etc.) en forma de producto. Existen distintos métodos de factorización, dependiendo de los objetos matemáticos estudiados; el objetivo es simplificar una expresión o reescribirla en términos de «bloques fundamentales», que reciben el nombre de factores, como por ejemplo un número en números primos, o un polinomio en polinomios irreducibles. Lo contrario de la factorización de polinomios es la expansión, la multiplicación de los factores juntos polinómicas a un polinomio "ampliado", escrito como una simple suma de términos. El teorema fundamental de la aritmética cubre la factorización de números enteros, y para la factorización de polinomios, el teorema fundamental del álgebra. La factorización de números enteros muy grandes en producto de factores primos requiere de algoritmos sofisticados, el nivel de complejidad de tales algoritmos está a la base de la fiabilidad de algunos sistemas de criptografía asimétrica como el RSA.

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In mathematics, factorization (also factorisation in some forms of British English) or factoring is the decomposition of an object (for example, a number, a polynomial, or a matrix) into a product of other objects, or factors, which when multiplied together give the original. For example, the number 15 factors into primes as 3 × 5, and the polynomial x2 − 4 factors as (x − 2)(x + 2). In all cases, a product of simpler objects is obtained. The aim of factoring is usually to reduce something to “basic building blocks”, such as numbers to prime numbers, or polynomials to irreducible polynomials. Factoring integers is covered by the fundamental theorem of arithmetic and factoring polynomials by the fundamental theorem of algebra. Viète's formulas relate the coefficients of a polynomial to its roots. The opposite of polynomial factorization is expansion, the multiplying together of polynomial factors to an “expanded” polynomial, written as just a sum of terms. Integer factorization for large integers appears to be a difficult problem. There is no known method to carry it out quickly. Its complexity is the basis of the assumed security of some public key cryptography algorithms, such as RSA. A matrix can also be factorized into a product of matrices of special types, for an application in which that form is convenient. One major example of this uses an orthogonal or unitary matrix, and a triangular matrix. There are different types: QR decomposition, LQ, QL, RQ, RZ. Another example is the factorization of a function as the composition of other functions having certain properties; for example, every function can be viewed as the composition of a surjective function with an injective function. This situation is generalized by factorization systems.

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