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JRF IN MATHEMATICS 2011
JRF IN MATHEMATICS 2011

The Fundamental Theorem of Arithmetic
The Fundamental Theorem of Arithmetic

Explicit Methods for Solving Diophantine Equations
Explicit Methods for Solving Diophantine Equations

Notes on the Fundamental Theorem of Arithmetic
Notes on the Fundamental Theorem of Arithmetic

Encoding Rational Numbers for FHE
Encoding Rational Numbers for FHE

Hidden Markov Model Cryptanalysis
Hidden Markov Model Cryptanalysis

18.786 PROBLEM SET 3
18.786 PROBLEM SET 3

Solutions - MIT OpenCourseWare
Solutions - MIT OpenCourseWare

Unit 6: Section 8.1 Factors and Greatest Common Factors Numbers
Unit 6: Section 8.1 Factors and Greatest Common Factors Numbers

Eigenvalues, eigenvectors, and eigenspaces of linear operators
Eigenvalues, eigenvectors, and eigenspaces of linear operators

Fields - MIT Mathematics
Fields - MIT Mathematics

Document
Document

Solution
Solution

Integers modulo N
Integers modulo N

Lesson 11: The Special Role of Zero in Factoring
Lesson 11: The Special Role of Zero in Factoring

Factoring Polynomials
Factoring Polynomials

Algebraic Systems
Algebraic Systems

... by ◦ the operation of composition of functions. The result of this operation is a new function f◦g from Y into Y, whose value on every yY is defined as (f◦g)(y)=f(g(y)). Example 1.7. Symmetric difference. For any set X, 2X denotes the set of all subsets of X. In addition to the well-known set opera ...
Math Circles - Number Theory
Math Circles - Number Theory

Math 1100: Quantitative Analysis Limits of Rational Functions Limits of Polynomial Functions
Math 1100: Quantitative Analysis Limits of Rational Functions Limits of Polynomial Functions

Mathematics of Cryptography Part I: Modular Arithmetic
Mathematics of Cryptography Part I: Modular Arithmetic

Modular Arithmetic, Congruence, and Matrices
Modular Arithmetic, Congruence, and Matrices

Mathematics of Cryptography
Mathematics of Cryptography

HALL-LITTLEWOOD POLYNOMIALS, ALCOVE WALKS, AND
HALL-LITTLEWOOD POLYNOMIALS, ALCOVE WALKS, AND

inverse scattering of buried inhomogeneous dielectric material
inverse scattering of buried inhomogeneous dielectric material

HOMEWORK 3: SOLUTIONS 1. Consider a Markov chain whose
HOMEWORK 3: SOLUTIONS 1. Consider a Markov chain whose

< 1 ... 104 105 106 107 108 109 110 111 112 ... 231 >

Factorization of polynomials over finite fields

In mathematics and computer algebra the factorization of a polynomial consists of decomposing it into a product of irreducible factors. This decomposition is theoretically possible and is unique for polynomials with coefficients in any field, but rather strong restrictions on the field of the coefficients are needed to allow the computation of the factorization by means of an algorithm. In practice, algorithms have been designed only for polynomials with coefficients in a finite field, in the field of rationals or in a finitely generated field extension of one of them.The case of the factorization of univariate polynomials over a finite field, which is the subject of this article, is especially important, because all the algorithms (including the case of multivariate polynomials over the rational numbers), which are sufficiently efficient to be implemented, reduce the problem to this case (see Polynomial factorization). It is also interesting for various applications of finite fields, such as coding theory (cyclic redundancy codes and BCH codes), cryptography (public key cryptography by the means of elliptic curves), and computational number theory.As the reduction of the factorization of multivariate polynomials to that of univariate polynomials does not have any specificity in the case of coefficients in a finite field, only polynomials with one variable are considered in this article.
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