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14. The minimal polynomial For an example of a matrix which
14. The minimal polynomial For an example of a matrix which

... first case every vector is an eigenvector with eigenvalue 0, E0 (A0 ) = F 3 . In the second case the kernel is z = 0 so that (1, 0, 0) and (0, 1, 0) span E0 (A1 ). In the third case the kernel is y = z = 0, so that E0 (A2 ) is spanned by (1, 0, 0). But we already know that similar matrices have eige ...
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... all of algebraic number theory. 2. Dedekind domains We are now ready to prove the following theorem: Theorem 2.1. A ring of integers OK is a Dedekind domain: i.e., it satisfies (i) OK is Noetherian; (ii) Every non-zero prime ideal of OK is maximal; (iii) OK is integrally closed in its field of fract ...
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... reflection in G. An element c ∈ G is regular if and only if it has an eigenvector which is regular. Examples: (Springer, Invent. Math 25 (1974)) With Σn permuting x1 , . . . , xn in characteristic zero the regular elements are the n-cycles and the (n − 1)-cycles. (An eigenvector of any shorter cycle ...
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... • the rationals (Q, +, ∗), reals (R, +, ∗) and complex numbers (C, +, ∗) form fields; • the set of 2 × 2 matrices with real entries forms a non-commutative ring with identity w.r.t. matrix addition and multiplication. • the group Zn with addition as before and multiplication defined by [a][b] := [ab ...
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... I don’t have time to describe them here. I will say that the key element, which took me years to find, is an algorithm that factors f (x) mod g(y) when f and g are monic irreducible polynomials with integer coefficients, or, more generally, with coefficients in Z[c1 , c2 , . . . , cν ]. Note that th ...
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Gröbner basis

In mathematics, and more specifically in computer algebra, computational algebraic geometry, and computational commutative algebra, a Gröbner basis is a particular kind of generating set of an ideal in a polynomial ring over a field K[x1, ..,xn]. A Gröbner basis allows many important properties of the ideal and the associated algebraic variety to be deduced easily, such as the dimension and the number of zeros when it is finite. Gröbner basis computation is one of the main practical tools for solving systems of polynomial equations and computing the images of algebraic varieties under projections or rational maps.Gröbner basis computation can be seen as a multivariate, non-linear generalization of both Euclid's algorithm for computing polynomial greatest common divisors, andGaussian elimination for linear systems.Gröbner bases were introduced in 1965, together with an algorithm to compute them (Buchberger's algorithm), by Bruno Buchberger in his Ph.D. thesis. He named them after his advisor Wolfgang Gröbner. In 2007, Buchberger received the Association for Computing Machinery's Paris Kanellakis Theory and Practice Award for this work.However, the Russian mathematician N. M. Gjunter had introduced a similar notion in 1913, published in various Russian mathematical journals. These papers were largely ignored by the mathematical community until their rediscovery in 1987 by Bodo Renschuch et al. An analogous concept for local rings was developed independently by Heisuke Hironaka in 1964, who named them standard bases.The theory of Gröbner bases has been extended by many authors in various directions. It has been generalized to other structures such as polynomials over principal ideal rings or polynomial rings, and also some classes of non-commutative rings and algebras, like Ore algebras.
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