TL;DR: In the Groebner package, the most commonly used commands are NormalForm, for doing the division algorithm, and Basis, for computing a Groebners basis as mentioned in this paper. But these commands require a large number of variables.
Abstract: (here, > is the Maple prompt). Once the Groebner package is loaded, you can perform the division algorithm, compute Groebner bases, and carry out a variety of other commands described below. In Maple, a monomial ordering is called a monomial order. The monomial orderings lex, grlex, and grevlex from Chapter 2 are easy to use in Maple. Lex order is called plex (for “pure lexicographic”), grlex order is called grlex, and grevlex order is called tdeg (for “total degree”). Be careful not to confuse tdeg with grlex. Since a monomial order depends also on how the variables are ordered, Maple needs to know both the monomial order you want (plex, grlex or tdeg) and a list of variables. For example, to tell Maple to use lex order with variables x > y > z, you would need to input plex(x,y,z). The Groebner package also knows some elimination orders, as defined in Exercise 5 of Chapter 3, §1. To eliminate the first k variables from x1, . . . , xn, one can use the monomial order lexdeg([x 1,. . .,x k],[x {k+1},. . . ,x n]) (remember that Maple encloses a list inside brackets [. . .]). This order is the elimination order of Bayer and Stillman described in Exercise 6 of Chapter 3, §1. The Maple documentation for the Groebner package also describes how to use certain weighted orders, and we will explain below how matrix orders give us many more monomial orderings. The most commonly used commands in the Groebner package are NormalForm, for doing the division algorithm, and Basis, for computing a Groebner basis. NormalForm has the following syntax:
TL;DR: The Grobner bases technique as mentioned in this paper provides algorithmic solutions to a variety of problems connected with ideals generated by finite sets F of multivariate polynomials, such as exact solutions of F viewed as a system of algebraic equations, computations in the residue class ring modulo the ideal generated by F, decision about various properties of the ideal created by F and word problems modulo ideals.
Abstract: Problems connected with ideals generated by finite sets F of multivariate polynomials occur, as mathematical subproblems, in various branches of systems theory, see, for example, [5]. The method of Grobner bases is a technique that provides algorithmic solutions to a variety of such problems, for instance, exact solutions of F viewed as a system of algebraic equations, computations in the residue class ring modulo the ideal generated by F, decision about various properties of the ideal generated by F, polynomial solution of the linear homogeneous equation with coefficients in F, word problems modulo ideals and in commutative semigroups (reversible Petri nets), the bijective enumeration of all polynomial ideal over a given coefficient domain etc.
TL;DR: In this paper, the Hilbert series of monotone monomial ideals and their deformation is shown to be bounded by the Hilbert sequence of the deformation of a monomial ideal.
Abstract: For a graph G, we construct two algebras whose dimensions are both equal to the number of spanning trees of G. One of these algebras is the quotient of the polynomial ring modulo certain monomial ideal, while the other is the quotient of the polynomial ring modulo certain powers of linear forms. We describe the set of monomials that forms a linear basis in each of these two algebras. The basis elements correspond to G-parking functions that naturally came up in the abelian sandpile model. These ideals are instances of the general class of monotone monomial ideals and their deformations. We show that the Hilbert series of a monotone monomial ideal is always bounded by the Hilbert series of its deformation. Then we define an even more general class of monomial ideals associated with posets and construct free resolutions for these ideals. In some cases these resolutions coincide with Scarf resolutions. We prove several formulas for Hilbert series of monotone monomial ideals and investigate when they are equal to Hilbert series of deformations. In the appendix we discuss the abelian sandpile model.
TL;DR: An efficient algorithm that solves the problem of finding the minimal polynomial of an ideal with respect to a certain monomial order is presented based on the theory of Grobner bases of modules.
TL;DR: In this article, the complexity of solving "typical" overdetermined algebraic systems with solutions in GF(2) using Grobner bases has been studied and a priori upper bound on the complexity is given.
Abstract: We present complexity results for solving "typical"overdetermined algebraic systems over GF(2) with solutions in GF(2) using Grobner bases. They are useful for instance to predictthe complexity of an algebraic cryptanalysis over a cryptosystem,they give a priori upper bounds. We define semi-regularsequences and their associated notion of degree of regularity Dreg.The motivation for studying semi-regular sequences is that"random" sequences are semi-regular, and Dreg is closely related tothe global cost of the Grobner basis computation for a gradedadmissible monomial order. Using inparticular the F5 Grobner basis algorithm, we show that forsemi-regular sequences the behavior of F5 (in a matrix version)can be followed step by step, and the size of all matrices madeexplicit. We deduce Dmax, and using asymptotic analysis methodswe compute its asymptotic expansion. We give many explicitexamples, and discuss the complexity of the global arithmeticcost of the Grobner basis computation for m quadratic equations in n variables: for m=N n with N constant, the computationis exponential, if n