A new algorithm for Gröbner bases conversion

IF 0.6 4区 数学 Q4 COMPUTER SCIENCE, THEORY & METHODS
Amir Hashemi , Deepak Kapur
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引用次数: 0

Abstract

A new approach for Gröbner bases conversion of polynomial ideals (over a field) of arbitrary dimension is presented. In contrast to the only other approach based on Gröbner fan and Gröbner walk for positive dimensional ideals, the proposed approach is simpler to understand, prove, and implement. It is based on defining for a given polynomial, a truncated sub-polynomial consisting of all monomials that can possibly become the leading monomial with respect to the target ordering: the monomials between the leading monomial of the target ordering and the leading monomial of the initial ordering.
The main ingredient of the new algorithm is the computation of a Gröbner basis with respect to the target ordering for the ideal generated by such truncated parts of the input Gröbner basis. This is done using the extended Buchberger algorithm that also outputs the relationship between the input and output bases. That information is used in attempts to recover a Gröbner basis of the ideal with respect to the target ordering. In general, more than one iteration may be needed to get a Gröbner basis with respect to the target ordering since truncated polynomials may miss some leading monomials.
The new algorithm has been implemented in Maple and its operation is illustrated using an example. The performance of this implementation is compared with the implementations of other approaches in Maple. In practice, a Gröbner basis with respect to a target ordering can be computed in a single iteration on most examples.
Since the proposed basis conversion algorithm uses simple concepts of Gröbner basis theory, it can be easily taught in contrast to methods based on Gröbner walk.
格氏碱基转换的新算法
本文提出了一种转换任意维度多项式理想(在一个域上)的格罗布纳基的新方法。与其他唯一基于格罗伯纳扇形和格罗伯纳走正维理想的方法相比,所提出的方法更易于理解、证明和实施。它的基础是为给定的多项式定义一个截断的子多项式,该子多项式由所有可能成为目标排序的前导单项式的单项式组成:目标排序的前导单项式和初始排序的前导单项式之间的单项式。计算是通过扩展的布赫伯格算法完成的,该算法还能输出输入和输出基础之间的关系。这些信息将被用于恢复与目标排序相关的理想格罗伯纳基。一般来说,由于截断多项式可能会遗漏一些前导单项式,因此可能需要不止一次迭代才能得到与目标排序相关的格罗伯纳基。新算法已在 Maple 中实现,并通过一个例子对其操作进行了说明。该实现方法的性能与 Maple 中其他方法的实现方法进行了比较。实际上,在大多数例子中,一次迭代就可以计算出与目标排序相关的格罗伯纳基础。由于所提出的基础转换算法使用的是格罗伯纳基础理论的简单概念,因此与基于格罗伯纳行走的方法相比,它很容易教授。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Symbolic Computation
Journal of Symbolic Computation 工程技术-计算机:理论方法
CiteScore
2.10
自引率
14.30%
发文量
75
审稿时长
142 days
期刊介绍: An international journal, the Journal of Symbolic Computation, founded by Bruno Buchberger in 1985, is directed to mathematicians and computer scientists who have a particular interest in symbolic computation. The journal provides a forum for research in the algorithmic treatment of all types of symbolic objects: objects in formal languages (terms, formulas, programs); algebraic objects (elements in basic number domains, polynomials, residue classes, etc.); and geometrical objects. It is the explicit goal of the journal to promote the integration of symbolic computation by establishing one common avenue of communication for researchers working in the different subareas. It is also important that the algorithmic achievements of these areas should be made available to the human problem-solver in integrated software systems for symbolic computation. To help this integration, the journal publishes invited tutorial surveys as well as Applications Letters and System Descriptions.
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