Subresultants of several univariate polynomials in Newton basis

IF 0.6 4区 数学 Q4 COMPUTER SCIENCE, THEORY & METHODS Journal of Symbolic Computation Pub Date : 2024-08-30 DOI:10.1016/j.jsc.2024.102378
Weidong Wang, Jing Yang
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Abstract

In this paper, we consider the problem of formulating the subresultant polynomials for several univariate polynomials in Newton basis. It is required that the resulting subresultant polynomials be expressed in the same Newton basis as that used in the input polynomials. To solve the problem, we devise a particular matrix with the help of the companion matrix of a polynomial in Newton basis. Meanwhile, the concept of determinant polynomial in power basis for formulating subresultant polynomials is extended to that in Newton basis. It is proved that the generalized determinant polynomial of the specially designed matrix provides a new formula for the subresultant polynomial in Newton basis, which is equivalent to the subresultant polynomial in power basis. Furthermore, we show an application of the new formula in devising a basis-preserving method for computing the gcd of several Newton polynomials.

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几个单变量多项式在牛顿基上的子结果
在本文中,我们考虑的问题是在牛顿基础上为多个单变量多项式编制子结果多项式。要求得到的子结果多项式与输入多项式所用的牛顿基相同。为了解决这个问题,我们借助牛顿基多项式的伴矩阵设计了一个特殊的矩阵。同时,将幂基行列式多项式的概念扩展到牛顿基行列式多项式。研究证明,特殊设计矩阵的广义行列式多项式提供了牛顿基次结果多项式的新公式,它等价于幂基次结果多项式。此外,我们还展示了新公式在设计计算多个牛顿多项式的 gcd 的保基方法中的应用。
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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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