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A Theory and an Algorithm for Computing Sparse Multivariate Polynomial Remainder Sequence

机译:稀疏多元多项式余数序列的计算理论和算法

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This paper presents an algorithm for computing the polynomial remainder sequence (PRS) and corresponding cofactor sequences of sparse multivariate polynomials over a number field K. Most conventional algorithms for computing PRSs are based on the pseudo remainder (Prem), and the celebrated subresultant theory for the PRS has been constructed on the Prem. The Prem is uneconomical for computing PRSs of sparse polynomials. Hence, in this paper, the concept of sparse pseudo remainder (spsPrem) is defined. No subresultant-like theory has been developed so far for the PRS based on spsPrem. Therefore, we develop a matrix theory for spsPrem-based PRSs. The computational formula for PRS, regardless of whether it is based on Prem or spsPrem, causes a considerable intermediate expression growth. Hence, we next propose a technique to suppress the expression growth largely. The technique utilizes the power-series arithmetic but no Hensel lifting. Simple experiments show that our technique suppresses the intermediate expression growth fairly well, if the sub-variable ordering is set suitably.
机译:本文提出了一种在数域K上计算稀疏多元多项式的多项式余数序列(PRS)和对应的辅因子序列的算法。大多数传统的计算PRS的算法都基于伪余数(Prem),以及著名的关于PRS的子结果理论。 PRS已在Prem上构建。对于计算稀疏多项式的PRS,Prem不经济。因此,在本文中,定义了稀疏伪余数(spsPrem)的概念。到目前为止,尚未开发基于spsPrem的PRS的类似亚结果的理论。因此,我们开发了基于spsPrem的PRS的矩阵理论。不管它是基于Prem还是spsPrem的,PRS的计算公式都会导致大量的中间表达增长。因此,我们接下来提出一种抑制表达增长的技术。该技术利用幂级数算法,但不使用Hensel提升。简单的实验表明,如果适当设置子变量的顺序,我们的技术可以很好地抑制中间表达的增长。

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