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

机译:一种计算稀疏多变量多项式剩余序列的理论和算法

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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:本文介绍了一种计算多项式剩余序列(PRS)的算法,以及在数字K上的稀疏多变量多项式的相应辅助因子序列。计算PRSS的大多数传统算法基于伪余数(PROP),以及庆祝的子节点理论PRS已经在预制。在稀疏多项式的计算PRS的PRS是不经济的。因此,在本文中,定义了稀疏伪余量(SPSPrem)的概念。到目前为止,没有基于SPSPrem的PRS开发了类似的子文化理论。因此,我们为基于SPSPREM的PRS制定了矩阵理论。 PRS的计算公式,无论它是基于PREM还是SPSPREM,都会导致相当大的中间表达生长。因此,我们接下来提出了一种在很大程度上抑制表达生长的技术。该技术利用电源系列算术,但没有Hensel提升。如果适当地设定了子变量排序,则简单的实验表明,我们的技术抑制了相当良好的中间表达生长。

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