An extended GCD algorithm for parametric univariate polynomials and application to parametric smith normal form

Dingkang Wang, Hesong Wang, Fanghui Xiao
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引用次数: 1

Abstract

An extended greatest common divisor (GCD) algorithm for parametric univariate polynomials is presented in this paper. This algorithm computes not only the GCD of parametric univariate polynomials in each constructible set but also the corresponding representation coefficients (or multipliers) for the GCD expressed as a linear combination of these parametric univariate polynomials. The key idea of our algorithm is that for non-parametric case the GCD of arbitrary finite number of univariate polynomials can be obtained by computing the minimal Gröbner basis of the ideal generated by those polynomials. But instead of computing the Gröbner basis of the ideal generated by those polynomials directly, we construct a special module by adding the unit vectors which can record the representation coefficients, then obtain the GCD and representation coefficients by computing a Gröbner basis of the module. This method can be naturally generalized to the parametric case because of the comprehensive Gröbner systems for modules. As a consequence, we obtain an extended GCD algorithm for parametric univariate polynomials. More importantly, we apply the proposed extended GCD algorithm to the computation of Smith normal form, and give the first algorithm for reducing a univariate polynomial matrix with parameters to its Smith normal form.
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参数一元多项式的扩展GCD算法及其在参数史密斯范式中的应用
提出了一种参数一元多项式的扩展最大公约数算法。该算法不仅计算每个可构造集中参数单变量多项式的GCD,而且计算这些参数单变量多项式的线性组合所对应的GCD的表示系数(或乘数)。该算法的核心思想是,对于非参数情况,任意有限个数的单变量多项式的GCD可以通过计算这些多项式所产生的理想的最小Gröbner基得到。但是我们不是直接计算由这些多项式产生的理想的Gröbner基,而是通过添加记录表征系数的单位向量来构造一个特殊的模块,然后通过计算该模块的Gröbner基来获得GCD和表征系数。这种方法可以很自然地推广到参数情况,因为对模块有全面的Gröbner系统。因此,我们得到了参数单变量多项式的扩展GCD算法。更重要的是,我们将所提出的扩展GCD算法应用于Smith范式的计算,并给出了将带参数的单变量多项式矩阵约化为Smith范式的第一个算法。
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