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引用次数: 0
摘要
卡萨斯-阿尔维罗猜想预言,特性为零的域上的每一个单变量多项式与其导数 \(H_i(f)\)都有一个公共因子,都是线性多项式的幂。证明这个猜想的一种方法是,首先证明某个小度 d 的多项式的猜想,编制一个该度的坏素数列表(即在度 d 和特征 p 中猜想失败的素数 p),然后推导出形式为 \(dp^\ell \), \(\ell \in \mathbb {N}\) 的所有度的猜想,其中 p 是 d 的好素数。在本文中,我们计算了结果 \(R(f,H_i(f))\中出现的某些区分单项式,并得到了每个度 \(d\in \mathbb {N}\setminus \{0\}\)的坏素数列表(并非详尽无遗)。
On the set of bad primes in the study of the Casas–Alvero conjecture
The Casas–Alvero conjecture predicts that every univariate polynomial over a field of characteristic zero having a common factor with each of its derivatives \(H_i(f)\) is a power of a linear polynomial. One approach to proving the conjecture is to first prove it for polynomials of some small degree d, compile a list of bad primes for that degree (namely, those primes p for which the conjecture fails in degree d and characteristic p) and then deduce the conjecture for all degrees of the form \(dp^\ell \), \(\ell \in \mathbb {N}\), where p is a good prime for d. In this paper, we calculate certain distinguished monomials appearing in the resultant \(R(f,H_i(f))\) and obtain a (non-exhaustive) list of bad primes for every degree \(d\in \mathbb {N}\setminus \{0\}\).
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.