一种计算参数多元多项式GCD的有效算法

D. Kapur, Dong Lu, M. Monagan, Yao Sun, Dingkang Wang
{"title":"一种计算参数多元多项式GCD的有效算法","authors":"D. Kapur, Dong Lu, M. Monagan, Yao Sun, Dingkang Wang","doi":"10.1145/3208976.3208980","DOIUrl":null,"url":null,"abstract":"A new efficient algorithm for computing a parametric greatest common divisor (GCD) of parametric multivariate polynomials over k[u][x] is presented. The algorithm is based on a well-known simple insight that the GCD of two multivariate polynomials (non-parametric as well as parametric) can be extracted using the generator of the quotient ideal of a polynomial with respect to the second polynomial. And, further, this generator can be obtained by computing a minimal Gröbner basis of the quotient ideal. The main attraction of this idea is that it generalizes to the parametric case for which a comprehensive Gröbner basis is constructed for the parametric quotient ideal. It is proved that in a minimal comprehensive Gröbner system of a parametric quotient ideal, each branch of specializations corresponds to a principal parametric ideal with a single generator. Using this generator, the parametric GCD of that branch is obtained by division. This algorithm does not need to consider whether parametric polynomials are primitive w.r.t. the main variable. This is in sharp contrast to two algorithms recently proposed by Nagasaka (ISSAC, 2017). The resulting algorithm is not only conceptually simple to understand but is considerably efficient. The proposed algorithm and both of Nagasaka's algorithms have been implemented in Singular (available at http://www.mmrc.iss.ac.cn/~dwang/software.html), and their performance is compared on a number of examples. For more than two polynomials, this process can be repeated by considering pairs of polynomials; the efficiency in that case becomes even more evident.","PeriodicalId":105762,"journal":{"name":"Proceedings of the 2018 ACM International Symposium on Symbolic and Algebraic Computation","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"An Efficient Algorithm for Computing Parametric Multivariate Polynomial GCD\",\"authors\":\"D. Kapur, Dong Lu, M. Monagan, Yao Sun, Dingkang Wang\",\"doi\":\"10.1145/3208976.3208980\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new efficient algorithm for computing a parametric greatest common divisor (GCD) of parametric multivariate polynomials over k[u][x] is presented. The algorithm is based on a well-known simple insight that the GCD of two multivariate polynomials (non-parametric as well as parametric) can be extracted using the generator of the quotient ideal of a polynomial with respect to the second polynomial. And, further, this generator can be obtained by computing a minimal Gröbner basis of the quotient ideal. The main attraction of this idea is that it generalizes to the parametric case for which a comprehensive Gröbner basis is constructed for the parametric quotient ideal. It is proved that in a minimal comprehensive Gröbner system of a parametric quotient ideal, each branch of specializations corresponds to a principal parametric ideal with a single generator. Using this generator, the parametric GCD of that branch is obtained by division. This algorithm does not need to consider whether parametric polynomials are primitive w.r.t. the main variable. This is in sharp contrast to two algorithms recently proposed by Nagasaka (ISSAC, 2017). The resulting algorithm is not only conceptually simple to understand but is considerably efficient. The proposed algorithm and both of Nagasaka's algorithms have been implemented in Singular (available at http://www.mmrc.iss.ac.cn/~dwang/software.html), and their performance is compared on a number of examples. For more than two polynomials, this process can be repeated by considering pairs of polynomials; the efficiency in that case becomes even more evident.\",\"PeriodicalId\":105762,\"journal\":{\"name\":\"Proceedings of the 2018 ACM International Symposium on Symbolic and Algebraic Computation\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2018 ACM International Symposium on Symbolic and Algebraic Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3208976.3208980\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 ACM International Symposium on Symbolic and Algebraic Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3208976.3208980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

提出了一种计算k[u][x]上参数多元多项式参数最大公约数的高效算法。该算法基于一个众所周知的简单见解,即两个多元多项式(非参数和参数)的GCD可以使用多项式相对于第二个多项式的商理想的生成器来提取。进一步,该生成器可以通过计算商理想的最小Gröbner基来获得。这个想法的主要吸引力在于它推广到参数情况,为参数商理想构造了一个全面的Gröbner基。证明了在一个参数商理想的最小综合Gröbner系统中,每个专门化分支对应于一个主参数理想,并具有单个生成器。利用该生成器,通过除法得到该支路的参数GCD。该算法不需要考虑参数多项式是否为原始多项式,而不是主要变量。这与Nagasaka最近提出的两种算法(ISSAC, 2017)形成鲜明对比。所得到的算法不仅在概念上易于理解,而且相当高效。所提出的算法和Nagasaka的两种算法已经在Singular中实现(可在http://www.mmrc.iss.ac.cn/~dwang/software.html上获得),并在许多示例上比较了它们的性能。对于两个以上的多项式,这个过程可以通过考虑多项式对来重复;在这种情况下,效率变得更加明显。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An Efficient Algorithm for Computing Parametric Multivariate Polynomial GCD
A new efficient algorithm for computing a parametric greatest common divisor (GCD) of parametric multivariate polynomials over k[u][x] is presented. The algorithm is based on a well-known simple insight that the GCD of two multivariate polynomials (non-parametric as well as parametric) can be extracted using the generator of the quotient ideal of a polynomial with respect to the second polynomial. And, further, this generator can be obtained by computing a minimal Gröbner basis of the quotient ideal. The main attraction of this idea is that it generalizes to the parametric case for which a comprehensive Gröbner basis is constructed for the parametric quotient ideal. It is proved that in a minimal comprehensive Gröbner system of a parametric quotient ideal, each branch of specializations corresponds to a principal parametric ideal with a single generator. Using this generator, the parametric GCD of that branch is obtained by division. This algorithm does not need to consider whether parametric polynomials are primitive w.r.t. the main variable. This is in sharp contrast to two algorithms recently proposed by Nagasaka (ISSAC, 2017). The resulting algorithm is not only conceptually simple to understand but is considerably efficient. The proposed algorithm and both of Nagasaka's algorithms have been implemented in Singular (available at http://www.mmrc.iss.ac.cn/~dwang/software.html), and their performance is compared on a number of examples. For more than two polynomials, this process can be repeated by considering pairs of polynomials; the efficiency in that case becomes even more evident.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Constructive Arithmetics in Ore Localizations with Enough Commutativity Extending the GVW Algorithm to Local Ring Comparison of CAD-based Methods for Computation of Rational Function Limits Polynomial Equivalence Problems for Sum of Affine Powers Fast Straightening Algorithm for Bracket Polynomials Based on Tableau Manipulations
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1