{"title":"计算一般的二元Gröbner基与mathmagix","authors":"Robin Larrieu","doi":"10.1145/3371991.3371994","DOIUrl":null,"url":null,"abstract":"Let <i>A, B</i> ∈ K[<i>X,Y</i>] be two bivariate polynomials over an effective field K, and let <i>G</i> be the reduced Gröbner basis of the ideal <i>I</i> := ⟨<i>A, B</i>⟩ generated by <i>A</i> and <i>B</i> with respect to the usual degree lexicographic order. Assuming <i>A</i> and <i>B</i> sufficiently generic, <i>G</i> admits a so-called <i>concise representation</i> that helps computing normal forms more efficiently [7]. Actually, given this concise representation, a polynomial <i>P</i> ∈ K[<i>X, Y</i>] can be reduced modulo <i>G</i> with quasi-optimal complexity (in terms of the size of the input <i>A, B, P</i>). Moreover, the concise representation can be computed from the input <i>A, B</i> with quasi-optimal complexity as well. The present paper reports on an efficient implementation for these two tasks in the free software Mathemagix [10]. This implementation is included in Mathemagix as a library called Larrix.","PeriodicalId":7093,"journal":{"name":"ACM Commun. Comput. Algebra","volume":"530 1","pages":"41-44"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Computing generic bivariate Gröbner bases with Mathemagix\",\"authors\":\"Robin Larrieu\",\"doi\":\"10.1145/3371991.3371994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Let <i>A, B</i> ∈ K[<i>X,Y</i>] be two bivariate polynomials over an effective field K, and let <i>G</i> be the reduced Gröbner basis of the ideal <i>I</i> := ⟨<i>A, B</i>⟩ generated by <i>A</i> and <i>B</i> with respect to the usual degree lexicographic order. Assuming <i>A</i> and <i>B</i> sufficiently generic, <i>G</i> admits a so-called <i>concise representation</i> that helps computing normal forms more efficiently [7]. Actually, given this concise representation, a polynomial <i>P</i> ∈ K[<i>X, Y</i>] can be reduced modulo <i>G</i> with quasi-optimal complexity (in terms of the size of the input <i>A, B, P</i>). Moreover, the concise representation can be computed from the input <i>A, B</i> with quasi-optimal complexity as well. The present paper reports on an efficient implementation for these two tasks in the free software Mathemagix [10]. This implementation is included in Mathemagix as a library called Larrix.\",\"PeriodicalId\":7093,\"journal\":{\"name\":\"ACM Commun. Comput. Algebra\",\"volume\":\"530 1\",\"pages\":\"41-44\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Commun. Comput. Algebra\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3371991.3371994\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Commun. Comput. Algebra","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3371991.3371994","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computing generic bivariate Gröbner bases with Mathemagix
Let A, B ∈ K[X,Y] be two bivariate polynomials over an effective field K, and let G be the reduced Gröbner basis of the ideal I := ⟨A, B⟩ generated by A and B with respect to the usual degree lexicographic order. Assuming A and B sufficiently generic, G admits a so-called concise representation that helps computing normal forms more efficiently [7]. Actually, given this concise representation, a polynomial P ∈ K[X, Y] can be reduced modulo G with quasi-optimal complexity (in terms of the size of the input A, B, P). Moreover, the concise representation can be computed from the input A, B with quasi-optimal complexity as well. The present paper reports on an efficient implementation for these two tasks in the free software Mathemagix [10]. This implementation is included in Mathemagix as a library called Larrix.