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dc.contributor.authorSchost, Eric
dc.contributor.authorMehrabi, Esmaeil
dc.date.accessioned2023-03-21 19:07:10 (GMT)
dc.date.available2023-03-21 19:07:10 (GMT)
dc.date.issued2016-06
dc.identifier.urihttps://doi.org/10.1016/j.jco.2015.11.009
dc.identifier.urihttp://hdl.handle.net/10012/19221
dc.description.abstractWe give an algorithm for the symbolic solution of polynomial systems in Z[X,Y]. Following previous work with Lebreton, we use a combination of lifting and modular composition techniques, relying in particular on Kedlaya and Umans’ recent quasi-linear time modular composition algorithm. The main contribution in this paper is an adaptation of a deflation algorithm of Lecerf, that allows us to treat singular solutions for essentially the same cost as the regular ones. Altogether, for an input system with degree d and coefficients of bit-size h, we obtain Monte Carlo algorithms that achieve probability of success at least 1-1/2^P, with running time d^{2+e} O~(d^2+dh+dP+P^2) bit operations, for any e>0, where the O~ notation indicates that we omit polylogarithmic factorsen
dc.language.isoenen
dc.publisherElsevieren
dc.relation.ispartofseriesJournal of Complexity;
dc.subjectbivariate systemen
dc.subjectcomplexityen
dc.subjectalgorithmen
dc.titleA softly optimal Monte Carlo algorithm for solving bivariate polynomial systems over the integersen
dc.typeArticleen
dcterms.bibliographicCitationMehrabi, E., & Schost, É. (2016). A softly optimal Monte Carlo Algorithm for solving bivariate polynomial systems over the integers. Journal of Complexity, 34, 78–128. https://doi.org/10.1016/j.jco.2015.11.009en
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2David R. Cheriton School of Computer Scienceen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen


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