A softly optimal Monte Carlo algorithm for solving bivariate polynomial systems over the integers
Abstract
We 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 factors
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Cite this version of the work
Eric Schost, Esmaeil Mehrabi
(2016).
A softly optimal Monte Carlo algorithm for solving bivariate polynomial systems over the integers. UWSpace.
http://hdl.handle.net/10012/19221
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