Computer Science – Symbolic Computation
Scientific paper
2008-03-20
Computer Science
Symbolic Computation
Scientific paper
We have designed a new symbolic-numeric strategy to compute efficiently and accurately floating point Puiseux series defined by a bivariate polynomial over an algebraic number field. In essence, computations modulo a well chosen prime $p$ are used to obtain the exact information required to guide floating point computations. In this paper, we detail the symbolic part of our algorithm: First of all, we study modular reduction of Puiseux series and give a good reduction criterion to ensure that the information required by the numerical part is preserved. To establish our results, we introduce a simple modification of classical Newton polygons, that we call "generic Newton polygons", which happen to be very convenient. Then, we estimate the arithmetic complexity of computing Puiseux series over finite fields and improve known bounds. Finally, we give bit-complexity bounds for deterministic and randomized versions of the symbolic part. The details of the numerical part will be described in a forthcoming paper.
Poteaux Adrien
Rybowicz Marc
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