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Exact Symbolic-numeric Computation of Planar Algebraic Curves

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44118

Berberich,  Eric
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44381

Emeliyanenko,  Pavel
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44806

Kobel,  Alexander
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45332

Sagraloff,  Michael
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Zitation

Berberich, E., Emeliyanenko, P., Kobel, A., & Sagraloff, M. (2013). Exact Symbolic-numeric Computation of Planar Algebraic Curves. Theoretical Computer Science, 491, 1-32. doi:10.1016/j.tcs.2013.04.014.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0015-3B58-1
Zusammenfassung
We present a certified and complete algorithm to compute arrangements of real planar algebraic curves. It computes the decomposition of the plane induced by a finite number of algebraic curves in terms of a cylindrical algebraic decomposition. From a high-level perspective, the overall method splits into two main subroutines, namely an algorithm denoted BiSolve to isolate the real solutions of a zero-dimensional bivariate system, and an algorithm denoted GeoTop to compute the topology of a single algebraic curve. Compared to existing approaches based on elimination techniques, we considerably improve the corresponding lifting steps in both subroutines. As a result, generic position of the input system is never assumed, and thus our algorithm never demands for any change of coordinates. In addition, we significantly limit the types of symbolic operations involved, that is, we only use resultant and gcd computations as purely symbolic operations. The latter results are achieved by combining techniques from different fields such as (modular) symbolic computation, numerical analysis and algebraic geometry. We have implemented our algorithms as prototypical contributions to the C++-project CGAL. We exploit graphics hardware to expedite the remaining symbolic computations. We have also compared our implementation with the current reference implementations, that is, LGP and Maple�s Isolate for polynomial system solving, and CGAL�s bivariate algebraic kernel for analyses and arrangement computations of algebraic curves. For various series of challenging instances, our exhaustive experiments show that the new implementations outperform the existing ones.