Skip to main content
Log in

Robust Algorithms For Generalized Pham Systems

  • Published:
computational complexity Aims and scope Submit manuscript

Abstract.

We discuss the complexity of robust symbolic algorithms solving a significant class of zero–dimensional square polynomial systems with rational coefficients over the complex numbers, called generalized Pham systems, which represent the class of zero–dimensional homogeneous complete–intersection systems with “no points at infinity”. Our notion of robustness models the behavior of all known universal methods for solving (parametric) polynomial systems avoiding unnecessary branchings and allowing the solution of certain limit problems. We first show that any robust algorithm solving generalized Pham systems has complexity at least polynomial in the Bézout number of the system under consideration. Then we exhibit a robust probabilistic algorithm which solves generalized Pham systems with quadratic complexity in the Bézout number of the input system. The algorithm consists in a series of homotopies deforming the input system into a system which is “easy to solve”, together with a “projection algorithm” which allows to move the solutions of the known instance to the solutions of an arbitrary instance along the parameter space.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ezequiel Dratman.

Additional information

Manuscript received 22 May 2007

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dratman, E., Matera, G. & Waissbein, A. Robust Algorithms For Generalized Pham Systems. comput. complex. 18, 105–154 (2009). https://doi.org/10.1007/s00037-009-0268-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00037-009-0268-2

Keywords.

Subject classification.

Navigation