English

Multilevel polynomial partitions and simplified range searching

Data Structures and Algorithms 2015-07-20 v2 Algebraic Geometry

Abstract

The polynomial partitioning method of Guth and Katz [arXiv:1011.4105] has numerous applications in discrete and computational geometry. It partitions a given nn-point set PRdP\subset\mathbb{R}^d using the zero set Z(f)Z(f) of a suitable dd-variate polynomial ff. Applications of this result are often complicated by the problem, what should be done with the points of PP lying within Z(f)Z(f)? A natural approach is to partition these points with another polynomial and continue further in a similar manner. So far it has been pursued with limited success---several authors managed to construct and apply a second partitioning polynomial, but further progress has been prevented by technical obstacles. We provide a polynomial partitioning method with up to dd polynomials in dimension dd, which allows for a complete decomposition of the given point set. We apply it to obtain a new algorithm for the semialgebraic range searching problem. Our algorithm has running time bounds similar to a recent algorithm by Agarwal, Sharir, and the first author [SIAM~J.~Comput. 42(2013) 2039--2062], but it is simpler both conceptually and technically. While this paper has been in preparation, Basu and Sombra, as well as Fox, Pach, Sheffer, Suk, and Zahl, obtained results concerning polynomial partitions which overlap with ours to some extent.

Keywords

Cite

@article{arxiv.1406.3058,
  title  = {Multilevel polynomial partitions and simplified range searching},
  author = {Jiri Matousek and Zuzana Patakova},
  journal= {arXiv preprint arXiv:1406.3058},
  year   = {2015}
}

Comments

19 pages; The proof that the Groebner basis can be effectively computed is stated in more detail

R2 v1 2026-06-22T04:36:31.923Z