English

Orthogonal Point Location and Rectangle Stabbing Queries in 3-d

Computational Geometry 2018-05-23 v1 Data Structures and Algorithms

Abstract

In this work, we present a collection of new results on two fundamental problems in geometric data structures: orthogonal point location and rectangle stabbing. -We give the first linear-space data structure that supports 3-d point location queries on nn disjoint axis-aligned boxes with optimal O(logn)O\left( \log n\right) query time in the (arithmetic) pointer machine model. This improves the previous O(log3/2n)O\left( \log^{3/2} n \right) bound of Rahul [SODA 2015]. We similarly obtain the first linear-space data structure in the I/O model with optimal query cost, and also the first linear-space data structure in the word RAM model with sub-logarithmic query time. -We give the first linear-space data structure that supports 3-d 44-sided and 55-sided rectangle stabbing queries in optimal O(logwn+k)O(\log_wn+k) time in the word RAM model. We similarly obtain the first optimal data structure for the closely related problem of 2-d top-kk rectangle stabbing in the word RAM model, and also improved results for 3-d 6-sided rectangle stabbing. For point location, our solution is simpler than previous methods, and is based on an interesting variant of the van Emde Boas recursion, applied in a round-robin fashion over the dimensions, combined with bit-packing techniques. For rectangle stabbing, our solution is a variant of Alstrup, Brodal, and Rauhe's grid-based recursive technique (FOCS 2000), combined with a number of new ideas.

Keywords

Cite

@article{arxiv.1805.08602,
  title  = {Orthogonal Point Location and Rectangle Stabbing Queries in 3-d},
  author = {Timothy M. Chan and Yakov Nekrich and Saladi Rahul and Konstantinos Tsakalidis},
  journal= {arXiv preprint arXiv:1805.08602},
  year   = {2018}
}

Comments

Full version of the ICALP'18 paper