English

Dynamic Unit-Disk Range Reporting

Computational Geometry 2025-01-03 v1 Data Structures and Algorithms

Abstract

For a set PP of nn points in the plane and a value r>0r > 0, the unit-disk range reporting problem is to construct a data structure so that given any query disk of radius rr, all points of PP in the disk can be reported efficiently. We consider the dynamic version of the problem where point insertions and deletions of PP are allowed. The previous best method provides a data structure of O(nlogn)O(n\log n) space that supports O(log3+ϵn)O(\log^{3+\epsilon}n) amortized insertion time, O(log5+ϵn)O(\log^{5+\epsilon}n) amortized deletion time, and O(log2n/loglogn+k)O(\log^2 n/\log\log n+k) query time, where ϵ\epsilon is an arbitrarily small positive constant and kk is the output size. In this paper, we improve the query time to O(logn+k)O(\log n+k) while keeping other complexities the same as before. A key ingredient of our approach is a shallow cutting algorithm for circular arcs, which may be interesting in its own right. A related problem that can also be solved by our techniques is the dynamic unit-disk range emptiness queries: Given a query unit disk, we wish to determine whether the disk contains a point of PP. The best previous work can maintain PP in a data structure of O(n)O(n) space that supports O(log2n)O(\log^2 n) amortized insertion time, O(log4n)O(\log^4n) amortized deletion time, and O(log2n)O(\log^2 n) query time. Our new data structure also uses O(n)O(n) space but can support each update in O(log1+ϵn)O(\log^{1+\epsilon} n) amortized time and support each query in O(logn)O(\log n) time.

Keywords

Cite

@article{arxiv.2501.00120,
  title  = {Dynamic Unit-Disk Range Reporting},
  author = {Haitao Wang and Yiming Zhao},
  journal= {arXiv preprint arXiv:2501.00120},
  year   = {2025}
}

Comments

To appear in STACS 2025