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Storage in Computational Geometry

2023/02/23 by Yijie Han, Han, Yijie, Sanjeev Saxena +1
Computer Science · #Computational Geometry (cs.CG) #Computational Geometry and Mesh Generation #Data Management and Algorithms #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Image Processing and 3D Reconstruction

paper · pdf · doi:10.48550/arxiv.2302.11821

openalex publication_date 2023/02/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We show that n real numbers can be stored in a constant number of real numbers such that each original real number can be fetched in O(log n) time. Although our result has implications for many computational geometry problems, we show here, combined with Han's O(n√(log n)) time real number sorting algorithm [3, arXiv:1801.00776], we can improve the complexity of Kirkpatrick's point location algorithm [8] to O(n√(log n)) preprocessing time, a constant number of real numbers for storage and O(log n) point location time. Kirkpatrick's algorithm uses O(nlog n) preprocessing time, O(n) storage and O(log n) point location time. The complexity results in Kirkpatrick's algorithm was the previous best result. Although Lipton and Tarjan's algorithm [10] predates Kirkpatrick's algorithm and has the same complexity, Kirkpatrick's algorithm is simpler and has a better structure. This paper can be viewed as a companion paper of paper [3, arXiv:1801.00776].

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