Simplex Range Searching Revisited: How to Shave Logs in Multi-Level Data Structures
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We revisit the classic problem of simplex range searching and related problems in computational geometry. We present a collection of new results which improve previous bounds by multiple logarithmic factors that were caused by the use of multi-level data structures. Highlights include the following: ∙ For a set of n points in a constant dimension d, we give data structures with O(n^d) (or slightly better) space that can answer simplex range counting queries in optimal O(log n) time and simplex range reporting queries in optimal O(log n + k) time, where k denotes the output size. For semigroup range searching, we obtain O(log n) query time with O(n^d polylogn) space. Previous data structures with similar space bounds by Matoušek from nearly three decades ago had O(log^d+1n) or O(log^d+1n + k) query time. ∙ For a set of n simplices in a constant dimension d, we give data structures with O(n) space that can answer stabbing counting queries (counting the number of simplices containing a query point) in O(n^1-1/d) time, and stabbing reporting queries in O(n^1-1/d+k) time. Previous data structures had extra log^d n factors in space and query time. ∙ For a set of n (possibly intersecting) line segments in 2D, we give a data structure with O(n) space that can answer ray shooting queries in O(√(n)) time. This improves Wang's recent data structure [SoCG'20] with O(nlog n) space and O(√(n)log n) query time.
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