Range closest-pair search in higher dimensions
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Range closest-pair (RCP) search is a range-search variant of the classical closest-pair problem, which aims to store a given set S of points into some space-efficient data structure such that when a query range Q is specified, the closest pair in S ∩ Q can be reported quickly. RCP search has received attention over years, but the primary focus was only on R^2. In this paper, we study RCP search in higher dimensions. We give the first nontrivial RCP data structures for orthogonal, simplex, halfspace, and ball queries in R^d for any constant d. Furthermore, we prove a conditional lower bound for orthogonal RCP search for d ≥ 3.
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