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Given a function f from the set [N] to a d-dimensional integer grid, we consider data structures that allow efficient orthogonal range searching queries in the image of f, without explicitly storing it. We show that, if f is of the form [N] → [2w]d for some w = polylog(N) and is computable in constant time, then, for any 0 < α < 1, we can obtain a data structure using Õ(N1-α/3) words of space such that, for a given d-dimensional axis-aligned box B, we can search for some x ∈ [N] such that f (x) ∈ B in time Õ(Nα). This result is obtained simply by combining integer range searching with the Fiat-Naor function inversion scheme, which was already used in data-structure problems previously. We further obtain • data structures for range counting and reporting, predecessor, selection, ranking queries, and combinations thereof, on the set f ([N]), • data structures for preimage size and preimage selection queries for a given value of f, and • data structures for selection and ranking queries on geometric quantities computed from tuples of points in d-space. These results unify and generalize previously known results on 3SUM-indexing and string searching, and are widely applicable as a black box to a variety of problems. In particular, we give a data structure for a generalized version of gapped string indexing, and show how to preprocess a set of points on an integer grid in order to efficiently compute (in sublinear time), for points contained in a given axis-aligned box, their Theil-Sen estimator, the kth largest area triangle, or the induced hyperplane that is the kth furthest from the origin. 

We prove that some exact geometric pattern matching problems reduce in linear time to 𝑘-SUM when the pattern has a fixed size 𝑘. This holds in the real RAM model for searching for a similar copy of a set of 𝑘≥3 points within a set of n points in the plane, and for searching for an affine image of a set of 𝑘≥𝑑+2 points within a set of n points in d-space. As corollaries, we obtain improved real RAM algorithms and decision trees for the two problems. In particular, they can be solved by algebraic decision trees of near-linear height.