TL;DR
This paper explores the computational complexity of multidimensional range update and query problems, establishing hardness results and proposing algorithms for specific variants, advancing understanding in dynamic multidimensional data structures.
Contribution
It introduces the Grid Range class of problems, proves hardness for certain updates, and provides near-optimal algorithms for specific cases, extending multidimensional range query techniques.
Findings
No truly subquadratic algorithms for some update pairs unless popular conjectures are false.
Subquadratic algorithms exist for certain variants with specific geometric properties.
An $ ilde{O}(m^{1.478})$ algorithm for counting 3-paths in sparse graphs.
Abstract
Traditional orthogonal range problems allow queries over a static set of points, each with some value. Dynamic variants allow points to be added or removed, one at a time. To support more powerful updates, we introduce the Grid Range class of data structure problems over integer arrays in one or more dimensions. These problems allow range updates (such as filling all cells in a range with a constant) and queries (such as finding the sum or maximum of values in a range). In this work, we consider these operations along with updates that replace each cell in a range with the minimum, maximum, or sum of its existing value, and a constant. In one dimension, it is known that segment trees can be leveraged to facilitate any of these operations in time overall. Other than a few specific cases, until now, higher dimensional variants have been largely unexplored. We show…
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Videos
Algorithms and Hardness for Multidimensional Range Updates and Queries· youtube
