Year: 2014
Type: preprint
Abstract: The 3SUM conjecture has proven to be a valuable tool for proving conditional lower bounds on dynamic data structures and graph problems. This line of work was initiated by Pǎtraşcu (STOC 2010) who reduced 3SUM to an offline SetDisjointness problem. However, the reduction introduced by Pǎtraşcu suffers from several inefficiencies, making it difficult to obtain tight conditional lower bounds from the 3SUM conjecture. In this paper we address many of the deficiencies of Pǎtraşcu's framework. We give new and efficient reductions from 3SUM to offline SetDisjointness and offline SetIntersection (the reporting version of SetDisjointness) which leads to polynomially higher lower bounds on several problems. Using our reductions, we are able to show the essential optimality of several algorithms, assuming the 3SUM conjecture. - Chiba and Nishizeki's $O(mα)$-time algorithm (SICOMP 1985) for enumerating all triangles in a graph with arboricity/degeneracy $α$ is essentially optimal, for any $α$. - Bjørklund, Pagh, Williams, and Zwick's algorithm (ICALP 2014) for listing $t$ triangles is essentially optimal (assuming the matrix multiplication exponent is $ω=2$). - Any static data structure for SetDisjointness that answers queries in constant time must spend $Ω(N^{2-o(1)})$ time in preprocessing, where $N$ is the size of the set system. These statements were unattainable via Pǎtraşcu's reductions. We also introduce several new reductions from 3SUM to pattern matching problems and dynamic graph problems. Of particular interest are new conditional lower bounds for dynamic versions of Maximum Cardinality Matching, which introduce a new technique for obtaining amortized lower bounds.
Source: arXiv (Cornell University)
Authors: Kopelowitz, Tsvi, Pettie, Seth, Porat, Ely
Institutions: Bar-Ilan University, University of Michigan
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: AF: Small: Locality and Energy in Distributed Computing, AF:Small:Data Structures for Dynamic Networks, G4045262781, AitF:Collaborative Research: Bridging the Gap between Theory and Practice for Matching and Edge Cover Problems, G7979426425, TWC: Small: Collaborative: Cost-Competitve Analysis - A New Tool for Designing Secure Systems, AF: Medium: Collaborative Research: Hardness in Polynomial Time
OpenAlex ID: W4299817332