Monochromatic Triangles, Triangle Listing and APSP

TL;DR

This paper explores the relationships between fundamental problems in fine-grained complexity, establishing new reductions and hardness results that connect problems like APSP, 3SUM, and triangle detection, with implications for dynamic algorithms.

Contribution

It proves that the All-Edges Sparse Triangle problem is APSP-hard by reducing Exact Triangle to it, and links the All-Edges Monochromatic Triangle problem to the hardness of APSP and 3SUM hypotheses.

Findings

All-Edges Sparse Triangle is APSP-hard under the APSP hypothesis.

Reducing Exact Triangle to All-Edges Sparse Triangle establishes new hardness results.

If All-Edges Monochromatic Triangle can be solved faster than $O(n^{2.5})$, then APSP and 3SUM are false.

Abstract

One of the main hypotheses in fine-grained complexity is that All-Pairs Shortest Paths (APSP) for $n$-node graphs requires $n^{3-o(1)}$ time. Another famous hypothesis is that the $3$SUM problem for $n$ integers requires $n^{2-o(1)}$ time. Although there are no direct reductions between $3$SUM and APSP, it is known that they are related: there is a problem, $(\min,+)$-convolution that reduces in a fine-grained way to both, and a problem Exact Triangle that both fine-grained reduce to. In this paper we find more relationships between these two problems and other basic problems. P\u{a}tra\c{s}cu had shown that under the $3$SUM hypothesis the All-Edges Sparse Triangle problem in $m$-edge graphs requires $m^{4/3-o(1)}$ time. The latter problem asks to determine for every edge $e$, whether $e$ is in a triangle. It is equivalent to the problem of listing $m$ triangles in an $m$-edge graph where $m=\tilde{O}(n^{1.5})$, and can be solved in $O(m^{1.41})$ time [Alon et al.'97] with the current matrix multiplication bounds, and in $\tilde{O}(m^{4/3})$ time if $\omega=2$. We show that one can reduce Exact Triangle to All-Edges Sparse Triangle, showing that All-Edges Sparse Triangle (and hence Triangle Listing) requires $m^{4/3-o(1)}$ time also assuming the APSP hypothesis. This allows us to provide APSP-hardness for many dynamic problems that were previously known to be hard under the $3$SUM hypothesis. We also consider the previously studied All-Edges Monochromatic Triangle problem. Via work of [Lincoln et al.'20], our result on All-Edges Sparse Triangle implies that if the All-Edges Monochromatic Triangle problem has an $O(n^{2.5-\epsilon})$ time algorithm for $\epsilon>0$, then both the APSP and $3$SUM hypotheses are false. We also connect the problem to other ``intermediate'' problems, whose runtimes are between $O(n^\omega)$ and $O(n^3)$, such as the Max-Min product problem.