# Tight Hardness for Shortest Cycles and Paths in Sparse Graphs

arXiv: https://arxiv.org/abs/1712.08147 · HTML: https://mlsanity.com/paper/1712.08147/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Dec 2017.

## Built on by (most cited first, 1 of 1)

- [Deep Distance Sensitivity Oracles](https://mlsanity.com/paper/2211.02681/) (2022)

## Abstract (arXiv)

Fine-grained reductions have established equivalences between many core problems with tildeO(n3)-time algorithms on n-node weighted graphs, such as Shortest Cycle, All-Pairs Shortest Paths (APSP), Radius, Replacement Paths, Second Shortest Paths, and so on. These problems also have tildeO(mn)-time algorithms on m-edge n-node weighted graphs, and such algorithms have wider applicability. Are these mn bounds optimal when m ll n2? Starting from the hypothesis that the minimum weight (2ℓ+1)-Clique problem in edge weighted graphs requires n2ℓ+1-o(1) time, we prove that for all sparsities of the form m = Theta(n1+1/ℓ), there is no O(n2 + mn1-ε) time algorithm for ε>0 for any of the below problems: Minimum Weight (2ℓ+1)-Cycle in a directed weighted graph, Shortest Cycle in a directed weighted graph, APSP in a directed or undirected weighted graph, Radius (or Eccentricities) in a directed or undirected weighted graph, Wiener index of a directed or undirected weighted graph, Replacement Paths in a directed weighted graph, Second Shortest Path in a directed weighted graph, Betweenness Centrality of a given node in a directed weighted graph. That is, we prove hardness for a variety of sparse graph problems from the hardness of a dense graph problem. Our results also lead to new conditional lower bounds from several related hypothesis for unweighted sparse graph problems including k-cycle, shortest cycle, Radius, Wiener index and APSP.