Tight Hardness for Shortest Cycles and Paths in Sparse Graphs

Abstract: Fine-grained reductions have established equivalences between many core problems with $\tilde{O}(n<sup>3)$-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 $\tilde{O}(mn)$-time algorithms on $m$-edge $n$-node weighted graphs, and such algorithms have wider applicability. Are these $mn$ bounds optimal when $m \ll n<sup>2$? Starting from the hypothesis that the minimum weight $(2\ell+1)$-Clique problem in edge weighted graphs requires $n<sup>{2\ell+1-o(1)}$ time, we prove that for all sparsities of the form $m = \Theta(n<sup>{1+1/\ell})$, there is no $O(n² + mn<sup>{1-\epsilon})$ time algorithm for $\epsilon&gt;0$ for \emph{any} of the below problems: Minimum Weight $(2\ell+1)$-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.