Into the Square - On the Complexity of Quadratic-Time Solvable Problems.

This paper will analyze several quadratic-time solvable problems, and will classify them into two classes: problems that are solvable in truly subquadratic time (that is, in time $O(n^{2-\epsilon})$ for some $\epsilon>0$) and problems that are not, unless the well known Strong Exponential Time Hypothesis (SETH) is false. In particular, we will prove that some quadratic-time solvable problems are indeed easier than expected. We will provide an algorithm that computes the transitive closure of a directed graph in time $O(mn^{\frac{\omega+1}{4}})$, where $m$ denotes the number of edges in the transitive closure and $\omega$ is the exponent for matrix multiplication. As a side effect, we will prove that our algorithm runs in time $O(n^{\frac{5}{3}})$ if the transitive closure is sparse. The same time bounds hold if we want to check whether a graph is transitive, by replacing m with the number of edges in the graph itself. As far as we know, this is the fastest algorithm for sparse transitive digraph recognition. Finally, we will apply our algorithm to the comparability graph recognition problem (dating back to 1941), obtaining the first truly subquadratic algorithm. The second part of the paper deals with hardness results. Starting from an artificial quadratic-time solvable variation of the k-SAT problem, we will construct a graph of Karp reductions, proving that a truly subquadratic-time algorithm for any of the problems in the graph falsifies SETH. The analyzed problems are the following: computing the subset graph, finding dominating sets, computing the betweenness centrality of a vertex, computing the minimum closeness centrality, and computing the hyperbolicity of a pair of vertices. We will also be able to include in our framework three proofs already appeared in the literature, concerning the graph diameter computation, local alignment of strings and orthogonality of vectors.