2020/08/12 by Li, Ray
#Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences
paper · doi:10.48550/arxiv.2008.05106
We prove several tight results on the fine-grained complexity of approximating the diameter of a graph. First, we prove that, for any ε>0, assuming the Strong Exponential Time Hypothesis (SETH), there are no near-linear time 2-ε-approximation algorithms for the Diameter of a sparse directed graph, even in unweighted graphs. This result shows that a simple near-linear time 2-approximation algorithm for Diameter is optimal under SETH, answering a question from a survey of Rubinstein and Vassilevska-Williams (SIGACT '19) for the case of directed graphs. In the same survey, Rubinstein and Vassilevska-Williams also asked if it is possible to show that there are no 2-ε approximation algorithms for Diameter in a directed graph in O(n1.499) time. We show that, assuming a hypothesis called NSETH, one cannot use a deterministic SETH-based reduction to rule out the existence of such algorithms. Extending the techniques in these two results, we characterize whether a 2-ε approximation algorithm running in time O(n1+δ) for the Diameter of a sparse directed unweighted graph can be ruled out by a deterministic SETH-based reduction for every δ∈(0,1) and essentially every ε∈(0,1), assuming NSETH. This settles the SETH-hardness of approximating the diameter of sparse directed unweighted graphs for deterministic reductions, up to NSETH. We make the same characterization for randomized SETH-based reductions, assuming another hypothesis called NUNSETH. We prove additional hardness and non-reducibility results for undirected graphs.