Bow Metrics and Hyperbolicity
Abstract: A ($\lambda,\mu$)-bow metric was defined in (Dragan & Ducoffe, 2023) as a far reaching generalization of an $\alpha_i$-metric (which is equivalent to a ($0,i$)-bow metric). A graph $G=(V,E)$ is said to satisfy ($\lambda,\mu$)-bow metric if for every four vertices $u,v,w,x$ of $G$ the following holds: if two shortest paths $P(u,w)$ and $P(v,x)$ share a common shortest subpath $P(v,w)$ of length more than $\lambda$ (that is, they overlap by more than $\lambda$), then the distance between $u$ and $x$ is at least $d_G(u,v)+d_G(v,w)+d_G(w,x)-\mu$. ($\lambda,\mu$)-Bow metric can also be considered for all geodesic metric spaces. It was shown by Dragan & Ducoffe that every $\delta$-hyperbolic graph (in fact, every $\delta$-hyperbolic geodesic metric space) satisfies ($\delta, 2\delta$)-bow metric. Thus, ($\lambda,\mu$)-bow metric is a common generalization of hyperbolicity and of $\alpha_i$-metric. In this paper, we investigate an intriguing question whether ($\lambda,\mu$)-bow metric implies hyperbolicity in graphs. Note that, this is not the case for general geodesic metric spaces as Euclidean spaces satisfy ($0,0$)-bow metric whereas they have unbounded hyperbolicity. We conjecture that, in graphs, ($\lambda,\mu$)-bow metric indeed implies hyperbolicity and show that our conjecture is true for several large families of graphs.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.