Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
978195 | Physica A: Statistical Mechanics and its Applications | 2011 | 8 Pages |
A Horizontal Visibility Graph (HVG) is defined in association with an ordered set of non-negative reals. HVGs realize a methodology in the analysis of time series, their degree distribution being a good discriminator between randomness and chaos Luque et al. [B. Luque, L. Lacasa, F. Ballesteros, J. Luque, Horizontal visibility graphs: exact results for random time series, Phys. Rev. E 80 (2009), 046103]. We prove that a graph is an HVG if and only if it is outerplanar and has a Hamilton path. Therefore, an HVG is a noncrossing graph, as defined in algebraic combinatorics Flajolet and Noy [P. Flajolet, M. Noy, Analytic combinatorics of noncrossing configurations, Discrete Math., 204 (1999) 203–229]. Our characterization of HVGs implies a linear time recognition algorithm. Treating ordered sets as words, we characterize subfamilies of HVGs highlighting various connections with combinatorial statistics and introducing the notion of a visible pair. With this technique, we determine asymptotically the average number of edges of HVGs.
► We prove that a graph is an HVG if and only if it is outerplanar and has a Hamilton path. This an exact characterization of HVGs. ► Based on the characterization, we point out that if we are given a graph, we have an efficient algorithm to determine if there is a time series associated to the graph. ► We open a new direction to study HVGs via algebraic combinatorics on words, a well-established area of research.