Linearity and contiguity are two parameters devoted to graph encoding. Linearity is a generalisation of contiguity in the sense that every encoding achieving contiguity k induces an encoding achieving linearity k, both encoding having size Θ(k.n), where n is the number of vertices of G. In this paper, we prove that linearity is a strictly more powerful encoding than contiguity, i.e. there exists some graph family such that the linearity is asymptotically negligible in front of the contiguity. We prove this by answering an open question asking for the worst case linearity of a cograph on n vertices: we provide an O(log n/ log log n) upper bound which matches the previously known lower bound.
CITATION STYLE
Crespelle, C., Le, T. N., Perrot, K., & Phan, T. H. D. (2015). Linearity is strictly more powerful than contiguity for encoding graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9214, pp. 212–223). Springer Verlag. https://doi.org/10.1007/978-3-319-21840-3_18
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