We study a class of networks generated by sequences of letters taken from a finite alphabet consisting of m letters (corresponding to m types of nodes) and a fixed set of connectivity rules. Recently, it was shown how a binary alphabet might generate threshold nets in a similar fashion. Just like threshold nets, sequence nets in general possess a modular structure reminiscent of everyday-life nets and are easy to handle analytically (i.e., calculate degree distribution, shortest paths, betweenness centrality, etc.). Exploiting symmetry, we make a full classification of two- and three-letter sequence nets, discovering two classes of two-letter sequence nets. These sequence nets retain many of the desirable analytical properties of threshold nets while yielding richer possibilities for the modeling of everyday-life complex networks more faithfully.
|Original language||English (US)|
|Journal||Physical Review E - Statistical, Nonlinear, and Soft Matter Physics|
|State||Published - Aug 8 2008|
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Statistics and Probability
- Condensed Matter Physics