Properties of Random Graphs via Boltzmann Samplers
Konstantinos D. Panagiotou, Andreas Weißl · Discrete Mathematics & Theoretical Computer Science · 2007
This work is devoted to the understanding of properties of random graphs from graph classes with structural constraints. We propose a method that is based on the analysis of the behaviour of Boltzmann sampler algorithms, and may be used to obtain precise estimates for the maximum degree and maximum size of a biconnected block of a "typical'' member of the class in question. We illustrate how our method works on several graph classes, namely dissections and triangulations of convex polygons, embedded trees, and block and cactus graphs.