The two-star model: exact solution in the sparse regime and condensation transition

The $2$-star model is the simplest exponential random graph model that displays complex behavior, such as degeneracy and phase transition. Despite its importance, this model has been solved only in the regime of dense connectivity. In this work we solve the model in the finite connectivity regime, far more prevalent in real world networks. We show that the model undergoes a condensation transition from a liquid to a condensate phase along the critical line corresponding, in the ensemble parameters space, to the Erd\"os-R\'enyi graphs. In the fluid phase the model can produce graphs with a narrow degree statistics, ranging from regular to Erd\"os-R\'enyi graphs, while in the condensed phase, the "excess" degree heterogeneity condenses on a single site with degree $\sim\sqrt{N}$. This shows the unsuitability of the two-star model, in its standard definition, to produce arbitrary finitely connected graphs with degree heterogeneity higher than Erd\"os-R\'enyi graphs and suggests that non-pathological variants of this model may be attained by softening the global constraint on the two-stars, while keeping the number of links hardly constrained.Comment: 20 pages, 3 figure

Extremal Infinite Graph Theory

We survey various aspects of infinite extremal graph theory and prove several new results. The lead role play the parameters connectivity and degree. This includes the end degree. Many open problems are suggested.Comment: 41 pages, 16 figure

Optimal network topologies: Expanders, Cages, Ramanujan graphs, Entangled networks and all that

We report on some recent developments in the search for optimal network topologies. First we review some basic concepts on spectral graph theory, including adjacency and Laplacian matrices, and paying special attention to the topological implications of having large spectral gaps. We also introduce related concepts as ``expanders'', Ramanujan, and Cage graphs. Afterwards, we discuss two different dynamical feautures of networks: synchronizability and flow of random walkers and so that they are optimized if the corresponding Laplacian matrix have a large spectral gap. From this, we show, by developing a numerical optimization algorithm that maximum synchronizability and fast random walk spreading are obtained for a particular type of extremely homogeneous regular networks, with long loops and poor modular structure, that we call entangled networks. These turn out to be related to Ramanujan and Cage graphs. We argue also that these graphs are very good finite-size approximations to Bethe lattices, and provide almost or almost optimal solutions to many other problems as, for instance, searchability in the presence of congestion or performance of neural networks. Finally, we study how these results are modified when studying dynamical processes controlled by a normalized (weighted and directed) dynamics; much more heterogeneous graphs are optimal in this case. Finally, a critical discussion of the limitations and possible extensions of this work is presented.Comment: 17 pages. 11 figures. Small corrections and a new reference. Accepted for pub. in JSTA