The analysis of statistical ensembles of networks by means of simulation is an important, possibility to explore networks which emerge by optimization of some 'fitness'-function. In this paper, we compare the situations of the micro-, grand- and canonical ensemble based on their respective partition functions. We present results for a specific, recently introduced Hamiltonian. Interestingly, for all three ensembles we find scale-free networks with 'complex' topology for a wide range of parameters. We further show results of some topological measures depending on energy and temperature. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Biely, C., & Thurner, S. (2006). Simulation of micro-, grand-, and canonical ensembles of complex networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3993 LNCS-III, pp. 1067–1074). Springer Verlag. https://doi.org/10.1007/11758532_146
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