Deterministic hierarchical networks

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Issue date
2016-05Suggested citation
Barrière, Lali;
Comellas, Francesc;
Dalfó, Cristina;
Fiol, Miguel Angel;
.
(2016)
.
Deterministic hierarchical networks.
Journal of Physics A: Mathematical and Theoretical, vol. 49, núm. 22.
https://doi.org/10.1088/1751-8113/49/22/225202.
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Show full item recordAbstract
It has been shown that many networks associated with complex systems
are small-world (they have both a large local clustering coefficient and a small
diameter) and they are also scale-free (the degrees are distributed according
to a power law). Moreover, these networks are very often hierarchical, as they
describe the modularity of the systems that are modeled. Most of the studies
for complex networks are based on stochastic methods. However, a determin-
istic method, with an exact determination of the main relevant parameters
of the networks, has proven useful. Indeed, this approach complements and
enhances the probabilistic and simulation techniques and, therefore, it pro-
vides a better understanding of the modeled systems. In this paper we nd
the radius, diameter, clustering coefficient and degree distribution of a generic
family of deterministic hierarchical small-world scale-free networks that has
been considered for modeling real-life complex systems.