distributions. A fixed value for $S^{*}$ for the different cases would create networks with very different connectivities, which makes the comparison very hard. In order to set the thresholds in a compatible way, $S^{*}$ is taken as the minimal value of $S$ for which the networks are fully connected (99.9% of nodes have been considered). The resulting values are $0.02$, $0.06$, $0.11$, $0.16$ and $0.18 \ r_0$ for $N=4-8$, respectively. These values increase in a similar manner as the average value of the distance $S$ (see Fig. \[fig:Sdistrib\]-b). $S^{*}$ lies just above the tails of the pairwise distance distributions. Consequently, only the most similar structures are linked together. Lower values of the cut-off would generate a disconnected network, while values too close to the maximum of the distributions would put links between structures that are not very similar. For the clusterization process the goal is to separate the bulk of the signal from the statistical noise. To this aim, one can look at the population of the clusters obtained, ranked by decreasing size. Typically, the signal is formed by a small number of populated clusters, while the noise is composed of a large number of small clusters which follow an 