FIG. 3.

Partition results for Gaussian graphs. (a) Performance against different values of variance (σ²) of the Gaussian distribution and zero additive noise ( ${\sigma }_N^2=0$); (b) adjacency matrix; (c) difference between adjacency matrix of original graph versus null model ${\mathbf{A}}_{\mid \mathbf{k}}^{\text{NULL}}$; (d) same for R null model. Top row: 12 vs 8 cluster size; bottom row: 10 vs 10 cluster size. Method Q_A accurately partitions the graph for all values of σ², whereas method Q_B fails for low values of σ².