Figure 2

The effect of edge propensities on the configuration model. Differently from the standard configuration model, here the stubs are not sampled uniformly at random (cf. Fig. 1). Given an out-stub, each in-stub is characterized by a propensity \(\Omega _{ij}\) of being chosen. As a result, the probability of wiring the out-stub \((A,\cdot )\) to the vertex \(D\) is larger than that of \(B\) due to a very large edge propensity \(\Omega _{AD}\), even though vertex \(B\) has three times more in-stubs than vertex \(D\).