Moreover, we conducted a Principal Component Analysis (PCA) of all explored solutions achieved through the use of Swarm-CG. Figure shows the high density regions (i.e., the solutions projected on the first two principal components) that represent the optimal solution obtained from our optimization cycles. The different colors represent the different runs. The contour lines illustrated in Figure represent density isolines, which enable us to identify the regions of higher density points containing a set of optimal water models (according to our scoring function), which are characterized by slightly different set of parameters. These data demonstrate how Swarm-CG brings the model systematically not to a to a specific solution (i.e., to a specific optimal model), but to a region of the space which contains "equally optimal, although slightly different solutions". Interesting questions are, for example, why the method behaves in this way, and specifically why slightly different solutions are "equally optimal".