  Our ability to control a whole network can be achieved via a small set of
driver nodes. While the minimum number of driver nodes needed for control is
fixed in a given network, there are multiple choices for the driver node set. A
quantity used to investigate this multiplicity is the fraction of redundant
nodes in the network, referring to nodes that do not need any external control.
Previous work has discovered a bimodality feature characterized by a
bifurcation diagram: networks with the same statistical property would stay
with equal probability to have a large or small fraction of redundant nodes.
Here we find that this feature is rooted in the symmetry of the directed
network, where both the degree distribution and the degree correlation can play
a role. The in-in and out-out degree correlation will suppress the bifurcation,
as networks with such degree correlations are asymmetric under network
transpose. The out-in and in-out degree correlation do not change the network
symmetry, hence the bimodality feature is preserved. However, the out-in degree
correlation will change the critical average degree needed for the bifurcation.
Hence by fixing the average degree of networks and tuning out-in degree
correlation alone, we can observe a similar bifurcation diagram. We conduct
analytical analyses that adequately explain the emergence of bimodality caused
by out-in degree correlation. We also propose a quantity, taking both degree
distribution and degree correlation into consideration, to predict if a network
would be at the upper or lower branch of the bifurcation. As is well known that
most real networks are not neutral, our results extend our understandings of
the controllability of complex networks.
