Abstract by Ethan Walker
Network Specialization and Synchronizing Communities
One of the hallmarks of real networks is their ability to perform increasingly complex tasks as their topology evolves. To explain this, it has been observed that as a network grows certain subsets of the network begin to specialize the function(s) they perform. A recent model of network growth based on this notion of specialization has been able to reproduce some of the most well-known topological features found in real-world networks. We find that specialization naturally creates equitable partitions in the topology of the network, which are known to be a necessary condition for synchronization. These resulting communities are nontrivial and predicable. Through specialization we can create, destroy, and maintain communities, and therefore predict network dynamics after network growth. We also find, based on the stability of sub-networks, that after specialization we have synchrony among groups of strongly connected components.