Optimal contact process on complex networks

Contact processes on complex networks are a recent subject of study in nonequilibrium statistical physics and they are also important to applied fields such as epidemiology and computer and communication networks. A basic issue concerns finding an optimal strategy for spreading. We provide a universal strategy that, when a basic quantity in the contact process dynamics, the contact probability determined by a generic function of its degree W(k), is chosen to be inversely proportional to the node degree, i.e., W(k)similar to k(-1), spreading can be maximized. Computation results on both model and real-world networks verify our theoretical prediction. Our result suggests the determining role played by small-degree nodes in optimizing spreading, in contrast to the intuition that hub nodes are important for spreading dynamics on complex networks.