title: Variation of critical point of aging transition in a networked oscillators system.
abstract: In this work, we study the variation of critical point in aging transition in a networked system consisting of both active and inactive oscillators. By theoretical analysis and numerical simulations, we show that the critical point of aging transition actually is determined by the (normalized) cross links between active and inactive subpopulations of oscillators. This reveals how specific configuration of active and inactive oscillators in the network can lead to the variation of transition point. In particular, we investigate how different strategies of targeted inactivation influence the transition point based on the theory. Our results theoretically explain why the low-degree nodes are crucial regarding dynamical robustness in such systems.
authors.affiliation: Department of Physics, East China Normal University, Shanghai 200241, People's Republic of China.
authors.forename: Wenwen
authors.initials: W
authors.lastname: Huang
authors.affiliation: Department of Physics, East China Normal University, Shanghai 200241, People's Republic of China.
authors.forename: Xiyun
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Physics, East China Normal University, Shanghai 200241, People's Republic of China.
authors.forename: Xin
authors.initials: X
authors.lastname: Hu
authors.affiliation: Department of Physics, East China Normal University, Shanghai 200241, People's Republic of China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Zou
authors.affiliation: Department of Physics, East China Normal University, Shanghai 200241, People's Republic of China.
authors.forename: Zonghua
authors.initials: Z
authors.lastname: Liu
authors.affiliation: Department of Physics, East China Normal University, Shanghai 200241, People's Republic of China.
authors.forename: Shuguang
authors.initials: S
authors.lastname: Guan
mesh_terms: D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D013997:Time Factors