An Improved Heterogeneous Mean-Field Theory for the Ising Model on Complex Networks**Supported by the National Natural Science Foundation of China under Grant Nos. 11875069, 11405001, and the Key Scientific Research Fund of Anhui Provincial Education Department under Grant No. KJ2019A0781

Abstract

Heterogeneous mean-field theory is commonly used methodology to study dynamical processes on complex networks, such as epidemic spreading and phase transitions in spin models. In this paper, we propose an improved heterogeneous mean-field theory for studying the Ising model on complex networks. Our method shows a more accurate prediction in the critical temperature of the Ising model than the previous heterogeneous mean-field theory. The theoretical results are validated by extensive Monte Carlo simulations in various types of networks.