Work

Statistical mechanics of a coevolving spin system

Year: 2018

Type: article

Abstract: We propose a statistical mechanics approach to a coevolving spin system with an adaptive network of interactions. The dynamics of node states and network connections is driven by both spin configuration and network topology. We consider a Hamiltonian that merges the classical Ising model and the statistical theory of correlated random networks. As a result, we obtain rich phase diagrams with different phase transitions both in the state of nodes and in the graph topology. We argue that the coupling between the spin dynamics and the structure of the network is crucial in understanding the complex behavior of real-world systems and omitting one of the approaches renders the description incomplete.

Source: Physical review. E

DOI: 10.1103/physreve.98.030301

Authors: Tomasz Raducha, Mateusz Wilinski, Tomasz Gubiec, H. Eugene Stanley