Visualization of topological landscape in shear-flow dynamics of amorphous solids

A potential energy landscape (PEL) gives rise to diverse non-equilibrium dynamics in complex systems. In this study, we visualize the topological landscape of a steady-state flow under shear deformation in a model metallic glass. We use the "state space network" as the best predictor of state transitions in terms of statistical model selection. The proposed scheme visualizes the underlying PEL regarding transitions associated with irreversible cage-breaking events as the cooperative motion of clusters. By characterizing the topological property of the state space network, we observe characteristics of a small-world network. The proposed scheme has a significant potential to enable the understanding of the underlying mechanisms of glass physics, and is analogous to biological networks.