Abstract
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 α 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.
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