Exploring the energy landscapes of soft glassy systems

Soft-glassy systems have been studied for a long time with wide-ranging applications in everyday life. The slow non-equilibrium dynamics, though, restricts the ability to study them computationally or experimentally using conventional tools, particularly at low temperatures or high volume fractions. The properties of low energy states are of particular importance to answering many fundamental questions surrounding the glass transition and in connecting simulation results to experiments. In this study, we present an algorithm to sample the energy landscape and probe low-energy inherent structures(IS) of the conventionally studied Kob-Anderson(KA) glass. Our algorithm is inspired by metadynamics, though rather than biasing on a small number of reaction coordinates, we bias on the system's high-dimensional configuration space. For certain bias dimensions in energy and space, the algorithm samples low energy ISs in a computationally efficient way, as compared to other conventional techniques. We further use algorithm-generated ISs to thermalize and generate equilibrium-like ensembles close to predicted Kauzmann temperatures. Lastly we note that the ISs reveal interesting fractal and low-dimensional characteristics of the underlying energy basins of the KA system.