Dr Astrid de Wijn (SU Fysikum/Kemisk Fysik)
Diffusion can be strongly affected by the appearance of ballistic flights (long jumps) as well as long-lived sticking trajectories (long sticks). Using statistical inference techniques, we investigate the appearance of long jumps and sticks in molecular-dynamics simulations of diffusion in a prototype system, a benzene molecule on a graphite substrate. These techniques are usually reserved for prediction of large rare events, such as earth quakes and strong wind gusts. We find that specific fluctuations in certain, but not all, internal degrees of freedom of the molecule can be linked to the occurrence of either long jumps or sticks. Furthermore, we show that by changing the prevalence of these predictors with an outside influence, the diffusion of the molecule can be controlled. The approach presented is very generic, and can be applied to larger and more complex molecules. Additionally, the predictor variables can be chosen in a general way so as to be accessible in experiments, making the method feasible for control of diffusion in applications. Our results also demonstrate that data-mining techniques can be used to investigate the phase-space structure of high-dimensional nonlinear dynamical systems.