  Diffusion can be strongly affected by ballistic flights (long jumps) as well
as long-lived sticking trajectories (long sticks). Using statistical inference
techniques in the spirit of Granger causality, 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. We find that
specific fluctuations in certain, but not all, internal degrees of freedom of
the molecule can be linked to either long jumps or sticks. Furthermore, by
changing the prevalence of these predictors with an outside influence, the
diffusion of the molecule can be controlled. The approach presented in this
proof of concept study 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.
