Stochastic models for heterogeneous relaxation: application to inhomogeneous optical lineshapes

Abstract

Dynamic heterogeneity has often been modeled by assuming that a single-particle observable, fluctuating at a molecular scale, is influenced by its coupling to environmental variables fluctuating on a second, perhaps slower, time scale. Starting from the most simple Gaussian Markov process we model the exchange between `slow' and `fast' environments by treating the fluctuating single-particle variable as a projection from a higher-dimensional Markov process. The moments of the resulting stochastic process are calculated from the corresponding master equations or Langevin equations, depending on the model. The calculations show the importance of the way to treat exchange processes. The resulting stochastic process is non-Markovian for all models. However, the deviations from a Gaussian behavior depend on the details of the models. A comparison of our results with other model treatments and experiments should provide further insight into the concept of dynamic heterogeneity.