Place: Structural Transitions in Solids: Theory, Simulations, Experiments and Visualization Techniques, Lugano, Switzerland
The dynamical properties of complex systems are often characterized by the existence of several (meta)stable states separated by large free energy barriers. Examples for such complex systems are omnipresent throughout nature varying from conformational changes in biological relevant molecules to phase transitions as well as many chemical reactions. The long time dynamical behavior of these systems is usually determined by transitions between the stable states. However, the sampling of such transition networks is often severely hampered by the high free energy barriers between the states making it unfeasible to use regular molecular dynamics simulations. For the unbiased study of the dynamics, rate constants, and mechanism of such rare events, transition path sampling has proven to be an effective method. However, in case there are multiple states, only one pair of states can be handled simultaneously. Here, we present an efficient extension of the path ensemble that includes trajectories connecting any two arbitrary stable states within the system. Combining this approach with transition interface sampling we directly obtain an expression for the rate constants of all possible transitions. The key issue for an efficient sampling of the path space is a good switching behaviour between different types of trajectories. If some of the transitions are much more likely than others, a biasing approach can be applied to the path ensemble. We find that such a biasing method does indeed improve the sampling in some cases, but not in general. Additionally, the sampling of trajectory space can be enhanced by including a replica exchange algorithm in the multiple state path sampling.