Sampling ensembles of deterministic transition pathways

We extend the method of transition-path sampling to the case of determinist ic dynamics. This method is a Monte Carlo procedure for sampling the ensemb le of trajectories that carry a many-particle system from one set of stable or metastable states to another. It requires no preconceived notions of tr ansition mechanisms or transition states. Rather, it is from the resulting set of suitably weighted dynamical transition paths that one identifies tra nsition mechanisms, determines relevant transition states and calculates tr ansition rate constants. In earlier work, transition-path sampling was cons idered in the context of stochastic dynamics. Here, the necessary modificat ions that make it applicable to deterministic dynamics are discussed and th e modifications illustrated with microcanonical simulations of isomerizatio n events in two-dimensional seven-atom Lennard-Jones clusters.