  Analysing stationary point databases to extract phenomenological rate
constants can become time-consuming for systems with large potential energy
barriers. In the present contribution we analyse several different approaches
to this problem. First, we show how the original rate constant prescription
within the discrete path sampling approach can be rewritten in terms of
committor probabilities. Two alternative formulations are then derived in which
the steady-state assumption for intervening minima is removed, providing both a
more accurate kinetic analysis, and a measure of whether a two-state
description is appropriate. The first approach involves running additional
short kinetic Monte Carlo (KMC) trajectories, which are used to calculate
waiting times. Here we introduce `leapfrog' moves to second-neighbour minima,
which prevent the KMC trajectory oscillating between structures separated by
low barriers. In the second approach we successively remove minima from the
intervening set, renormalising the branching probabilities and waiting times to
preserve the mean first-passage times of interest. Regrouping the local minima
appropriately is also shown to speed up the kinetic analysis dramatically at
low temperatures. Applications are described where rates are extracted for
databases containing tens of thousands of stationary points, with effective
barriers that are several hundred times kT.
