Other uni-and bi-directional estimators are based on a Gaussian approximation of the probability distribution. However, these introduce significant errors even with large amounts of sampling, since the underlying work distributions are not always Gaussian, as demonstrated in the recent SAMPL6 SAMPLing challenge. Non-equilibrium switching transition data must be collected from independent and uncorrelated trials in order for the average to converge to the true free energy. This is beneficial, in that switching transitions can be run in parallel and thus deploy extremely well in distributed computing environments. This can reduce the wall-clock time of these calculations relative to the EQ approach, at least when a large number of processors is available.