In previous sections, we examined the ability of our NN architecture to perform single step LS method mixing on configurations originating from single black-white initial conditions created using the LS method. Each step of NN-driven mixing results in an error in cut-location on the order of 10 -5 (MSE ∼ 10 -10 ) when compared with the LS method (Fig. ). We now turn our attention to the performance of the NN on longer time-horizons produced by the NN's own approximation of the LS method starting from single black-white initial conditions. The required accuracy needed to mix increases with each step due to the accumulation of error in NN cut locations and the normal shrinking of features in the mixing process. The question is if configurations created by NN mixing can be extrapolated by repeated application of the NN. Thus, while in the previous sections we only considered the success of the NN in placing the set of cuts in the next step, here we consider the success of the NN in placing the set of cuts in multiple ongoing steps as errors accumulate.