Fig. 6.2.

Increasing the value of M inAlgorithm 5.2. Plotted are weighted ensemble bins$\mathcal{B}$computed usingAlgorithm 5.2with M = 4, 8, 12, 16. For each value of M, we use 10⁶ iterations of Algorithm 5.2, with α tuned between 10⁵ and 10⁶. Note that with increasing M, additional bins are initially devoted to resolving the energy barrier between the two rightmost superbasins. Since the observable f is the rightmost microbin, this is the most important energy barrier for the bins to resolve. Note that the multiple adjacent small bins for M = 16 correspond to the steepest gradients of $\tilde{K}\tilde{h}$ in the top right of Figure 6.1. All plots have been cropped at x > 0.4.