To discuss the approach developed in this work in detail, it is helpful to begin by introducing how DPA allows the estimation of an FES from unbiased MDgenerated data. Density Peaks Advanced (DPA) is run on a subset of configurations sampled from an MD trajectory. The size of this subset is the limiting factor in the cost of this approach as each point has a local density determined by the distance to its neighbors, so the process depends on constructing a complete distance matrix between all configuration pairs. We, therefore, expect the cost of this approach to scale with the square of the dataset size, as demonstrated in Figure . Because the thermodynamics of the system directs the MD trajectory's sampling, the local density of each configuration is proportional to the relative probability of encountering this configuration. It thus can be directly inverted to the free energy of the configuration using Equation .