Adaptive Free-Energy Methods

The histogram reweighting approach has a lot of parameters that have to be optimized in order to generate a reliable $F$: the number of windows, the spring constant for the window potentials, how the windows are spaced, how much sampling in each window, and more. This is often a problem because without knowing something about $F$ it is hard to guess the best set of WHAM parameters. This has led to the development of “adaptive” approaches that aim to overcome this supposed weakness of histogram reweighting.

The two most well-known adaptive biasing approaches are metadynamics [46] and the adaptive-biasing forces (ABF) method [47].