“…Among them, very recently we have introduced the repository based adaptive umbrella sampling ͑RBAUS͒ method, 27 in which a sampling repository is periodically updated based on the latest simulation data, and the accumulated knowledge and sampling history are then employed to determine whether and how to update the biasing umbrella potential to achieve more uniform sampling for subsequent simulations. In comparison with other adaptive sampling methods, such as adaptive umbrella sampling, 3,[11][12][13][14] the Wang-Landau approach, 15,16 the adaptive biasing force, 17,18,28 nonequilibrium metadynamics, 8,19,20 and self-healing umbrella sampling, 24 a unique and attractive feature of the RBAUS method is that the frequency for updating the biasing potential is not predetermined but depends on the sampling history and is adaptively determined on the fly, which smoothly bridges nonequilibrium and equilibrium simulations. Such an adaptive updating is achieved by employing the following general principle: If the subsequent simulations still explore a previously oversampled region more than a previously undervisited one, the biasing potential needs to be updated, otherwise, no updating.…”