Within the framework of potential contrasting, the conformations {x p i : i = 1, ..., N } are referred to as data conformations. Besides data conformations, potential contrasting also requires conformations generated from a predefined potential energy function. These conformations and the predefined potential energy function are termed as noise conformations and the noise potential energy function, respectively. The potential contrasting method optimizes the force field parameters θ by learning its contrast with the noise potential energy function using both data and noise conformations. Here we use the potential energy U (x; θ 0 ) with the original force field θ 0 as the noise potential energy function. We generate noise samples {x q i : i = 1, ..., N } by running simulations with the potential energy U (x; θ 0 ). Then we optimizes the force field parameters θ by maximizing the following log-likelihood function: