Intuitively, because negative samples from p 0 have high energy, if we reweight the ensemble, they will be assigned smaller (negligible in this example) statistical weight. Therefore, p r , the reweighted distribution, contains fewer (almost none) samples in the negative region. However, if a simulation starts from a negative sample from the surrogate, it would approach the left node of the stationary distribution, following the steep energy gradient, so, intuitively, reweighting should slow down the convergence in this constructed example.