Title: Stratification as a general variance reduction method for Markov chain Monte Carlo,
Abstract: The Eigenvector Method for Umbrella Sampling (EMUS) belongs to a popular
class of methods in statistical mechanics which adapt the principle of
stratified survey sampling to the computation of free energies. By theoretical
analysis and numerical experiments, we demonstrate that EMUS is an efficient
general method for computing averages with respect to arbitrary target
distributions. We show that EMUS can be dramatically more efficient than direct
MCMC when the target distribution is multimodal or when the goal is to compute
tail probabilities.