Information theory and the optimization of Monte Carlo simulations

We develop a convenient, quantitative measure of the sampling efficiency of equilibrium Monte Carlo algorithms. This measure, based on information theoretic methods, is optimized by indenpendent random sampling. We illustrate present developments with selected numerical examples.