If a random variable X is easier to simulate than to analyze, one way to estimate its expected value E(X) is to generate n samples that are distributed according to the law of X and take their average. If the samples are independent, then (assuming X has finite variance) the estimate will have typical error O(1/sqrt(n)). But often one can do better by introducing appropriate forms of negative...