  Small expectation values are difficult to measure in Monte Carlo calculations
as they tend to get swamped by noise. Recently an algorithm has been proposed
by Luscher and Weisz which allows one to measure expectation values which
previously could not be measured reliably in Monte Carlo simulations. We will
test our implementation of this algorithm by looking at Polyakov loop
correlators and then explore ways of applying it for measuring large Wilson
loops.
