Information guided noise reduction for Monte Carlo integration of oscillatory functions

A simple procedure for decreasing the statistical error associated with Monte Carlo integration of oscillatory functions is presented. The method uses available information about the integral of a similar oscillatory function to correlate the estimates of the positive and negative components of the integral. Numerical tests show that information guided noise reduction (IGNoR) leads to substantial decrease of the statistical error, allowing meaningful results to be obtained with a fraction of the cost required to attain similar precision from the raw Monte Carlo estimate.