Effect of variance reduction techniques on Monte Carlo simulated energy spectra

Variance reduction techniques are applied to a Monte Carlo program in order to reduce the time required to compute a given number of gamma events in the detector. Energy spectra are generated and compared using brute force and two forced detection variance reduction techniques. The spectra demonstrate that the variance reduction does not significantly bias the character of the emerging gamma ray energy spectra. The mean error between the three simulated energy spectra is less than 5%. The agreement between the three spectra allows a level of confidence in the faster Monte Carlo variance reduction calculations that could not be achieved by merely comparing images calculated at the camera surface