Turbolinux would like to thank Dr. Igor Mandic from Institute Jozef Stefan for sharing his use of EnFuzion in high energy physics. The background is well reproduced using Monte Carlo simulation data. The researchers also have Monte Carlo data of the signal events, which are the events for which the researcher were searching. For separation of event categories, the researchers use vertex fit probability, probabilities of two different constraint fits, and particle identification. The particle identification provides the possibility of choosing the purity of identification.
Higher purity means lower efficiency.
Similarly, the distributions of vertex and constraint fit probabilities are different for signal and background events. The researchers can also vary the values of the probabilities that are required for accepting an event, which changes the signal and background efficiencies. The problem in this kind of analysis is to choose the actual values at which one cuts because the separation quantities are correlated. In this case, the researchers wanted to maximize the statistical significance of a potential signal. This significance is described by the ratio and are signal and background efficiencies, respectively.