TMVA Study for B′B′ Search

Successfully separating background from signal is vital to finding a small signal amongst a large background in High Energy Physics. This can be very difficult when just using the standard cut-based separation, and computer-modeled multivariate analysis processes can be more efficient and useful. A list of 36 variables pertaining to both background and signal was narrowed down to 9 important variables using TMVA. These 9 variables were then examined for their accuracy when comparing Monte Carlo generated background and 2012 data in control regions. Though more tests should be undertaken, TMVA seems to be more efficient than the previous cut-based selection. TMVA could be a much more efficient and useful tool to differentiate between background and signal than cut-based selection to help with the B′B′ search.