Background Estimation for Inclusive SUSY Searches - The Tiles Method

We discuss a new data-driven estimation technique, denoted {em Tiles Method}, for Standard Model (SM) background in inclusive SUSY searches. The Tiles Method translates prior knowledge on the SM distributions of discriminating variables in a two or higher dimensional grid into an estimate of the abundances of SM and beyond-SM events. Depending on the grid granularity, the abundances are calculated by solving a system of linear equations or by minimising a log-likelihood function. The method does not rely on assumptions on background dominance for particular values of the variables, nor does it require iterations. Correlations between the variables are fully taken into account for SM events, while they are assumed to vanish for beyond-SM events. Systematic effects due to uncertainties in the simulated prior distributions are investigated. Results for various mSUGRA scenarios are presented.