Non-Parametric Data-Driven Background Modelling using Conditional Probabilities

Understand

Background modelling is one of the main challenges in particle physics data analysis.

• Commonly employed strategies include the use of simulated events of the background processes, and the fitting of parametric background models to the observed data.
• However, reliable simulations are not always available or may be extremely costly to produce.
• As a result, in many cases, uncertainties associated with the accuracy or sample size of the simulation are the limiting factor in the analysis sensitivity.