Abstract:
Reinterpretation of the results published by experimental collaborations is vital for theorists to check their own BSM model against the published data. Often, background model used in an analysis has large number of parameters to model the uncertainties. To test the applicability of an analysis to a new BSM model requires dedicated reinterpretation (CheckMATE is one such tool). This means only a few signal hypothesis can be tested, given the limitation on computational resources. To overcome this, the idea of simplified likelihood was proposed. Simplified likelihood uses a reduced set of parameters to model the background contributions. It makes reinterpretation of the CMS experiments relatively easy. In this thesis, a procedure for constructing the simplified likelihood has been presented. Validation of this procedure has been done using toy data provided by the CMS. We also implemented a CMS search for dark matter and shows how this simplified likelihood framework can be used to set exclusions on the model parameters.
