Speaker
Description
The Model Unspecific Search in CMS (MUSiC) represents an alternative analysis strategy to the wide range of dedicated searched performed with LHC data. Apart from offering a consistent overview of a large portion of the CMS data, the analysis also assists in covering regions not investigated by other analyses. This ensures new phenomena are not overlooked simply because certain sectors of the data have not been considered.
Largely unbiased by BSM theory assumptions, data taken with the CMS experiment are compared to a MC simulation based prediction of the full SM. Hundreds of search channels, so called event classes, are automatically constructed and defined by the composition of final state objects found in each event. A fully automated search algorithm surveys several kinematic distributions in each event class and determines the region which exhibits the strongest deviation between data and SM prediction. Subsequent to a look-elsewhere effect correction, all significance values of the individual event class distributions are aggregated to offer a global overview of the findings.
Following an introduction to the MUSiC strategy, results of the application to lepton-triggered events in data taken at sqrt(s)=8 TeV are presented in this talk. In over 300 different final states good agreement between the measured data and SM MC expectation is found. Sensitivity studies show that the analysis is capable of discovering signatures of specific BSM scenarios or SM processes.
