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dc.contributorDallapiccola, Carlo
dc.contributorPeterson, Mark
dc.contributorNordstrom, Kerstin
dc.contributor.advisorDallapiccola, Carlo
dc.contributor.advisorPeterson, Mark
dc.contributor.authorGuhit, Jem
dc.description.abstractThe Large Hadron Collider (LHC) in Geneva, Switzerland has made an astounding discovery in 2012 when it detected a particle mimicking the properties of the Higgs Boson which causes spontaneous electroweak symmetry breaking which gives masses of current known particles. However, the true structure and dynamics of this scalar boson is still unknown. One of the theories suggest the involvement of the newly discovered boson particle in the dark matter sector, which hypothesizes that an analog dark Higgs mechanism breaks the U(1)D dark gauge symmetry. The theory lays the foundation of possible theoretical decay channels of a Higgs Boson to decay to dark charge particles in the dark matter sector that is mediated by a vector boson called the dark photon. The upcoming High Luminosity-LHC (HL-LHC) would significantly extend the sensitivity of these direct searches. This thesis focuses on a predictive study of a specific exotic higgs decay mode for the run 3 of the ATLAS Experiment in the LHC. Using Monte Carlo (MC) simulated data sets of dark photon with mass ranging from 20 and 60 GeV for the signal data and using the previous run 2 dataset for the background data, the efficiency is calculated to solve for the cross section of the signal. Using the built-in statistical methods in ROOT, the 95% Confidence Level (CL) Upper-Limit (UL) of the signal would be calculated and then be converted to a 95% CL Cross-Section UL for run 3.en_US
dc.rightsAttribution-ShareAlike 3.0 United States*
dc.subjectexotic higgs decaysen_US
dc.subjectdata analysisen_US
dc.subjectATLAS Experimenten_US
dc.titleA Predictive Study of Exotic Higgs Decays for the Run 3 of the ATLAS Experimenten_US
mhc.institutionMount Holyoke College

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Attribution-ShareAlike 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-ShareAlike 3.0 United States