Graduate Program Events |
The physics search targets massive, narrow-width resonances in the 1 to 4.5 TeV mass range that decay to Higgs boson pairs in the b bbar tau+ tau- final state, using proton-proton collision data at sqrt(s) = 13 TeV recorded by the CMS experiment during 2016 to 2018, corresponding to an integrated luminosity of 138 fb^-1. Such resonances are predicted by beyond-the-Standard-Model theories, which aim to address shortcomings in our current understanding of fundamental particles and their interactions.
The analysis targets final states where one Higgs boson decays into a pair of bottom quarks and the other into a pair of tau leptons: X -> HH -> b bbar tau+ tau-. It uses a single large-radius jet to reconstruct the H -> b bbar decay, while the H -> tau+ tau- decay products can either be contained within a single large-radius jet or appear as two isolated tau leptons. The reconstruction and identification of physics objects used in the analysis are enhanced using advanced machine learning techniques, including a graph convolutional neural network for merged b bbar jets and a convolutional neural network for tau+ tau- identification.
The observed data are consistent with Standard Model background expectations. Upper limits at 95% confidence level are set on the production cross section for resonant HH production for masses between 1 and 4.5 TeV. This analysis sets the most sensitive limits to date on X -> HH -> b bbar tau+ tau- decays in the mass range of 1.4 to 4.5 TeV.
The second component of the thesis describes the commissioning and validation of GPU-based reconstruction at the CMS high-level trigger for Run 3 data-taking. To address increasing computational demands arising from higher instantaneous luminosity and increasing event complexity, parallelizable reconstruction algorithms for the hadron calorimeter, electromagnetic calorimeter, and pixel tracker were offloaded to GPUs. Dedicated physics validation was required to ensure that the GPU-offloaded algorithms produce physics results consistent with CPU-based reconstruction within acceptable tolerances. The final trigger configuration seamlessly utilizes GPU hardware when available while maintaining backward compatibility with CPU-only configuration, establishing a foundation for meeting the computational challenges of the high-luminosity LHC era.