06 October 2023
Science Building
America/Chicago timezone
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Comparing the Efficacy of SMS Prediction to That of a More Complex Framework
 
Supersymmetric models provide explanations for the relic abundance of dark matter, resolve the higgs boson hierarchy problem, and predict that gauge couplings will unify at high energies. It also predicts a new particle for each Standard Model (SM) particle. Considering the number of states these models predict, there can be more than 100 free parameters in a supersymmetric theory. To facilitate experimental investigation, these theories are often constrained by allowing only a few masses to vary and assuming new states decay through a single process limiting the predicted particles that can be generated by an event. A relevant example of this is the Simplified Model Spectra (SMS) used in many predictions tested by the Compact Muon Solenoid (CMS) experiment. In this work, we present a study testing the robustness of assumptions made by CMS in producing mass exclusion limits of superpartners using SMS. Using a theoretical framework published in 2020, we computed the expected limits of neutralinos and charginos, and those from the SMS assumptions in order to see how robust the CMS results are with respect to different parameterizations of superpartners’ properties. We elected to focus on a high energy diboson jet plus missing energy search, as it is a distinct final state that is rarely seen in SM interactions. Our data showed that, despite the increased complexity of the model we used, the upper limit was either not significantly changed, or improved by around a factor of two, depending on the values of the mass parameters. This leads us to the conclusion that, at least for parameterization studied here, applying a more complex framework to simulation may not be necessary.
 
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Id: 30
Place: Science Building
Texas Tech University, Physics & Astronomy 

Room: 106
Starting date:
06-Oct-2023   13:00 (America/Chicago)
Duration: 03h00'
Contribution type: Poster
Primary Authors: Prof. WHITBECK, Andrew (Texas Tech University)
LEE, Sung-Won (Texas Tech Univ.)
Dr. HEGDE, Vinay (Texas Tech University)
Mr. GOGATE, Niramay (Texas Tech University)
Mr. SEWELL, Julian (Texas Tech University)
WIBERT, Elizabeth (Texas Tech University)
Presenters: WIBERT, Elizabeth
Material: poster Poster