2021 Student Research Conference:
34th Annual Student Research Conference

Using Machine Learning to Improve Sensitivity in Top-Antitop Resonance Searches with the ATLAS Experiment

Angelina Partenheimer
Dr. Ian Lindevald, Faculty Mentor

Proton-proton collisions resulting in four top quarks may be relevant for probing Beyond-Standard-Model (BSM) physics, and are being studied by the ATLAS experiment at the Large Hadron Collider. While four-top-quark final states are predicted by the Standard Model, they are rare, and therefore difficult to detect. Even though the ATLAS experiment has found evidence of the four-top-quark final state, it still has not achieved the 5σ certainty required to claim observation. Furthermore, in order to distinguish production of a BSM top-antitop heavy resonance, the current analysis would require better resolution of the four-top-quark final state. This talk discusses the feasibility of using machine learning with TensorFlow to improve sensitivity in top-antitop resonance searches.

Keywords: machine learning, particle physics, Large Hadron Collider, ATLAS experiment, top quarks , Beyond-Standard-Model physics


Presentation Type: Face-to-Face Oral Presentation

Session: 102-6
Location: SUB Activities Room
Time: 9:45

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