Speaker
Justin Kerr
(York University (CA))
Description
Magnetic monopoles remain a highly motivated yet experimentally elusive exotic particle. Point-like Dirac monopoles, along with other High-Electric-Charge Objects, could be produced in proton-proton collisions at the Large Hadron Collider and would generate a characteristic highly ionizing signature within the ATLAS detector. Building on a previous Run 2 analysis, I will present plans for a new ATLAS Run 3 search using a machine learning technique incorporating several additional detector-level quantities. Preliminary results suggest that this approach achieves more robust background separation and estimation, maximizing potential for the discovery of magnetic monopoles at the LHC.
| Keyword-1 | Magnetic Monopole |
|---|---|
| Keyword-2 | Machine Learning |
Author
Justin Kerr
(York University (CA))
Co-authors
Ethan Brooks
(York University (CA))
Priyanka Kumari
(York University (CA))
Ting Fung Lee
(York University (CA))
Wendy Taylor
(York University (CA))