Xabier Cid Vidal and Alberto Martínez Armas

Machine Learning for Long-Lived Particle Searches at CODEX-beta

Titor: Xabier Cid Vidal

Supervisor: Alberto Martínez Armas

The study of Long-Lived Particles (LLPs) constitutes a promising path to find physics beyond the Standard Model. These particles are characterized by having a decay point far from the proton-proton collision point. CODEX-beta, located near LHCb at CERN, is a new detector prototype designed specifically to search for these displaced signatures. In this project, we will develop a Machine Learning algorithm capable of reconstructing trajectories from the detector data and extracting potentially discriminating variables. This approach will help discern between the LLP signal and the Standard Model background, significantly improving the search sensitivity.