Detail of the student project

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Topic:Pátrání po axionu podobných částicích s využitím strojového učení pro optimalizaci citlivosti k signálu s daty experimentu ATLAS z LHC Run-3
Department:Katedra kybernetiky
Supervisor:doc. Dr. André Sopczak
Announce as:Diplomová práce, Bakalářská práce, Semestrální projekt
Description:The neutral Standard Model Higgs boson was discovered in 2012 at CERN, and the search for further particles of extended models continues. In particular, the search for an Axion-Like-Particle (ALP). An ALP can be produced with a signature of two photons. Using machine learning technology, this analysis addresses the separation of ALP production from unwanted background reactions. There are three analysis levels: generator level, full ATLAS detector simulation, and real recorded data. In this project, the data from the full ATLAS detector simulation shall be used and the performance of the machine learning algorithms be optimized in the search for the ALPs, separating.
Responsible person: Petr Pošík