Göttingen 2025 – scientific programme

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T: Fachverband Teilchenphysik

T 47: Axions/ALPs II

T 47.5: Talk

Wednesday, April 2, 2025, 17:15–17:30, VG 0.110

Optimization of Background Determination Using Machine Learning with ATLAS Forward Proton Detector Data — •Andrei Aiurov, Viktoriia Lysenko, and Andre Sopczak — Czech Technical University in Prague

The neutral Standard Model Higgs boson was discovered in 2012 at CERN with a two-photon signature, 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. The separation of ALP production from unwanted background reactions is crucial. In this analysis, the recorded data is used to determine the background expectation with machine learning algorithms to optimize the search for ALPs.

Keywords: Axion-Like-Particle; machine learning; ATLAS; CERN