Analysis of Fluorescence Telescope Data Using Machine Learning Methods

Fluorescence telescopes (FTs) are an important part of all major modern experiments aimed at studying ultra-high energy cosmic rays (UHECRs, E 1 EeV), both the Pierre Auger Observatory [1] and the Telescope Array [2]. FTs register scintillation light emitted from nitrogen molecules in the air excited during the development of extensive air showers (EASs) generated by UHECRs. Measurements are performed in clear moonless nights in the near-UV band. The future cosmic ray observatories are also planned to employ the fluorescence technique, both in ground-based experiments like GCOS [3] and in orbital experiments like K-EUSO [4] or POEMMA [5].