Speaker
Grigory Rubtsov
(INR RAS)
Description
We report new results on the search for ultra-high energy photons using the Telescope Array Surface Detector (TA SD) array. The method is based on a neural network classifier trained on the photon-induced and proton-induced Monte-Carlo event sets. The classifier is trained on waveform signals at each SD station supplemented with event-level composition-sensitive parameters. The latter parameters such as the curvature of the shower front, area-over-peak, asymmetry of the signal at the upper and lower detector layers lead to an increase of the classification accuracy. The limits on the ultra-high energy photons based on 16 years of TA SD data are presented.
