Speaker
Nikita Pozdnukhov
(INR RAS)
Description
We report our results on the new technique for searching for photon-induced EAS events at the Carpet-3 experiment. To search for photon-like events, we employ a neural network, trained on Monte-Carlo simulations of the experiment. Both reconstructed EAS parameters and raw detector signal data are being used. On Monte-Carlo simulations our method achieves considerably higher background rejection efficiency than traditional methods, particularly for EAS events with high muon content.
Primary authors
Nikita Pozdnukhov
(INR RAS)
Grigory Rubtsov
(INR RAS)
