TAIGA Experiment

The TAIGA experiment uses a hybrid array of detectors, including Imaging Atmospheric Cherenkov Telescopes (IACTs) and a wide-angle timing Cherenkov system (HiSCORE), to study high-energy gamma rays and cosmic rays. Current research focuses on applying deep learning methods, particularly convolutional neural networks (CNNs) and conditional generative adversarial networks (cGANs), to analyze the resulting images and improve the reconstruction of particle energy and arrival direction, surpassing traditional methods like Hillas parameterization. These advancements enhance the accuracy and efficiency of gamma-ray event selection and energy reconstruction, leading to a more precise understanding of high-energy astrophysical phenomena.