Deep learning with photosensor timing information as a background rejection method for the Cherenkov Telescope Array - Spencer, ST; Armstrong, T; Watson, J; Mangano, S; Renier, Y; Cotter, G (Elsevier, 2021)
New deep learning techniques present promising new analysis methods for Imaging Atmospheric Cherenkov Telescopes (IACTs) such as the upcoming Cherenkov Telescope Array (CTA). In particular, the use of Convolutional Neural Networks (CNNs) could provide a direct event classification method that uses the entire information contained within the Cherenkov shower image, bypassing the need to Hillas parameterise the image and allowing fast processing of the data.