Deep learning with photosensor timing information as a background rejection method for the Cherenkov Telescope Array
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 t...
Những tác giả chính: | Spencer, ST, Armstrong, T, Watson, J, Mangano, S, Renier, Y, Cotter, G |
---|---|
Định dạng: | Journal article |
Ngôn ngữ: | English |
Được phát hành: |
Elsevier
2021
|
Những quyển sách tương tự
-
Science with the Cherenkov Telescope Array
Bằng: Acharya, B, et al.
Được phát hành: (2019) -
Muons as a tool for background rejection in imaging atmospheric Cherenkov telescope arrays
Bằng: L. Olivera-Nieto, et al.
Được phát hành: (2021-12-01) -
The gamma-ray Cherenkov telescope for the Cherenkov telescope array
Bằng: Tibaldo, L, et al.
Được phát hành: (2017) -
Background rejection using image residuals from large telescopes in imaging atmospheric Cherenkov telescope arrays
Bằng: L. Olivera-Nieto, et al.
Được phát hành: (2022-12-01) -
Background rejection in atmospheric Cherenkov telescopes using recurrent convolutional neural networks
Bằng: R. D. Parsons, et al.
Được phát hành: (2020-05-01)