Artificial neural networks for neutron/? discrimination in the neutron detectors of NEDA
Küçük Resim Yok
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Three different Artificial Neural Network architectures have been applied to perform neutron/gamma discrimination in NEDA based on waveform and time-of-flight information. Using the coincident gamma-rays from AGATA, we have been able to measure and compare on real data the performances of the Artificial Neural Networks as classifiers. While the general performances are quite similar for the data set we used, differences, in particular related to the computing times, have been highlighted. One of the Artificial Neural Network architecture has also been found more robust to time misalignment of the waveforms. Such a feature is of great interest for online processing of waveforms.
Açıklama
Anahtar Kelimeler
gamma-ray spectroscopy, Neutron detector, n-gamma discrimination, Pulse-shape discrimination, Machine learning, Artificial neural networks
Kaynak
Nuclear Instruments & Methods in Physics Research Section A-Accelerators Spectrometers Detectors and Associated Equipment
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
986