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

Sayı

Künye