Artificial neural networks for neutron/γ discrimination in the neutron detectors of NEDA

被引：18

作者：

Fabian, X. ^{[1
]}

Baulieu, G. ^{[1
]}

Ducroux, L. ^{[1
]}

Stezowski, O. ^{[1
]}

Boujrad, A. ^{[2
,3
]}

Clement, E. ^{[2
,3
]}

Coudert, S. ^{[2
,3
]}

de France, G. ^{[2
,3
]}

Erduran, N. ^{[3
,4
]}

Erturk, S. ^{[5
]}

Gonzalez, V. ^{[6
]}

Jaworski, G. ^{[7
]}

Nyberg, J. ^{[8
]}

Ralet, D. ^{[2
,3
]}

Sanchis, E. ^{[6
]}

Wadsworth, R. ^{[9
]}

机构：

[1] Univ Claude Bernard Lyon 1, Univ Lyon, CNRS IN2P3, IP2I Lyon,UMR 5822, F-69622 Villeurbanne, France

[2] CEA DRF, Grand Accelerateur Natl Ions Lourds GANIL, BP 55027, F-14076 Caen 05, France

[3] CNRS IN2P3, BP 55027, F-14076 Caen 05, France

[4] Istanbul Sabahattin Zaim Univ, Fac Engn & Nat Sci, TR-34303 Istanbul, Turkey

[5] Nigde Omer Halisdemir Univ, Dept Phys, TR-51200 Nigde, Turkey

[6] Univ Valencia, Dept Ingn Elect, Valencia, Spain

[7] Univ Warsaw, Heavy Ion Lab, Warsaw, Poland

[8] Uppsala Univ, Dept Phys & Astron, SE-75120 Uppsala, Sweden

[9] Univ York, Dept Phys, York YO10 5DD, N Yorkshire, England

来源：

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT | 2021年 / 986卷

关键词：

gamma-ray spectroscopy; Neutron detector; n-gamma discrimination; Pulse-shape discrimination; Machine learning; Artificial neural networks; GAMMA; CAMPAIGN; DESIGN; WALL;

D O I：

10.1016/j.nima.2020.164750

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

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.

引用

页数：9

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