scholarly journals High‐Performance Single‐Crystal Diamond Detector for Accurate Pulse Shape Discrimination Based on Self‐Organizing Map Neural Networks

2021 ◽  
Vol 2 (12) ◽  
pp. 2170042
Author(s):  
Guang-Wei Huang ◽  
Zhi-Yuan Li ◽  
Zun-Gang Wang ◽  
Wu-Rui Song ◽  
Kun Wu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Single Crystal ◽  
Pulse Shape ◽  
High Performance ◽  
Pulse Shape Discrimination ◽  
Self Organizing Map ◽  
Shape Discrimination ◽  
Diamond Detector ◽  
Single Crystal Diamond ◽  
Self Organizing

scholarly journals Pulse Shape Discrimination in Impure and Mixed Single-Crystal Organic Scintillators

2011 ◽  
Vol 58 (6) ◽  
pp. 3411-3420 ◽  
Author(s):  
Natalia Zaitseva ◽  
Andrew Glenn ◽  
Leslie Carman ◽  
Robert Hatarik ◽  
Sebastien Hamel ◽  
...  
Keyword(s):  
Single Crystal ◽  
Pulse Shape ◽  
Pulse Shape Discrimination ◽  
Shape Discrimination ◽  
Organic Scintillators

scholarly journals Pulse Shape Discrimination of Neutrons and Gamma Rays Using Kohonen Artificial Neural Networks

2013 ◽  
Vol 3 (2) ◽  
pp. 77-88 ◽  
Author(s):  
Tatiana Tambouratzis ◽  
Dina Chernikova ◽  
Imre Pzsit
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Gamma Rays ◽  
Pulse Shape ◽  
Energy Levels ◽  
Pulse Shape Discrimination ◽  
Shape Discrimination ◽  
Discrimination Ability ◽  
Artificial Neural ◽  
Self Organising Map

Abstract The potential of two Kohonen artificial neural networks I ANNs) - linear vector quantisa - tion (LVQ) and the self organising map (SOM) - is explored for pulse shape discrimination (PSD), i.e. for distinguishing between neutrons (n's) and gamma rays (γ’s). The effect that la) the energy level, and lb) the relative- of the training and lest sets, have on iden- tification accuracy is also evaluated on the given PSD datasel The two Kohonen ANNs demonstrate compfcmentary discrimination ability on the training and test sets: while the LVQ is consistently mote accurate on classifying the training set. the SOM exhibits higher n/γ identification rales when classifying new paltms regardless of the proportion of training and test set patterns at the different energy levels: the average tint: for decision making equals ∼100 /e in the cax of the LVQ and ∼450 μs in the case of the SOM.

Digital liquid-scintillation counting and effective pulse-shape discrimination with artificial neural networks

2015 ◽  
Vol 103 (1) ◽  
pp. 15-25
Author(s):  
Gert Langrock ◽  
Norbert Wiehl ◽  
Hans-Otto Kling ◽  
Matthias Mendel ◽  
Andrea Nähler ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Pulse Shape ◽  
Liquid Scintillation ◽  
Pulse Shape Discrimination ◽  
Shape Discrimination ◽  
Background Count ◽  
High Background ◽  
Pile Up ◽  
Artificial Neural

Abstract A typical problem in low-level liquid scintillation (LS) counting is the identification of α particles in the presence of a high background of β and γ particles. Especially the occurrence of β-β and β-γ pile-ups may prevent the unambiguous identification of an α signal by commonly used analog electronics. In this case, pulse-shape discrimination (PSD) and pile-up rejection (PUR) units show an insufficient performance. This problem was also observed in own earlier experiments on the chemical behaviour of transactinide elements using the liquid-liquid extraction system SISAK in combination with LS counting. α-particle signals from the decay of the transactinides could not be unambiguously assigned. However, the availability of instruments for the digital recording of LS pulses changes the situation and provides possibilities for new approaches in the treatment of LS pulse shapes. In a SISAK experiment performed at PSI, Villigen, a fast transient recorder, a PC card with oscilloscope characteristics and a sampling rate of 1 giga samples s−1 (1 ns per point), was used for the first time to record LS signals. It turned out, that the recorded signals were predominantly α, β-β and β-γ pile up, and fission events. This paper describes the subsequent development and use of artificial neural networks (ANN) based on the method of “back-propagation of errors” to automatically distinguish between different pulse shapes. Such networks can “learn” pulse shapes and classify hitherto unknown pulses correctly after a learning period. The results show that ANN in combination with fast digital recording of pulse shapes can be a powerful tool in LS spectrometry even at high background count rates.

scholarly journals High-Performance 14C Gas-Proportional Counting System Applying Pulse-Shape Discrimination

Radiocarbon ◽  
1992 ◽  
Vol 34 (3) ◽  
pp. 414-419 ◽  
Author(s):  
Osmo Äikää ◽  
Pertti Mäntynen ◽  
Tuovi Kankainen
Keyword(s):  
Count Rate ◽  
Pulse Shape ◽  
High Performance ◽  
Liquid Scintillation ◽  
Pulse Height ◽  
Pulse Shape Discrimination ◽  
Pulse Height Spectrum ◽  
Shape Discrimination ◽  
Counting System ◽  
Faraday Cage

The new 14C dating system of the Geological Survey of Finland consists of three CO2 proportional counters of conventional size, a liquid scintillation anticoincidence guard, and a passive shield of about 90-year-old iron. The counting room is an air-conditioned Faraday cage constructed of concrete with aggregate of crystalline Precambrian limestone. We apply pulse-shape discrimination that greatly improves the precision of our 14C analyses - the reduction of background is over 70%, while the modern count rate is reduced only by 15 to 20%. The purity of the counting gas is monitored by recording the cosmic muon pulse-height spectrum. At present, the dating limit for a two-day measurement is 57 ka. We summarize here the most significant results and aspects of pulse-shape discrimination

Solar Flare Energetic Neutral Emission Measurements in the Project Coronas-I

1994 ◽  
Vol 144 ◽  
pp. 635-639
Author(s):  
J. Baláž ◽  
A. V. Dmitriev ◽  
M. A. Kovalevskaya ◽  
K. Kudela ◽  
S. N. Kuznetsov ◽  
...  
Keyword(s):  
Solar Flare ◽  
Energy Range ◽  
Gamma Rays ◽  
Pulse Shape ◽  
Gamma Ray ◽  
Pulse Shape Discrimination ◽  
Shape Discrimination ◽  
Solar Neutron ◽  
Low Altitude

AbstractThe experiment SONG (SOlar Neutron and Gamma rays) for the low altitude satellite CORONAS-I is described. The instrument is capable to provide gamma-ray line and continuum detection in the energy range 0.1 – 100 MeV as well as detection of neutrons with energies above 30 MeV. As a by-product, the electrons in the range 11 – 108 MeV will be measured too. The pulse shape discrimination technique (PSD) is used.

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