Abstract
During high event rates, discrimination of neutron and gamma-ray pulses can be challenging because of pulse pileup. In this paper, we develop a novel approach to deal with this problem. In our method, the normalized cross correlation (NCC) is used to characterize the behavior of typical neutron and gamma-ray pulses. The gradient of the NCC curve is shown to provide distinct features that can be used to distinguish neutron from gamma-ray pulses. Principal component analysis (PCA) is employed to extract features from the NCC gradient curve. We have employed the standard PCA approach and a modified PCA version to obtain unique features. The modified PCA method first extracts 20 Kolmogorov-Smirnov points and then computes the principal components of these 20 coefficients. We have exercised the technique on both simulated (for different pileup delays) and measurement data from a CLYC detector (for varying event rates). The modified PCA approach shows more promising results than the standard PCA approach with better figure of merit.
Original language | English (US) |
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Pages (from-to) | 2764-2771 |
Number of pages | 8 |
Journal | IEEE Transactions on Nuclear Science |
Volume | 63 |
Issue number | 6 |
DOIs | |
State | Published - Dec 2016 |
Keywords
- CLYC
- FOM
- KS test
- PCA
- gamma ray
- neutron
- pulse pileup
- pulse shape discrimination
ASJC Scopus subject areas
- Nuclear and High Energy Physics
- Nuclear Energy and Engineering
- Electrical and Electronic Engineering