Discrimination of Neutron-Gamma Ray Pulses with Pileup Using Normalized Cross Correlation and Principal Component Analysis

Arindam Dutta, Keith Holbert

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

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 languageEnglish (US)
Pages (from-to)2764-2771
Number of pages8
JournalIEEE Transactions on Nuclear Science
Volume63
Issue number6
DOIs
StatePublished - 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

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