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Title: Application of Bayes' theorem for pulse shape discrimination

Abstract

A Bayesian approach is proposed for pulse shape discrimination of photons and neutrons in liquid organic scinitillators. Instead of drawing a decision boundary, each pulse is assigned a photon or neutron confidence probability. This allows for photon and neutron classification on an event-by-event basis. The sum of those confidence probabilities is used to estimate the number of photon and neutron instances in the data. An iterative scheme, similar to an expectation-maximization algorithm for Gaussian mixtures, is used to infer the ratio of photons-to-neutrons in each measurement. Therefore, the probability space adapts to data with varying photon-to-neutron ratios. A time-correlated measurement of Am–Be and separate measurements of 137Cs, 60Co and 232Th photon sources were used to construct libraries of neutrons and photons. These libraries were then used to produce synthetic data sets with varying ratios of photons-to-neutrons. Probability weighted method that we implemented was found to maintain neutron acceptance rate of up to 90% up to photon-to-neutron ratio of 2000, and performed 9% better than the decision boundary approach. Furthermore, the iterative approach appropriately changed the probability space with an increasing number of photons which kept the neutron population estimate from unrealistically increasing.

Authors:
 [1];  [2];  [2];  [2]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Univ. of Michigan, Ann Arbor, MI (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States); Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation; USDOE National Nuclear Security Administration (NNSA), Office of Nonproliferation and Verification Research and Development (NA-22)
OSTI Identifier:
1235311
Alternate Identifier(s):
OSTI ID: 1365791; OSTI ID: 1422673
Report Number(s):
SAND-2015-1190J
Journal ID: ISSN 0168-9002; 567086
Grant/Contract Number:  
AC04-94AL85000; NA0002534
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment
Additional Journal Information:
Journal Volume: 795; Journal Issue: C; Journal ID: ISSN 0168-9002
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; pulse shape discrimination; liquid scintillator; Bayes׳ theorem; expectation-maximization

Citation Formats

Marleau, Peter, Monterial, Mateusz, Clarke, Shaun, and Pozzi, Sara. Application of Bayes' theorem for pulse shape discrimination. United States: N. p., 2015. Web. doi:10.1016/j.nima.2015.06.014.
Marleau, Peter, Monterial, Mateusz, Clarke, Shaun, & Pozzi, Sara. Application of Bayes' theorem for pulse shape discrimination. United States. https://doi.org/10.1016/j.nima.2015.06.014
Marleau, Peter, Monterial, Mateusz, Clarke, Shaun, and Pozzi, Sara. 2015. "Application of Bayes' theorem for pulse shape discrimination". United States. https://doi.org/10.1016/j.nima.2015.06.014. https://www.osti.gov/servlets/purl/1235311.
@article{osti_1235311,
title = {Application of Bayes' theorem for pulse shape discrimination},
author = {Marleau, Peter and Monterial, Mateusz and Clarke, Shaun and Pozzi, Sara},
abstractNote = {A Bayesian approach is proposed for pulse shape discrimination of photons and neutrons in liquid organic scinitillators. Instead of drawing a decision boundary, each pulse is assigned a photon or neutron confidence probability. This allows for photon and neutron classification on an event-by-event basis. The sum of those confidence probabilities is used to estimate the number of photon and neutron instances in the data. An iterative scheme, similar to an expectation-maximization algorithm for Gaussian mixtures, is used to infer the ratio of photons-to-neutrons in each measurement. Therefore, the probability space adapts to data with varying photon-to-neutron ratios. A time-correlated measurement of Am–Be and separate measurements of 137Cs, 60Co and 232Th photon sources were used to construct libraries of neutrons and photons. These libraries were then used to produce synthetic data sets with varying ratios of photons-to-neutrons. Probability weighted method that we implemented was found to maintain neutron acceptance rate of up to 90% up to photon-to-neutron ratio of 2000, and performed 9% better than the decision boundary approach. Furthermore, the iterative approach appropriately changed the probability space with an increasing number of photons which kept the neutron population estimate from unrealistically increasing.},
doi = {10.1016/j.nima.2015.06.014},
url = {https://www.osti.gov/biblio/1235311}, journal = {Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment},
issn = {0168-9002},
number = C,
volume = 795,
place = {United States},
year = {Sun Jun 14 00:00:00 EDT 2015},
month = {Sun Jun 14 00:00:00 EDT 2015}
}

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Cited by: 11 works
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Works referencing / citing this record:

Extension of the neutron scatter camera sensitivity to the ∼10–200 MeV neutron energy range
journal, May 2019


Gaussian mixture models as automated particle classifiers for fast neutron detectors
journal, July 2019