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:
-
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- 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}
}
Web of Science
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Works referencing / citing this record:
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