Application of Bayes' theorem for pulse shape discrimination

Marleau, Peter; Monterial, Mateusz; Clarke, Shaun; Pozzi, Sara

doi:10.1016/j.nima.2015.06.014

Title: Application of Bayes' theorem for pulse shape discrimination

Journal Article · Sun Jun 14 00:00:00 EDT 2015 · Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment

DOI:https://doi.org/10.1016/j.nima.2015.06.014· OSTI ID:1235311

Marleau, Peter ^[1]; Monterial, Mateusz ^[2]; Clarke, Shaun ^[2]; Pozzi, Sara ^[2]

Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Univ. of Michigan, Ann Arbor, MI (United States)

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.

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Research Organization:: Sandia National Lab. (SNL-CA), Livermore, CA (United States); Univ. of Michigan, Ann Arbor, MI (United States)

Sponsoring Organization:: 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)

Grant/Contract Number:: AC04-94AL85000; NA0002534

OSTI ID:: 1235311

Alternate ID(s):: OSTI ID: 1365791; OSTI ID: 1422673

Report Number(s):: SAND-2015-1190J; 567086

Journal Information:: Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 795, Issue C; ISSN 0168-9002

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 11 works

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References (10)

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Cited By (3)

Extension of the neutron scatter camera sensitivity to the ∼10–200 MeV neutron energy range Cabrera Palmer, B.; Brubaker, E.; Gerling, M. Review of Scientific Instruments, Vol. 90, Issue 5 https://doi.org/10.1063/1.5091715	journal	May 2019
Gaussian mixture models as automated particle classifiers for fast neutron detectors Blair, Brenton; Chen, Cliff; Glenn, Andrew Statistical Analysis and Data Mining: The ASA Data Science Journal, Vol. 12, Issue 6 https://doi.org/10.1002/sam.11432	journal	July 2019
Characterizing Subcritical Assemblies with Time of Flight Fixed by Energy Estimation Distributions Monterial, Mateusz; Marleau, Peter; Pozzi, Sara arXiv https://doi.org/10.48550/arxiv.1801.08126	text	January 2018

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