On the equivalence of the RTI and SVM approaches to time correlated analysis

Croft, S.; Favalli, A.; Henzlova, D.; Santi, P. A.

doi:10.1016/j.nima.2014.11.064

Title: On the equivalence of the RTI and SVM approaches to time correlated analysis

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Abstract

Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal [1,2]. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in [1] is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in [2]. Mathematically we could also use other numerical ways to extract the time correlated information from the histogram data including for example what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.

Authors:

Croft, S. ^[1]; Favalli, A. ^[2]; Henzlova, D. ^[2]; Santi, P. A. ^[2]

Safe Guard & Security Technology (SST), Oak Ridge, TN (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Publication Date:: Fri Nov 21 00:00:00 EST 2014

Research Org.:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1239269

Alternate Identifier(s):: OSTI ID: 1247606

Report Number(s):: LA-UR-14-28053
Journal ID: ISSN 0168-9002; PII: S0168900214013527

Grant/Contract Number:: NA-22; AC52-06NA25396

Resource Type:: Accepted Manuscript

Journal Name:: Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment

Additional Journal Information:: Journal Volume: 773; Journal Issue: C; Journal ID: ISSN 0168-9002

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; 98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION; 73 NUCLEAR PHYSICS AND RADIATION PHYSICS

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                    Croft, S., Favalli, A., Henzlova, D., and Santi, P. A. On the equivalence of the RTI and SVM approaches to time correlated analysis.  United States: N. p., 2014. 
Web.  doi:10.1016/j.nima.2014.11.064.

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                    Croft, S., Favalli, A., Henzlova, D., & Santi, P. A. On the equivalence of the RTI and SVM approaches to time correlated analysis.  United States.  https://doi.org/10.1016/j.nima.2014.11.064

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                    Croft, S., Favalli, A., Henzlova, D., and Santi, P. A. Fri .  
"On the equivalence of the RTI and SVM approaches to time correlated analysis".  United States.  https://doi.org/10.1016/j.nima.2014.11.064.  https://www.osti.gov/servlets/purl/1239269.

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@article{osti_1239269,

  title        = {On the equivalence of the RTI and SVM approaches to time correlated analysis},

  author       = {Croft, S. and Favalli, A. and Henzlova, D. and Santi, P. A.},

  abstractNote = {Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal [1,2]. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in [1] is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in [2]. Mathematically we could also use other numerical ways to extract the time correlated information from the histogram data including for example what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.},

  doi          = {10.1016/j.nima.2014.11.064},

  journal      = {Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment},

  number       = C,

  volume       = 773,

  place        = {United States},

  year         = {Fri Nov 21 00:00:00 EST 2014},

  month        = {Fri Nov 21 00:00:00 EST 2014}

}

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