Development of a Markov chain Monte Carlo imaging algorithm for muon tomography

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Authors
  1. Drouin, P-L.
Corporate Authors
Defence Research and Development Canada, Ottawa Research Centre, Ottawa ON (CAN)
Abstract
The detection of Special Nuclear Material (SNM) represents one of the greatest challenges for radiation and nuclear defence, due to the very low emission of gamma rays and neutrons from Highly Enriched Uranium (HEU). Muon tomography systems constitute a promising avenue for SNM detection. These systems use measurements of muon deflection inside the analysed volume to estimate the scattering density of a set of voxels defined within this volume. In this document, a Bayesian model suitable to be used with a Markov Monte Carlo algorithm is investigated.

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Keywords
muon tomography;special nuclear material detection;Markov chain Monte Carlo;maximum likelihood expectation maximisation;MuSCet
Report Number
DRDC-RDDC-2016-R165 — Scientific Report
Date of publication
01 Sep 2016
Number of Pages
16
DSTKIM No
CA043182
CANDIS No
804477
Format(s):
Electronic Document(PDF)

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