EPJ Web of Conferences
Volume 66, 2014INPC 2013 – International Nuclear Physics Conference
|Number of page(s)||4|
|Section||Nuclear Physics Based Applications|
|Published online||20 March 2014|
Event based neutron activation spectroscopy and analysis algorithm using MLE and metaheuristics
Département de Physique, de Génie Physique et d’Optique, Université Laval, Québec, G1V 0A6, Québec, Canada
a Barton Wallace: firstname.lastname@example.org
Published online: 20 March 2014
Techniques used in neutron activation analysis are often dependent on the experimental setup. In the context of developing a portable and high efficiency detection array, good energy resolution and half-life discrimination are difficult to obtain with traditional methods  given the logistic and financial constraints. An approach different from that of spectrum addition and standard spectroscopy analysis  was needed. The use of multiple detectors prompts the need for a flexible storage of acquisition data to enable sophisticated post processing of information. Analogously to what is done in heavy ion physics, gamma detection counts are stored as two-dimensional events. This enables post-selection of energies and time frames without the need to modify the experimental setup. This method of storage also permits the use of more complex analysis tools. Given the nature of the problem at hand, a light and efficient analysis code had to be devised. A thorough understanding of the physical and statistical processes  involved was used to create a statistical model. Maximum likelihood estimation was combined with metaheuristics to produce a sophisticated curve-fitting algorithm. Simulated and experimental data were fed into the analysis code prompting positive results in terms of half-life discrimination, peak identification and noise reduction. The code was also adapted to other fields of research such as heavy ion identification of the quasi-target (QT) and quasi-particle (QP). The approach used seems to be able to translate well into other fields of research.
© Owned by the authors, published by EDP Sciences, 2014
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 2.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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