Gamma ray full spectral analysis method optimization of an ill-conditioned problem
Department of Nuclear Science and Technology, College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China
2 School of Nuclear Science and Technology, Lanzhou University, 730000, Lanzhou, China
3 School of Physical Science and Technology, Lanzhou University, 730000, Lanzhou, China
Accepted: 25 July 2022
Published online: 16 August 2022
In gamma ray full spectral analysis, the risk that the covariance matrix is ill-conditioned is high, especially in prompt gamma ray neutron activation analysis technology. The ill-conditioned matrix increases the sensitivity of the system to errors. To address this issue, this study offered an optimization approach that involved adding minor disturbances to the covariance matrix and determining the value of the disturbances using the particle swarm optimization algorithm. After optimization, the datasets from two verification experiments became more stable.
© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.