Issue |
EPJ Nuclear Sci. Technol.
Volume 4, 2018
Special Issue on 4th International Workshop on Nuclear Data Covariances, October 2–6, 2017, Aix en Provence, France – CW2017
|
|
---|---|---|
Article Number | 37 | |
Number of page(s) | 6 | |
Section | Covariance Evaluation Methodology | |
DOI | https://doi.org/10.1051/epjn/2018037 | |
Published online | 14 November 2018 |
https://doi.org/10.1051/epjn/2018037
Regular Article
Covariance analysis for total neutron cross sections based on a microscopic optical model potential
China Nuclear Data Center, China Institute of Atomic Energy,
P.O. Box 275(41),
Beijing
102413, P.R. China
* e-mail: xrr-001@163.com
Received:
7
December
2017
Received in final form:
1
March
2018
Accepted:
28
May
2018
Published online: 14 November 2018
The deterministic simple least square (LS) approach is employed in the covariance analysis of the total neutron cross section (n,tot) calculated by a microscopic optical potential, CTOM, which is based on a fundamental theory − Dirac Brueckner Hartree Fock. The sensitivity to the CTOM parameters is firstly systematically calculated for 77 stable nuclei in the range 12C–208Pb within neutron energy 5–200 MeV. Then, an equivalent covariance of experimental data (EVexp) is constructed to describe the experimental data uncertainties and the systematic difference between experimental data and CTOM calculation. The variance and covariance of EVexp matrix are both evaluated via the Gaussian analysis to the ratios of measured (n,tot) cross sections and the CTOM calculations. In addition, a technique named “selection of effective points (SEP)” is suggested additionally to reduce the influence of the Peelle's Pertinent Puzzle problem in this work.
© R. Xu et al., published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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