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Python-based program for universal nuclear data extraction
Martin, M. S. McDonald, W. Blair, H. Consalvi, P. Garbiso, M. Grover, H. Harget, A. Natzke, C. Leach, Kyle
Martin, M. S.
McDonald, W.
Blair, H.
Consalvi, P.
Garbiso, M.
Grover, H.
Harget, A.
Natzke, C.
Leach, Kyle
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2017-07
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Abstract
Over the past 70 years, nuclear and atomic physics experiments have provided a vast quantity of experimental data. As a result, extraction of this data can be cumbersome and difficult. Although the compilation, evaluation, and digitization of this data over the past several decades has dramatically changed this process, systematic study of nuclear data can still be time consuming. Furthermore, work towards understanding the detailed interactions between the atomic nucleus and its constituent electrons require the combination of several sets of evaluated data. To aide in this, a python-based data extraction tool is currently under development at the Colorado School of Mines to provide the first steps towards performing large-scale predictions of decay modes under extreme conditions using all known experimental data.
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