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DOE OSTI · 1885949

Automating neutron resonances classification with Machine Learning [Slides]

Nobre, Gustavo P.A.·Brown, D.·Hollick, Sophia·Scoville, Sergey·Rodriguez, Pedro·Fucci, Mary·Crawford, Rose-Marie·Ruiz, Sergio·Coles, A.·Vorabbi, M.
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Abstract

Team reported the following accomplishments: the development of a Machine-Learning method to properly assign spins to neutron resonances (automated, general, reproducible); full integration with evaluated resonances in the Atlas (automation of new editions); training and optimization in synthetic data; validation and deployment to real experimental resonances. Future perspectives include exploration of other classifiers and hyper-parameter combinations, further validation with well-known nucleus (e.g. 235 U), and publication pipeline.

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73 NUCLEAR PHYSICS AND RADIATION PHYSICS97 MATHEMATICS AND COMPUTINGfeature impactmachine learningNuclear Criticality Safety Program (NCSP)nuclear dataresonance spin assignmentsshape analysis

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BibTeXRIS

Nobre, Gustavo P.A., Brown, D., Hollick, Sophia, Scoville, Sergey, Rodriguez, Pedro, Fucci, Mary, Crawford, Rose-Marie, Ruiz, Sergio, Coles, A., Vorabbi, M.. 2022-02-15. Automating neutron resonances classification with Machine Learning [Slides]. https://doi.org/10.2172/1885949

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