Nuclear masses learned from a probabilistic neural network
Author:
Funder
U.S. Department of Energy
Los Alamos National Laboratory
Laboratory Directed Research and Development
Publisher
American Physical Society (APS)
Link
http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevC.106.014305/fulltext
Reference52 articles.
1. The impact of individual nuclear properties on r-process nucleosynthesis
2. r-process nucleosynthesis: connecting rare-isotope beam facilities with the cosmos
3. Markov Chain Monte Carlo Predictions of Neutron-rich Lanthanide Properties as a Probe of r-process Dynamics
4. Origin of the heaviest elements: The rapid neutron-capture process
5. Phenomenological Nuclear Level Densities using the KTUY05 Nuclear Mass Formula for Applications Off-Stability
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