http://arxiv.org/abs/2212.02156
Nuclear astrophysics is a multi-disciplinary field with a huge demand for nuclear data. Among its various fields, stellar evolution and nucleosynthesis are clearly the most closely related to nuclear physics. The need for nuclear data for astrophysics applications challenges experimental techniques as well as the robustness and predictive power of present nuclear models. Despite impressive progress for the last years, major problems and puzzles remain. In the present contribution, only a few nuclear astrophysics specific aspects are discussed. These concern some experimental progress related to the measurement of key reactions of relevance for the so-called s-and p-processes of nucleosynthesis, the theoretical effort in predicting nuclear properties of exotic neutron-rich nuclei of interest for the r-process nucleosynthesis, and the recent introduction of machine learning techniques in nuclear astrophysics applications.
S. Goriely, A. Choplin, W. Ryssens, et. al.
Tue, 6 Dec 22
80/87
Comments: 8 pages, 4 figures; Contribution to the proceedings of INPC 2022, Cape Town, South Africa
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