Issue |
A&A
Volume 693, January 2025
|
|
---|---|---|
Article Number | A1 | |
Number of page(s) | 8 | |
Section | Astrophysical processes | |
DOI | https://doi.org/10.1051/0004-6361/202451986 | |
Published online | 23 December 2024 |
Impact of nuclear mass models on r-process nucleosynthesis and heavy element abundances in r-process-enhanced metal-poor stars
1
Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, China
2
Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, Nanning 530004, China
3
Guangxi Key Laboratory of Nuclear Physics and Technology, Department of Physics, Guangxi Normal University, Guilin 541004, China
⋆ Corresponding authors; physcmh@pku.edu.cn, lew@gxu.edu.cn
Received:
26
August
2024
Accepted:
21
November
2024
Because we lack experimental data on extremely neutron-rich nuclei, theoretical values derived from nuclear physics models are essential for the rapid neutron-capture process (r-process). Metal-poor stars enriched by the r-process offer valuable cases for studying the impact of nuclear physics models on r-process nucleosynthesis. This study analyzes four widely used nuclear physics models in detail: the finite-range droplet model, the Hartree-Fock-Bogoliubov, the Duflo-Zuker, and the Weizsäcker-Skyrme model. Theoretical values predicted by the Weizsäcker-Skyrme model are found to agree well with experimental data, and the deviations are significantly smaller than those predicted by other models. The heavy element abundances observed in r-process-enhanced metal-poor stars can be accurately reproduced by r-process nucleosynthesis simulations using the Weizsäcker-Skyrme model, particularly for the rare-earth elements. This suggests that nuclear data provided by a nuclear physics model such as that of Weizsäcker-Skyrme are both essential and crucial for r-process nucleosynthesis studies.
Key words: nuclear reactions / nucleosynthesis / abundances
© The Authors 2024
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://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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