| NUCLEAR PHYSICS |
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Reaction Rate Weighted Multilayer Nuclear Reaction Network |
| Huan-Ling Liu1,2, Ding-Ding Han3*, Peng Ji4, and Yu-Gang Ma1* |
1Key Laboratory of Nuclear Physics and Ion-beam Application (MOE), Institute of Modern Physics, Fudan University, Shanghai 200433, China
2Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
3School of Information Science and Technology, Fudan University, Shanghai 200433, China
4The Institute of Science and Technology for Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai 200433, China
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| Cite this article: |
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Huan-Ling Liu, Ding-Ding Han, Peng Ji et al 2020 Chin. Phys. Lett. 37 112601 |
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Abstract Nuclear reaction rate $\lambda$ is a significant factor in processes of nucleosyntheses. A multi-layer directed-weighted nuclear reaction network, in which the reaction rate is taken as the weight, and neutron, proton, $^4$He and the remainder nuclei as the criteria for different reaction layers, is for the first time built based on all thermonuclear reactions in the JINA REACLIB database. Our results show that with the increase in the stellar temperature $T_{9}$, the distribution of nuclear reaction rates on the R-layer network demonstrates a transition from unimodal to bimodal distributions. Nuclei on the R-layer in the region of $\lambda = [1,2.5\times10^{1}]$ have a more complicated out-going degree distribution than that in the region of $\lambda = [10^{11},10^{13}]$, and the number of involved nuclei at $T_{9} = 1$ is very different from the one at $T_{9} = 3$. The redundant nuclei in the region of $\lambda = [1, 2.5\times10^{1}]$ at $T_{9} = 3$ prefer $(\gamma,{\rm p})$ and $({\gamma,\alpha})$ reactions to the ones at $T_{9}=1$, which produce nuclei around the $\beta$ stable line. This work offers a novel way to the big-data analysis on the nuclear reaction network at stellar temperatures.
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Received: 05 September 2020
Published: 14 October 2020
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| Fund: Supported by the National Natural Science Foundation of China (Grant Nos. 11890714, 11421505, 11875133, and 11075057), the National Key R$\&$D Program of China (Grant No. 2018YFB2101302), the Key Research Program of Frontier Sciences of the CAS (Grant No. QYZDJ-SSW-SLH002), and the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB34030200). |
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