Reaction rate weighted multilayer nuclear reaction network

TL;DR

This paper constructs a multilayer nuclear reaction network weighted by reaction rates to analyze nucleosynthesis, revealing temperature-dependent distribution changes and reaction preferences, providing a new big-data approach for stellar nuclear processes.

Contribution

First construction of a multilayer nuclear reaction network weighted by reaction rates based on all thermonuclear reactions in the JINA REACLIB database.

Findings

Reaction rate distribution shifts from unimodal to bimodal with increasing temperature.

Nuclei exhibit different out-going degree distributions at different reaction rate regions.

Reaction preferences change with temperature, favoring certain reactions around the beta stable line.

Abstract

Nuclear reaction rate ($\lambda$) is a significant factor in the process of nucleosynthesis. A multi-layer directed-weighted nuclear reaction network in which the reaction rate as the weight, and neutron, proton, $^4$He and the remainder nuclei as the criterion 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 of 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 the one 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 $(\gamma,p)$ 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 nuclear reaction network at stellar temperatures.