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우주 물질 연구소(국문 홈페이지)

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제목 - 설명
  • Comprehensive Analyses of the Neutrino-Process in the Core-collapsing Supernova

    • 등록일
      2022.03.24
    • 조회수
      133
저자
Heamin Ko, Dukjae Jang, Myung-Ki Cheoun, Motohiko Kusakabe, Hirokazu Sasaki, Xingqun Yao, Toshitaka Kajino, Takehito Hayakawa, Masaomi Ono, Toshihiko Kawano, Grant J Mathews
게시 날짜
2022/3/24
저널
arXiv preprint arXiv:2203.13365
설명
We investigate the effects of the neutrino flavor change by the neutrino self-interaction, the shock effect and the matter effect on the neutrino-process of the core-collapsing supernova (CCSN). For the hydrodynamics, we compare the results of a simple thermal bomb and a specified hydrodynamic model for SN1987A. As a pre-supernova model, we take an updated model adjusted to explain the SN1987A employing recent development of the  reaction rates calculated for nuclei near the stability line . As for the neutrino luminosity, we adopt two different models: equivalent neutrino luminosity and non-equivalent luminosity models. The latter is taken from the synthetic analysis of the CCSN simulation data which compared quantitatively the results obtained by various neutrino transport models. Relevant neutrino-induced reaction rates are calculated by a shell model for light nuclei and a quasi-particle random phase approximation model for heavy nuclei. For each model, we present and discuss abundances of the light nuclei (Li, Be, B and C) and heavy nuclei (Nb, Tc, La and Ta). The light nuclei are known to be sensitive to the Mikheyev-Smirnov-Wolfenstein region around O-Ne-Mg region. Through the detailed analysis of the numerical abundances, we find that neutrino self-interaction becomes a key ingredient in addition to the MSW effect for understanding the neutrino-process and the relevant nuclear abundances. However, the whole results are shown to depend on the adopted neutrino luminosity scheme. Detailed analyses of the nuclear abundances for the two possible neutrino mass hierarchies are also performed …
학술 문서
H Ko, D Jang, MK Cheoun, M Kusakabe, H Sasaki… – arXiv preprint arXiv:2203.13365, 2022
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