JOURNAL ARTICLE

Analysis of astrophysical 26Mg(n,γ)27Mg reaction via the asymptotic normalization coefficient method.

  • Published In: Modern Physics Letters A, 2024, v. 39, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Kilic, A. I. 3 of 3

Abstract

The 2 6 Mg (n , γ) 2 7 Mg reaction plays a crucial role in the process of nucleosynthesis in stars. It occurs primarily in massive stars during their late evolutionary stages or during explosive events like supernovae. This paper focuses on investigating discrepancies in the ANC values of the 2 6 Mg (n , γ) 2 7 Mg reaction by analyzing experimental angular distributions of 2 6 Mg (d , p) 2 7 Mg using the DWBA, ADWA and CDCC methods for both ground and first excited states. We then use a mirror nucleus procedure to extract information on the ANCs of the ground state 2 6 Si (p , γ) 2 7 P reaction. The Hauser–Feshbach formalism of the statistical Compound Nucleus (CN) model was applied in this study to perform a compound-nucleus analysis of the 2 6 Mg (d , p) 2 7 Mg reaction. The 2 6 Mg (d , p) 2 7 Mg reaction has almost fulfilled the condition of peripherality, which is necessary for understanding the magnitude of the direct reaction contribution. ANCs for the 2 7 Mg → 2 6 Mg + n virtual decay system were obtained. Moreover, according to charge symmetry of mirror nuclei, the square of proton ANC for a 2 7 P → 2 6 Si + p is determined and comparison between the values of the presented ANCs. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Modern Physics Letters A. 2024/01, Vol. 39, Issue 2, p1
  • Document Type:Article
  • Subject Area:Astronomy and Astrophysics
  • Publication Date:2024
  • ISSN:0217-7323
  • DOI:10.1142/S0217732323501882
  • Accession Number:175572998
  • Copyright Statement:Copyright of Modern Physics Letters A is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.