JOURNAL ARTICLE
Relativistic chiral nuclear forces: Status and prospects.
Published In: International Journal of Modern Physics E: Nuclear Physics, 2025, v. 34, n. 11. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Lu, Jun-Xu; Xiao, Yang; Liu, Zhi-Wei; Geng, Li-Sheng 3 of 3
Abstract
Understanding nuclear structure, reactions, and the properties of neutron stars from ab initio calculations from the nucleon degrees of freedom has always been a primary goal of nuclear physics, in which the microscopic nuclear force serves as the fundamental input. So far, the Weinberg chiral nuclear force, first proposed by the Nobel laureate Weinberg, has become the de facto standard input for nuclear ab initio studies. However, compared to their nonrelativistic counterparts, relativistic ab initio calculations, which describe better nuclear observables, have only begun. The lack of modern relativistic nucleon–nucleon interactions is an important issue restricting their development. In this work, we briefly review the development and status of the Weinberg chiral nuclear force, as well as its limitations. We further present a concise introduction to the relativistic chiral nuclear force, show its description of the scattering phase shifts and observables such as differential cross-sections, and demonstrate its unique features. Additionally, we show that the relativistic framework could be naturally extended to the anti-nucleon–nucleon interaction. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Modern Physics E: Nuclear Physics. 2025/11, Vol. 34, Issue 11, p1
- Document Type:Literature Review
- Subject Area:Physics
- Publication Date:2025
- ISSN:0218-3013
- DOI:10.1142/S0218301325430074
- Accession Number:189015179
- Copyright Statement:Copyright of International Journal of Modern Physics E: Nuclear Physics 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.)
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