https://doi.org/10.1140/epja/s10050-025-01564-y
Regular Article - Theoretical Physics
Machine learning based study of collective quadrupole–octupole excitations
School of Physics, Nankai University, 300071, Tianjin, People’s Republic of China
Received:
14
January
2025
Accepted:
7
April
2025
Published online:
28
April
2025
We use the collective quadrupole–octupole model of axial symmetric shapes to study excited states in different Th and Ra isotopes. In this model, we use one of the most commonly used potentials in nuclear physics: Woods–Saxon potential. Extending this model based on the potential suggested is able to describe excited states due to quadrupole–octupole deformations satisfactorily. In this work, the necessary Hamiltonian is diagonalized in suitable bases to yield states of the candidate nuclei. This procedure also necessitates optimization, which is done using machine learning methods for each isotope. The findings and outcomes are carefully examined and contrasted with experimental values.
Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
