Hypernuclear cluster states of $_\Lambda^{12}\rm{B}$ Unveiled through Neural Network-Driven Microscopic Calculation
Abstract
We investigate the hypernuclear cluster states of using a neural-network-driven microscopic model. We extend the Control Neural Networks (Ctrl.NN) method and systematically calculate the positive-parity spectrum of . By incorporating -shell excitations and parity-coupling effects into the hypernuclear system, we reveal structural changes, including clustering effects and new configurations such as isosceles-triangle and -- linear-chain structures. Furthermore, by comparing with experimental data, we identify that many peaks (6 and 8) can be interpreted as dominant states, which is consistent with shell-model predictions. Notably, based on our analysis of the excited states of , we propose possible candidates for previously unexplained or controversial experimental peaks.
Keywords
Cite
@article{arxiv.2502.15450,
title = {Hypernuclear cluster states of $_\Lambda^{12}\rm{B}$ Unveiled through Neural Network-Driven Microscopic Calculation},
author = {Jiaqi Tian and Mengjiao Lyu and Zheng Cheng and Masahiro Isaka and Akinobu Dote and Takayuki Myo and Hisashi Horiuchi and Hiroki Takemoto and Niu Wan and Qing Zhao},
journal= {arXiv preprint arXiv:2502.15450},
year = {2025}
}
Comments
8 pages, 3 figures, 1 table