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arXiv · 2504.04449

Non-negligible influence of shape inheritance and staggering on {\alpha} decay

Ruixiong Li·Jingyu Xiao·Hongfei Zhang·Nana Ma
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Abstract

A series of findings in machine learning (ML) and decay theory are captured while exploring the role of deformation and preformation factors in {\alpha} decay. We provide a novel and practical paradigm for developing physics-driven machine learning in nuclear physics research by introducing known decay theory and statistical correlation analysis. Furthermore, this analysis verifies the Geiger-Nuttall law, and the relationship between the decay energy and {\alpha} formation amplitude, also releases a signal that nuclei with hexadecapole deformation are more likely to form {\alpha} clusters. In particular, we identify two novel phenomena, shape inheritance, in which the deformation properties are partially transmitted from parent to daughter nuclei; and half-life inversion due to shape staggering of adjacent even-even nuclei. This phenomenon occurs frequently in neutron-deficient nuclei near lead isotopes, which is consistent with shape coexistence in experiments. Surprisingly, it reappeared within the predicted half-life of the 119 and 120 isotope chains in the eighth period of the periodic table. The half-life considering the inversion effect is preferable for the study of new nuclides and shape coexistence in experiments.

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Ruixiong Li, Jingyu Xiao, Hongfei Zhang, Nana Ma. 2025-04-06. Non-negligible influence of shape inheritance and staggering on {\alpha} decay. https://arxiv.org/abs/2504.04449

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