中文

A unified classification-quantification framework for bubble-like nuclei within the extended quantum molecular dynamics model

核理论 2026-05-26 v1

摘要

A systematic study of relaxed low-energy cluster configurations for all nuclides listed in the AME2020 database is performed within the extended quantum molecular dynamics (EQMD) framework, with frictional cooling enabling stable relaxation. A unified classification-quantification framework based on the dimensionless parameters BHTUBHTU is established to characterize bubble-like nuclear morphologies. The factor BB, determined from the number of inflection points in the radial density profile, categorizes nuclei into droplet (B=0B=0), bubble (B=1B=1), and toroidal bubble (B=2B=2). The parameter HH defines the degree of central density depletion, while TT and UU characterize the relative surface thickness and the relative size of the internal low-density region, respectively. Light nuclei are predominantly droplet-like with B=0B=0, H=0H=0, T=1T=1, U=0U=0. Most medium-mass nuclei have B=1B=1, consistent with previous studies, especially in the vicinity of 40^{40}Ca and the neutron-rich region, where nuclei show a pronounced central hollowing with large HH and UU values, identifying them as prime candidates for experimental searches for bubble structures. Toroidal bubble nuclei (B=2B=2), emerging for Z25Z\approx25 and prevalent in heavy systems, display a local density minimum at intermediate radius together with a shell-like low-density region. Furthermore, bubble structures are found to be widespread in the superheavy region, in agreement with earlier studies. This parameter scheme not only reveals the morphological richness of nuclei but also establishes a predictive framework for exploring exotic nuclear shapes, thereby opening new avenues for future theoretical and experimental investigations.

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引用

@article{arxiv.2605.24676,
  title  = {A unified classification-quantification framework for bubble-like nuclei within the extended quantum molecular dynamics model},
  author = {Ge Ren and Chun-Wang Ma and Xi-Guang Cao and Kai-Xuan Cheng and Jie Pu},
  journal= {arXiv preprint arXiv:2605.24676},
  year   = {2026}
}