6 papers
Microscopic Calculation of Electric Quadrupole Effective Charges in Exotic Nuclei
Jia Liu, Yong Peng, Xiao-Yan Zhu +4
Electric quadrupole () effective charges are evaluated based on the self-consistent relativistic Hartree-Fock single-particle states, with core-polarization corrections resumme…
Bayesian neural network with autoencoder for model-based description of -particle preformation factor
Xiao-Yan Zhu, Heng-Jian Si-Tu, Hao Zhang +3
decay is an important probe for studying the structure of heavy and superheavy nuclei, in which the -particle preformation () is a key physical quantity for describing…
Correlation between nuclear isospin asymmetry and -particle preformation probability for superheavy nuclei from a Bayesian inference
Xiao-Yan Zhu, Hao Zhang, Wei Gao +3
In the study of decay within the superheavy nuclear region ( and ), the -particle preformation probability serves as a crucial physical quantity…
Centrifugal-corrected harmonic oscillator model for spherical proton emitters
Xiao-Yan Zhu, Wei Gao, Jia Liu +3
In the present work, we propose an improved harmonic oscillator model to systematically evaluate the proton radioactivity half-lives in spherical nuclei, incorporating centrifugal…
Discovering the Gell-Mann-Okubo Formula with Kolmogorov-Arnold Networks
Jian-Yao He, Xun Chen, Xiao-Yan Zhu +1
Uncovering physical laws from experimental data is a fundamental goal of theoretical physics. In this work, we apply the spline-based, interpretable Kolmogorov-Arnold Network (KAN)…
Extracting Transport Properties of Quark-Gluon Plasma from the Heavy-Quark Potential With Neural Networks in a Holographic Model
Wen-Chao Dai, Ou-Yang Luo, Bing Chen +3
Using Kolmogorov-Arnold Networks (KANs), we construct a holographic model informed by lattice QCD data. This neural network approach enables the derivation of an analytical solutio…