Hao Zhang

collaborators

3 papers

nucl-th2026

Bayesian neural network with autoencoder for model-based description of $α$ -particle preformation factor

Xiao-Yan Zhu, Heng-Jian Si-Tu, Hao Zhang +3

$α$ decay is an important probe for studying the structure of heavy and superheavy nuclei, in which the $α$ -particle preformation ( $P_{α}$ ) is a key physical quantity for describing…

nucl-th2026

Correlation between nuclear isospin asymmetry and $α$ -particle preformation probability for superheavy nuclei from a Bayesian inference

Xiao-Yan Zhu, Hao Zhang, Wei Gao +3

In the study of $α$ decay within the superheavy nuclear region ( $Z \geq 90$ and $N \geq 140$ ), the $α$ -particle preformation probability $P_{α}$ serves as a crucial physical quantity…

gr-qc2024

Gravitational losses for the binary systems induced by the next-to-leading spin-orbit coupling effects

Hao Zhang, Wei Gao, Guansheng He +3

The orbital energy and momentum of the compact binary systems will loss due to gravitational radiation. Based on the mass and mass-current multipole moments of the binary system wi…

Bayesian neural network with autoencoder for model-based description of α-particle preformation factor

Correlation between nuclear isospin asymmetry and α-particle preformation probability for superheavy nuclei from a Bayesian inference

Gravitational losses for the binary systems induced by the next-to-leading spin-orbit coupling effects

Bayesian neural network with autoencoder for model-based description of $α$ -particle preformation factor

Correlation between nuclear isospin asymmetry and $α$ -particle preformation probability for superheavy nuclei from a Bayesian inference