4 papers
A Data-Driven Model for -Process Production Patterns
Chen-Qi Li, Yong-Zhong Qian, Axel Gross +1
Using the elemental abundances in 68 metal-poor (MP) stars, we present a data-driven model for -process production patterns covering Sr to U. We show that essentially all the $r…
Propagating Uncertainties from Nuclear Physics to Gamma-rays in Core Collapse Supernovae
Chris L Fryer, Hendrik Schatz, Samuel Jones +18
Nuclear yields are powerful probes of supernova explosions, their engines and their progenitors. In addition, as we improve our understanding of these explosions, we can use nuclea…
Solving Einstein equations using deep learning
Zhi-Han Li, Chen-Qi Li, Long-Gang Pang
Einstein field equations are notoriously challenging to solve due to their complex mathematical form, with few analytical solutions available in the absence of highly symmetric sys…
Deep learning on nuclear mass and decay half-lives
Chen-Qi Li, Chao-Nan Tong, Hong-Jing Du +1
Ab-initio calculations of nuclear masses, the binding energy and the decay half-lives are intractable for heavy nucleus, because of the curse of dimensionality in many body qua…