54 citations · 125 across the 9 of their papers we have counts for
10 papers
Advancing Nuclear Physics with Machine Learning and Artificial Intelligence
Wanbing He, Qingfeng Li, Yugang Ma +3
Machine learning (ML) and artificial intelligence (AI) are becoming powerful tools in scientific research across various disciplines. In this review, we summarize recent progress i…
Neural-network excited states of nuclei and hypernuclei
Zi-Xiao Zhang, Yi-Long Yang, Xiao-Lu Qian +4
We present the first variational Monte Carlo study of nuclear and hypernuclear excited states within the neural-network quantum states (NQS) framework. We implement both the overla…
Machine learning the single- hypernuclei with neural-network quantum states
Zi-Xiao Zhang, Yi-Long Yang, Wan-Bing He +3
Single- hypernuclei are the most straightforward extension of atomic nuclei. A thorough description of baryonic system beyond first-generation quark sector is indispensable for…
Fudan Multi-purpose Active TArget Time Projection Chamber (fMeta-TPC) for Photonnuclear Reaction Experiments
Huang-Kai Wu, Xi-Yang Wang, Yu-Miao Wang +8
Active Target Time Projection Chambers (AT-TPCs) are state-of-the-art tools in the field of low-energy nuclear physics, particularly suitable for experiments using low-intensity ra…
Machine learning method for C event classification and reconstruction in the active target time-projection chamber
Huangkai Wu, Youjing Wang, Yumiao Wang +8
Active target time projection chambers are important tools in low energy radioactive ion beams or gamma rays related researches. In this work, we present the application of machine…
High energy nuclear physics meets Machine Learning
Wan-Bing He, Yu-Gang Ma, Long-Gang Pang +2
Though being seemingly disparate and with relatively new intersection, high energy nuclear physics and machine learning have already begun to merge and yield interesting results du…
Manipulation of Nuclear Isomers with Lasers: Mechanisms and Prospects
Zhiguo Ma, Changbo Fu, Wanbing He +1
Over one hundred years have passed since the nuclear isomer was first introduced, in analogy with chemical isomers to describe long-lived excited nuclear states. In 1921, Otto Hahn…
Machine-learning-based identification for initial clustering structure in relativistic heavy-ion collisions
Junjie He, Wan-Bing He, Yu-Gang Ma +1
-clustering structure is a significant topic in light nuclei. A Bayesian convolutional neural network (BCNN) is applied to classify initial non-clustered and clustered configura…
Nuclear liquid-gas phase transition with machine learning
Rui Wang, Yu-Gang Ma, R. Wada +4
The machine-learning techniques have shown their capability for studying phase transitions in condensed matter physics. Here, we employ the machine-learning techniques to study the…
Collective flows of O + O collisions with -clustering configurations
Chen-Chen Guo, Wan-Bing He, Yu-Gang Ma
The main purpose of the present paper is to discuss whether or not the collective flows in heavy-ion collision at Fermi energy can be taken as a tool to investigate the cluster con…