Neural network study of the nuclear ground-state spin distribution within a random interaction ensemble  

作　　者：Deng Liu Alam Noor A Zhen-Zhen Qin Yang Lei 

机构地区：[1]School of Mathematics and Physics,Southwest University of Science and Technology,Mianyang 621010,China [2]School of Nuclear Science and Technology,Southwest University of Science and Technology,Mianyang 621010,China

出　　处：《Nuclear Science and Techniques》2024年第3期216-227,共12页核技术（英文）

基　　金：supported by the National Natural Science Foundation of China Youth Fund(12105234)。

摘　　要：The distribution of the nuclear ground-state spin in a two-body random ensemble(TBRE)was studied using a general classification neural network(NN)model with two-body interaction matrix elements as input features and the corresponding ground-state spins as labels or output predictions.The quantum many-body system problem exceeds the capability of our optimized NNs in terms of accurately predicting the ground-state spin of each sample within the TBRE.However,our NN model effectively captured the statistical properties of the ground-state spin because it learned the empirical regularity of the ground-state spin distribution in TBRE,as discovered by physicists.

关 键 词：Neural network Two-body random ensemble Spin distribution of nuclear ground state 

分 类 号：O571[理学—粒子物理与原子核物理] TP183[理学—物理]