Random interaction study on angular-momentum distribution of nuclear ground state with neural networks

Subjects: Physics >> Nuclear Physics submitted time 2023-11-09

LIU Deng ALAM Noor A XIAO Yue LEI Yang QIN Zhenzhen

Abstract： The neural network model is employed to learn and simulate the ground state spin distribution of the nucleus within a stochastic two-system ensemble (TBRE), while analyzing the input characteristics of the learned model. This represents a typical application of NN models for classification in nuclear physics. It's still challenging to use the neural network with only a single hidden layer to accurately describe each sample in the TBRE. However, the neural network model effectively captures the statistical properties of the ground state spin, potentially due to its ability to learn empirical rule governing spin distributions in TBRE.

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