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arXiv · 2402.11278

Neural network study on nuclear ground-state spin distribution within random interaction ensemble

Deng Liu·Alam Noor A·Zhenzhen Qin·Yang Lei
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Abstract

The distribution of nuclear ground-state spin in the two-body random ensemble (TBRE) is studied by using a general classification neural network (NN) model with the two-body interaction matrix elements as input features and corresponding ground-state spins as labels or output predictions. It seems that quantum many-body system problem exceeds the capability of our optimized neural networks when it comes to accurately predicting the ground-state spin of each sample within the TBRE. However, our neural network model effectively captures the statistical properties of the ground-state spin. This may be attributed to the fact that the neural network (NN) model has learned the empirical regularity of the ground-state spin distribution in TBRE, as discovered by human physicists.

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Deng Liu, Alam Noor A, Zhenzhen Qin, Yang Lei. 2024-02-17. Neural network study on nuclear ground-state spin distribution within random interaction ensemble. https://arxiv.org/abs/2402.11278

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