تقرير
Neural network study on nuclear ground-state spin distribution within random interaction ensemble
| العنوان: | Neural network study on nuclear ground-state spin distribution within random interaction ensemble |
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| المؤلفون: | Liu, Deng, A, Alam Noor, Qin, Zhenzhen, Lei, Yang |
| سنة النشر: | 2024 |
| المجموعة: | Nuclear Theory |
| مصطلحات موضوعية: | Nuclear Theory |
| الوصف: | 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. Comment: 10 pages, 7 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2402.11278 |
| رقم الأكسشن: | edsarx.2402.11278 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |