首页|Backflow Transformation for A=3 Nuclei with Artificial Neural Networks

Backflow Transformation for A=3 Nuclei with Artificial Neural Networks

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A novel variational wave function defined as a Jastrow factor multiplying a backflow transformed Slater determinant was developed for A=3 nuclei.The Jastrow factor and backflow transformation were represented by artificial neural networks.With this newly developed wave function,variational Monte Carlo calculations were carried out for3H and3He nuclei starting from a nuclear Hamiltonian based on the leading-order pionless effective field theory.The obtained ground-state energy and charge radii were successfully benchmarked against the results of the highly-accurate hyperspherical-harmonics method.The backflow transformation plays a crucial role in improving the nodal surface of the Slater determinant and,thus,providing accurate ground-state energy.

nuclear many-body problemquantum Monte Carloartificial neural net-workbackflow transformation

YANG Yilong、ZHAO Pengwei

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State Key Laboratory of Nuclear Physics and Technology,School of Physics,Peking University,Beijing 100871,China

National Key R&D Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of China

018YFA04044001207013100111875075119350031197503112141501

2023

10.7538/yzk.2022.youxian.0765

原子能科学技术
中国原子能科学研究院

原子能科学技术

CSTPCDCSCD北大核心
影响因子：0.372
ISSN：1000-6931
年,卷(期)：2023.57(4)
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