标题： 机器学习在外核壳模型结果外推至无限基组中的应用 显示英文标题

标题： Machine Learning for Extrapolating No-Core Shell Model Results to Infinite Basis

摘要： 我们利用机器学习将无核壳模型（NCSM）对于6He基态和6Li最低激发态的能量和均方根半径的结果外推到无限模型空间。通过将来自较大模型空间的NCSM结果纳入人工神经网络集合的训练数据集，外推得到的能量和均方根半径逐渐收敛，从而能够对这些可观测量做出准确预测。 显示英文摘要

摘要： We utilize the machine learning to extrapolate to the infinite model space the no-core shell model (NCSM) results for the energies and rms radii of the 6He ground state and 6Li lowest states. The extrapolated energies and rms radii converge as the NCSM results from larger model spaces are included in the training dataset for ensemble of artificial neural networks thus enabling an accurate predictions for these observables.