By using a machine learning algorithm, we present an improved nuclear mass table with a root mean square deviation of less than 200 keV. The model is equipped with statistical error bars in order to compare with available experimental data. We use the resulting model to predict the composition of the outer crust of a neutron star. By means of simple Monte Carlo methods, we propagate the statistical uncertainties of the mass model to the equation of state of the system.

中文翻译：

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核天体物理学的新质量模型：精度超过200 keV

通过使用机器学习算法，我们提出了一种改进的核质量表，其均方根偏差小于200 keV。该模型配备了统计误差线，以便与可用的实验数据进行比较。我们使用所得模型来预测中子星外壳的组成。通过简单的蒙特卡洛方法，我们将质量模型的统计不确定性传播到系统状态方程。