论文标题
通过机器学习的限制系统的交互积分快速评估
Fast evaluation of interaction integrals for confined systems with machine learning
论文作者
论文摘要
相互作用积分的计算是用于处理多体量子系统的瓶颈，这是由于其高数值成本。我们对使用浅神经网络限制在III-V半导体2D结构中的几个电子状态进行配置相互作用计算来计算两电子积分，这些积分可用于一般的各向同性相互作用电位。这种方法允许评估能量水平和可控精度。
The calculation of interaction integrals is a bottleneck for the treatment of many-body quantum systems due to its high numerical cost. We conduct configuration interaction calculations of the few-electron states confined in III-V semiconductor 2D structures using a shallow neural network to calculate the two-electron integrals, that can be used for general isotropic interaction potentials. This approach allows for a speed up of the evaluation of the energy levels and a controllable accuracy.
