论文标题
逆量子散射的深度学习回归
Deep learning regression for inverse quantum scattering
论文作者
论文摘要
在这项工作中，我们通过深度学习回归研究了量子散射，该回归是通过多层感知器实现的。为了获得潜在参数，提供了分步方法。选择了圆形边界壁电势来体现该方法。提供了有关培训的详细讨论。提出了对嘈杂数据的研究，并观察到神经网络对于预测潜在参数很有用。
In this work we study the inverse quantum scattering via deep learning regression, which is implemented via a Multilayer Perceptron. A step-by-step method is provided in order to obtain the potential parameters. A circular boundary-wall potential was chosen to exemplify the method. Detailed discussion about the training is provided. A investigation with noisy data is presented and it is observed that the neural network is useful to predict the potential parameters.
