Jiang Anqing, Osamu Yoshie, Chen Liangyao
Graduate School of IPS, Waseda University, Fukuoka, Japan.
Department of Optical Science and Engineering, Fudan University, Shanghai, China.
Sci Rep. 2020 Jul 29;10(1):12780. doi: 10.1038/s41598-020-69754-w.
Multilayer optical film plays a significant role in broad fields of optical application. Due to the nonlinear relationship between the dispersion characteristics of optical materials and the actual performance parameters of optical thin films, it is challenging to optimize optical thin film structure with the traditional models. In this paper, we present an implementation of Deep Q-learning, which suited for the most part for optical thin film. As a set of concrete demonstrations, we optimize solar absorber. The optimal program could optimal this solar absorber in 500 epoch (about 200 steps per-epoch) without any human intervention. Search results perform better than researchers' manual searches.
多层光学薄膜在广泛的光学应用领域中发挥着重要作用。由于光学材料的色散特性与光学薄膜的实际性能参数之间存在非线性关系，使用传统模型优化光学薄膜结构具有挑战性。在本文中，我们提出了一种深度Q学习的实现方法，该方法在很大程度上适用于光学薄膜。作为一组具体的示例，我们对太阳能吸收器进行了优化。该优化程序可以在500个轮次（每轮次约200步）内对该太阳能吸收器进行优化，无需任何人工干预。搜索结果比研究人员的手动搜索效果更好。
