Multilayer optical thin film design with deep Q learning
An-Qing Jiang, Osamu Yoshie, Liang‐Yao Chen
Abstract
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.
Topics & Concepts
Computer scienceThin filmSet (abstract data type)OptoelectronicsEpoch (astronomy)Nonlinear opticalDispersion (optics)Thin film solar cellMaterials scienceNonlinear systemOpticsPhysicsNanotechnologyStarsProgramming languageComputer visionQuantum mechanicsNeural Networks and Reservoir ComputingOptical Network TechnologiesSemiconductor Quantum Structures and Devices