Metaphotonics gains intelligence

Advances in the field of artificial intelligence resulted in incorporation of these technologies into the process of scientific research and in the field of photonics. Such methods as machine learning and deep learning have become popular design tools for development of photonic devices. Design in this case implies prediction of a physical response of a given structure (forward design) as well as the reverse process of finding parameters of a structure required to provide a desired response (inverse design). While design procedures arguably remain the most widespread implementation of machine learning in photonics, novel applications begin to emerge leading to evolvement of a new research area of intelligent photonics.