Deep-learning assisted control of Optical Phased Array: a case study

Modern raster scanning techniques and single pixel applications require a precise control of the field profiles radiated by Optical Phased Arrays, which can be controlled by external electrical signals modifying the optical paths inside these devices. In particular for single pixel imaging solutions, it is generally not straightforward to identify the control signals required to generate the desired far field pattern. We propose therefore a Convolutional Neural Network based approach which allows a user to determine the signals required to accurately reproduce an arbitrary far field profile.