Learning-based focusing through scattering media

We present a machine-learning-based method for light focusing through scattering media. In this method, the optical process in a scattering medium is computationally inverted based on a nonlinear regression algorithm with a number of training input-output pairs through the medium, and an input optimized for a target output is calculated. We experimentally demonstrate focusing via a process involving randomness due to a scattering medium and nonlinearity due to double modulation with a spatial light modulator. Our approach realizes model-free control of optical fields, where optical processes or models are unknown.