Experimental phase control of a 100 laser beam array with quasi-reinforcement learning of a neural network in an error reduction loop.

An innovative scheme is proposed for the dynamic phase control of a laser beam array. It is based on a simple neural network included in a phase correction loop that predicts the complex field array from the intensity of the induced scattered pattern through a phase intensity transformer made of a diffuser. A crucial feature is the use of a kind of reinforcement learning approach for the neural network training which takes account of the iterated corrections.

Small footprint phase locking system for a large tiled aperture laser array.

A phase sensing system fitted to the control of coherent laser beam array of large cross section is experimented. It is based on the use of a fiber bundle that collects a weak part of the synthetic wavefront, that scales it down (1/40) and that reshapes it in a more compact arrangement (2D to 1D array). Then, the reconfigured beam array can be analyzed by a small footprint system making the large laser beam array easier to phase-lock.