Real-time adaptive wavefront correction by an artificial neural network at the multiple mirror telescope

Summary form only given. The authors reported the first results from an adaptive system operating online at the Multiple Mirror Telescope (MMT), in which the wavefront is sensed by a neural network, implemented on an array of 20 transputers. Star images were formed at a wavelength of 2.2 mu m by two coherently phased apertures of the MMT, and analyzed by the net. Outputs from the net were used to drive piezoelectric actuators on two segments of an adaptive mirror in the optical beam train, controlling five degrees of freedom of the wavefront. With the servo loop in operation, the corrected image shows significant power at the diffraction limit of 0.1 arcseconds (0.5 mu rad) and a much improved peak intensity.<>