Neural network adaptive optics for the Multiple Mirror Telescope

The MMT consists of six comounted 1.8 m telescopes from which the light is brought to a combined coherent focus. Atmospheric turbulence spoils the MMT diffraction-limited beam profile, which would otherwise have a central peak of 0.06 arcsec FWHM, at 2 microns wavelength. At this wavelength, the adaptive correction of the tilt and path difference of each telescope beam is sufficient to recover diffraction-limited angular resolution. Computer simulations have shown that these tilts and pistons can be derived by an artificial neural network, given only a simultaneous pair of in-focus and out-of-focus images of a reference star formed at the combined focus of all the array elements. We describe such an adaptive optics system for the MMT, as well as some successful tests of neural network wavefront sensing on images, and initial real-time tests of the adaptive system at the telescope; attention is given to a demonstration of the adaptive stabilization of the mean phase errors between two mirrors which resulted in stable fringes with 0.1 arcsec resolution.