Predicting wind-driven turbulence for adaptive optics control

Speaker: Alexander Rudy (UCSC)

Efficient and effective adaptive optics systems will become essential to the
productivity of the next generation of ground-based telescopes. We can build
larger deformable mirrors, and we can advance our wavefront sensing to
reconstruct a 3D model of atmospheric turbulence: adaptive optics in large
telescopes will quickly be limited by the speed at which we can reconstruct
the atmospheric turbulence. This talk will discuss a technique which allows
adaptive optics systems to run slower. Using Fourier analysis, we can
identify correlated turbulent motions in on-sky data. Our telemetry suggests
that frozen-flow turbulence is a dominant source of phase error for adaptive
optics systems. With a Linear-Quadratic-Gaussian-based phase reconstructor
we can remove the effects of these correlated motions from AO systems. We
demonstrate the use of one such predictive controller in a laboratory
environment, with artificial turbulence, and show how such a controller
could be applied to working adaptive optics systems to greatly reduce or
eliminate the temporal bandwidth error, the dominant source of error in most
operating AO systems, and one of the largest remaining sources of error for
large (30-meter class) telescopes.