DYNAMIC COMPENSATION OF ATMOSPHERIC-TURBULENCE WITH FAR-FIELD OPTIMIZATION

An application of far-field optimization to dynamic compensation of atmospheric turbulence is reported. The new method eliminates the need for a wave-front sensor, which is required in conventional adaptive-optical systems, and utilizes simple measures of the point-spread function as figures of merit. Far-field optimization employs the simplex algorithm to configure a segmented or continuous (rubber) deformable mirror iteratively to a state that is conjugate to the local atmospheric turbulence. We achieve significant adaptive-optics correction with far-field optimization in the presence of both static and dynamic Kolmogorov turbulence. Computer simulations are used to predict the far-field performance in terms of the wavelength-dependent turbulence strength, the spatial resolution of adaptive mirrors, and the speed of drifting turbulence with respect to the temporal bandwidth of adaptive optics. Far-field optimization yields better performance with a coarser segmented mirror in the presence of dynamic atmospheric turbulence because of the reduced burden in the optimization process with fewer actuators. There may be a trade-off in terms of efficiency and robustness between segmented adaptive optics and a high-quality deformable mirror.