DYNAMIC COMPENSATION OF ATMOSPHERIC-TURBULENCE WITH FAR-FIELD OPTIMIZATION

An application of far-field optimization to dynamic compensation of at mospheric turbulence is reported. The new method eliminates the need f or a wave-front sensor, which is required in conventional adaptive-opt ical systems, and utilizes simple measures of the point-spread functio n as figures of merit. Far-field optimization employs the simplex algo rithm to configure a segmented or continuous (rubber) deformable mirro r iteratively to a state that is conjugate to the local atmospheric tu rbulence. We achieve significant adaptive-optics correction with far-f ield optimization in the presence of both static and dynamic Kolmogoro v turbulence. Computer simulations are used to predict the far-field p erformance in terms of the wavelength-dependent turbulence strength, t he spatial resolution of adaptive mirrors, and the speed of drifting t urbulence with respect to the temporal bandwidth of adaptive optics. F ar-field optimization yields better performance with a coarser segment ed 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.