Optimization of random phase diversity for adaptive optics using an LCoS spatial light modulator

Phase retrieval is an attractive approach for sensor-less adaptive optics (AO) because of its relatively simple implementation. Recently, random phase diversity has shown fast convergence for phase retrieval algorithms. In this study, design optimization using random phase diversity is discussed with respect to a sensor-less AO system using a liquid-crystal-on-silicon (LCoS) spatial light modulator. The extrinsic phase disturbances studied are due to Kolmogorov turbulence. Simulation analysis shows that the size of super-pixel segments of the random phase patterns on the LCoS and the cropped image area of the phasorgrams are determined by Fried's parameter for high-Strehl-ratio and low-iteration-number reconstruction. AO experiments with an LCoS spatial light modulator confirm the simulation results.