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

Area of Science:

• Optics and Photonics
• Adaptive Optics Systems

Background:

• Phase retrieval offers a simpler alternative for sensor-less adaptive optics (AO).
• Random phase diversity has emerged as a method for accelerating phase retrieval algorithms.

Purpose of the Study:

• To optimize the design of sensor-less AO systems utilizing random phase diversity with liquid-crystal-on-silicon (LCoS) spatial light modulators.
• To investigate the impact of random phase diversity parameters on phase retrieval performance under Kolmogorov turbulence.

Main Methods:

• Simulated phase retrieval using a sensor-less AO system model with an LCoS modulator.
• Investigated extrinsic phase disturbances caused by Kolmogorov turbulence.
• Analyzed the influence of super-pixel segment size and phasorgram cropping on reconstruction quality.

Main Results:

• Simulation results indicate that super-pixel size on the LCoS and phasorgram cropping area are determined by Fried's parameter.
• These parameters are critical for achieving high Strehl ratios and minimizing reconstruction iterations.
• Experimental validation using an LCoS spatial light modulator confirmed the simulation findings.

Conclusions:

• Optimized design parameters for random phase diversity in sensor-less AO systems are identified.
• The study demonstrates the effectiveness of random phase diversity for LCoS-based AO systems.
• Findings provide practical guidelines for implementing efficient phase retrieval in AO applications.