Linearized wavefront sensing model for aberration retrieval from low-frequency Fourier coefficients.

This paper proposes and demonstrates a linearized model for phase diversity wavefront sensing, facilitating real-time processing and much less data required for training. Specifically, we find that the low-frequency Fourier coefficients of point spread function images are linearly proportional to pupil aberration coefficients under certain conditions. Simulation and experimental results show that the model can greatly reduce the processing time to several milliseconds by merely requiring hundreds of training samples while maintaining a comparatively high accuracy with state-of-the-art methods.