AUTHOR=Guan Hongli , Zhao Wang , Wang Shuai , Yang Kangjian , Zhao Mengmeng , Liu Shenghu , Guo Han , Yang Ping TITLE=Higher-resolution wavefront sensing based on sub-wavefront information extraction JOURNAL=Frontiers in Physics VOLUME=11 YEAR=2024 URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2023.1336651 DOI=10.3389/fphy.2023.1336651 ISSN=2296-424X ABSTRACT=

The limited spatial sampling rates of conventional Shack–Hartmann wavefront sensors (SHWFSs) make them unable to sense higher-order wavefront distortion. In this study, by etching a known phase on each microlens to modulate sub-wavefront, we propose a higher-resolution wavefront reconstruction method that employs a modified modal Zernike wavefront reconstruction algorithm, in which the reconstruction matrix contains quadratic information that is extracted using a neural network. We validate this method through simulations, and the results show that once the network has been trained, for various atmospheric conditions and spatial sampling rates, the proposed method enables fast and accurate high-resolution wavefront reconstruction. Furthermore, it has highly competitive advantages such as fast dataset generation, simple network structure, and short prediction time.