Visible pyramid wavefront sensing approach for daylight adaptive optics

Daytime application of the pyramid wavefront sensor (PyWFS) is greatly challenged by a bright and fluctuating sky background, especially in the visible. A daytime-Py approach to apply visible pyramid wavefront sensing for real-time daylight AO is described in this paper. A field stop (FS) and a lenslet array are applied in the daylight AO system based on a visible PyWFS to separate the object signal from the background signal and improve the signal-to-noise ratio (SNR). A background elimination algorithm is proposed to extract the effective object signal. Closed-loop experiment using the daytime-Py approach is performed, which presents the first laboratory real-time daylight natural guide star AO correction of a faint object based on a visible PyWFS. SNR ranges for both the daytime-Py approach and PyWFS are reported. Furthermore, the correction results in different SNRs using both methods and with various pupil samplings using the daytime-Py approach are presented to prove that our proposal has the advantages over the PyWFS and Shack-Hartmann wavefront sensor (SHWFS) tbr daylight AO. This study demonstrates that the daytime-Py approach can realize the real-time object tracking and closed-loop correction in the daylight natural guide star adaptive optics (AO) system based on the visible PyWFS. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement