Neural network assisted high flexibility and high resolution Shack-Hartmann wavefront sensing for astronomical observation in darker sky areas

Abstract

Shack-Hartmann (SH) wavefront sensing is widely applied to astronomical observations with its fast and accurate measurement. However, due to the computational nature of SH that the input beam is segmented to provide local wavefront slopes, the sampling density of the sub-apertures and the calculation accuracy of each sub-focal spot’s centroid have great influence on the wavefront reconstruction accuracy. Therefore, it is usually difficult to achieve high resolution wavefront reconstruction for dark stars in the astronomical observations with insufficient light intensity. We present a neural-network assisted high resolution SH wavefront sensing method to overcome the shortages and obtain results with enhanced resolution from the separated information inside each sub-aperture. With this method, high resolution wavefront sensing in darker sky area could be realized.