Pyramid and Hartmann–Shack wavefront sensor with artificial neural network for adaptive optics

Abstract

A three-sided pyramid prism is used as a wavefront sensor in non-modulating mode with an artificial neural network (NN) as a control unit in an adaptive optical setup. The NN is composed of a convolution network for feature extraction from the pyramid signal and a three-layer feed-forward back-propagation net. The network is trained with over 15,000 examples of signal–wavefront pairs. Presenting wavefronts of 6 mm pupil diameter and a RMS error of under 200 nm to the adaptive optical system with the trained network, it can correct the aberrations within three loops to a wavefront with <60 nm root mean square (RMS) error.

Keywords:

• wavefront
• pyramid sensor
• Hartmann–Shack sensor
• artificial neural networks
• retina imaging

Acknowledgements

CAD thanks Hongwei Zhang for his contribution to this work and the Pyramid group at Max-Plank Institute of Astronomy, especially Joanna Buechler Costa, Diethard Peter and Sebastian Egner for discussions and help.