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Title: Wavefront sensing with optical differentiation powered by deep learning

We report the experimental demonstration of an optical differentiation wavefront sensor (ODWS) based on binary pixelated linear and nonlinear amplitude filtering in the far-field. We trained and tested a convolutional neural network that reconstructs the spatial phase map from nonlinear-filter-based ODWS data for which an analytic reconstruction algorithm is not available. It shows accurate zonal retrieval over different magnitudes of wavefronts and on randomly shaped wavefronts. This work paves the way for the implementation of simultaneously sensitive, high dynamic range, and high-resolution wavefront sensing.

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NSF-PAR ID:
10541341
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
Optical Society of America
Date Published:
Journal Name:
Optics Letters
Volume:
49
Issue:
18
ISSN:
0146-9592; OPLEDP
Format(s):
Medium: X Size: Article No. 5216
Size(s):
Article No. 5216
Sponsoring Org:
National Science Foundation
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