Deep learning wavefront reconstruction for collimated beams with experimental data

Carlos González-Gutiérrez; Carlos González-Gutiérrez; Nazim Ali Bharmal; Jorge Rodríguez Muro; Jorge Rodríguez Muro; Francisco Javier de Cos Juez; Francisco Javier de Cos Juez

doi:10.1364/AOA.2022.OF2B.5

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
Technical Digest Series (Optica Publishing Group, 2022),
paper OF2B.5
•https://doi.org/10.1364/AOA.2022.OF2B.5

Deep learning wavefront reconstruction for collimated beams with experimental data

Carlos González-Gutiérrez, Nazim Ali Bharmal, Jorge Rodríguez Muro, and Francisco Javier de Cos Juez

Adaptive Optics and Applications 2022

Vancouver, British Columbia Canada
11–15 July 2022
ISBN: 978-1-957171-09-8

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FSO Wavefront Sensing and Control (OF2B)

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C. González-Gutiérrez, N. A. Bharmal, J. R. Muro, and F. J. de Cos Juez, "Deep learning wavefront reconstruction for collimated beams with experimental data," in Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), Technical Digest Series (Optica Publishing Group, 2022), paper OF2B.5.

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Abstract

A broad collimated laser beam and a pair of cameras combined with deep learning, helps to characterize atmospheric effects when observing distant objects with a telescope or the possible effects in ground communications.

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