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Proceedings Paper

Turbulence profiling for adaptive optics tomographic reconstructors
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Paper Abstract

To approach optimal performance advanced Adaptive Optics (AO) systems deployed on ground-based telescopes must have accurate knowledge of atmospheric turbulence as a function of altitude. Stereo-SCIDAR is a high-resolution stereoscopic instrument dedicated to this measure. Here, its profiles are directly compared to internal AO telemetry atmospheric profiling techniques for CANARY (Vidal et al. 20141), a Multi-Object AO (MOAO) pathfinder on the William Herschel Telescope (WHT), La Palma. In total twenty datasets are analysed across July and October of 2014. Levenberg-Marquardt fitting algorithms dubbed Direct Fitting and Learn 2 Step (L2S; Martin 20142) are used in the recovery of profile information via covariance matrices - respectively attaining average Pearson product-moment correlation coefficients with stereo-SCIDAR of 0.2 and 0.74. By excluding the measure of covariance between orthogonal Wavefront Sensor (WFS) slopes these results have revised values of 0.65 and 0.2. A data analysis technique that combines L2S and SLODAR is subsequently introduced that achieves a correlation coefficient of 0.76.

Paper Details

Date Published: 27 July 2016
PDF: 6 pages
Proc. SPIE 9909, Adaptive Optics Systems V, 99093I (27 July 2016); doi: 10.1117/12.2233323
Show Author Affiliations
Douglas J. Laidlaw, Durham Univ. (United Kingdom)
James Osborn, Durham Univ. (United Kingdom)
Richard W. Wilson, Durham Univ. (United Kingdom)
Timothy J. Morris, Durham Univ. (United Kingdom)
Timothy Butterley, Durham Univ. (United Kingdom)
Andrew P. Reeves, Durham Univ. (United Kingdom)
Matthew J. Townson, Durham Univ. (United Kingdom)
Éric Gendron, LESIA, Observatoire de Paris, CNRS, UPMC, Univ. Paris Diderot (France)
Fabrice Vidal, LESIA, Observatoire de Paris, CNRS, UPMC, Univ. Paris Diderot (France)
Carine Morel, LESIA, Observatoire de Paris, CNRS, UPMC, Univ. Paris Diderot (France)

Published in SPIE Proceedings Vol. 9909:
Adaptive Optics Systems V
Enrico Marchetti; Laird M. Close; Jean-Pierre Véran, Editor(s)

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