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Proceedings Paper

First on-sky results of a neural network based tomographic reconstructor: Carmen on Canary
Author(s): J. Osborn; D. Guzman; F. J. de Cos Juez; A. G. Basden; T. J. Morris; É. Gendron; T. Butterley; R. M. Myers; A. Guesalaga; F. Sanchez Lasheras; M. Gomez Victoria; M. L. Sánchez Rodríguez; D. Gratadour; G. Rousset
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Paper Abstract

We present on-sky results obtained with Carmen, an artificial neural network tomographic reconstructor. It was tested during two nights in July 2013 on Canary, an AO demonstrator on the William Hershel Telescope. Carmen is trained during the day on the Canary calibration bench. This training regime ensures that Carmen is entirely flexible in terms of atmospheric turbulence profile, negating any need to re-optimise the reconstructor in changing atmospheric conditions. Carmen was run in short bursts, interlaced with an optimised Learn and Apply reconstructor. We found the performance of Carmen to be approximately 5% lower than that of Learn and Apply.

Paper Details

Date Published: 21 July 2014
PDF: 6 pages
Proc. SPIE 9148, Adaptive Optics Systems IV, 91484M (21 July 2014); doi: 10.1117/12.2057462
Show Author Affiliations
J. Osborn, Durham Univ. (United Kingdom)
D. Guzman, Pontificia Univ. Católica de Chile (Chile)
F. J. de Cos Juez, Univ. de Oviedo (Spain)
A. G. Basden, Durham Univ. (United Kingdom)
T. J. Morris, Durham Univ. (United Kingdom)
É. Gendron, LESIA, CNRS, Observatoire de Paris (France)
T. Butterley, Durham Univ. (United Kingdom)
R. M. Myers, Durham Univ. (United Kingdom)
A. Guesalaga, Pontificia Univ. Católica de Chile (Chile)
F. Sanchez Lasheras, Univ. de Oviedo (Spain)
M. Gomez Victoria, Univ. de Oviedo (Spain)
M. L. Sánchez Rodríguez, Univ. de Oviedo (Spain)
D. Gratadour, LESIA, CNRS, Observatoire de Paris (France)
G. Rousset, LESIA, CNRS, Observatoire de Paris (France)


Published in SPIE Proceedings Vol. 9148:
Adaptive Optics Systems IV
Enrico Marchetti; Laird M. Close; Jean-Pierre Véran, Editor(s)

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