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PEPITO: atmospheric Profiling from short-Exposure focal Plane Images in seeing-limiTed mOde
Atmospheric profiling is a requirement for controlling wide-field adaptive optics (AO) instruments, analysing the AO performance with respect to the observing conditions and predicting the point spread function (PSF) spatial variations. We present PEPITO, a new concept for profiling atmospheric turb...
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Published in: | Monthly notices of the Royal Astronomical Society 2019-06, Vol.486 (2), p.2032-2041 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Atmospheric profiling is a requirement for controlling wide-field adaptive optics (AO) instruments, analysing the AO performance with respect to the observing conditions and predicting the point spread function (PSF) spatial variations. We present PEPITO, a new concept for profiling atmospheric turbulence from post facto tip-tilt (TT) corrected short-exposure images. PEPITO utilizes the anisokinetism effect in the images between several stars separated from a reference star, and then produces the profile estimation using a model-fitting methodology, by fitting to the long-exposure TT-corrected PSF. PEPITO has a high sensitivity to both C 2 n (h) and L 0 (h) by relying on the full telescope aperture and a large field of view (FOV). It then obtains a high vertical resolution (1-400 m) configurable by the camera pixel scale, taking advantage of fast statistical convergence (of the order of tens of seconds). With only a short-exposure capable large format detector and a numerical complexity independent of the telescope diameter, PEPITO perfectly suits accurate profiling for night optical turbulence site characterization or AO instruments operations. We demonstrate, in simulation, that the C 2 n (h) and L 0 (h) can be estimated to better than 1 per cent accuracy, from fitted PSFs of magnitude V = 11 on a D = 0.5 m telescope with a 10 arcmin FOV. |
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ISSN: | 0035-8711 1365-2966 |
DOI: | 10.1093/mnras/stz979 |