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Integrated turbulence parameters' estimation from NAOMI adaptive optics telemetry data

Title
Integrated turbulence parameters' estimation from NAOMI adaptive optics telemetry data
Type
Article in International Scientific Journal
Year
2023
Authors
Morujao, N
(Author)
Other
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Correia, C
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FEUP
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Andrade, P
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Woillez, J
(Author)
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Journal
Vol. 678
Final page: A193
ISSN: 0004-6361
Publisher: EDP Sciences
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Authenticus ID: P-00Z-6YS
Abstract (EN): Context. Monitoring turbulence parameters is crucial in high-angular resolution astronomy for various purposes, such as optimising adaptive optics systems or fringe trackers. The former systems are present at most modern observatories and will remain significant in the future. This makes them a valuable complementary tool for the estimation of turbulence parameters. Aims. The feasibility of estimating turbulence parameters from low-resolution sensors remains untested. We performed seeing estimates for both simulated and on-sky telemetry data sourced from the new adaptive optics module installed on the four Auxiliary Telescopes of the Very Large Telescope Interferometer. Methods. The seeing estimates were obtained from a modified and optimised algorithm that employs a chi-squared modal fitting approach to the theoretical von Karman model variances. The algorithm was built to retrieve turbulence parameters while simultaneously estimating and accounting for the remaining and measurement error. A Monte Carlo method was proposed for the estimation of the statistical uncertainty of the algorithm. Results. The algorithm is shown to be able to achieve per-cent accuracy in the estimation of the seeing with a temporal horizon of 20 s on simulated data. A (0.76 '' +/- 1.2%vertical bar(stat) +/- 1.2%vertical bar(sys)) median seeing was estimated from on-sky data collected from 2018 to 2020. The spatial distribution of the Auxiliary Telescopes across the Paranal Observatory was found to not play a role in the value of the seeing.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 11
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