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Adaptive Optics Telemetry Format
Tiago Gomes  1, 2@  , Carlos Correia  2, 3@  , Lisa Bardou  4@  , Thierry Fusco  5, 6@  , Caroline Kulcsar  7@  , Tim Morris  4@  , Nuno Morujão  2, 8@  , Benoit Neichel  5@  , James Osborn  4@  , Paulo J V Garcia  1, 2@  
1 : Faculdade de Engenharia da Universidade do Porto
2 : CENTRA - Center for Astrophysics and Gravitation
3 : Space ODT - Optical Deblurring Technologies
4 : Durham University
5 : Aix-Marseille Université
Aix-Marseille Université - AMU
6 : DOTA, ONERA, Université Paris Saclay [Palaiseau]
Université Paris-Saclay, ONERA
7 : Institut d'Optique Graduate School
Université Paris-Saclay, Institut d'Optique Graduate School, CNRS, Laboratoire Charles Fabry, 91127, Palaiseau, France, Université Paris-Saclay, Institut d'Optique Graduate School, CNRS, Laboratoire Charles Fabry, 91127, Palaiseau, France.
8 : Departamento de Física e Astronomia, Faculdade de Ciências da Universidade do Porto

Context:There is a growing volume of AO telemetry data being generated in facility-class ground-based VIS/NIR observatories, which has highlighted the need for a standardized data exchange format to enable performance analysis and AO R&D involving extensive telemetry mining, processing, and curation.

Aims:In this paper, we present the Adaptive Optics Telemetry (AOT) data exchange format, designed to facilitate the sharing of AO telemetry from visible/infrared ground-based observatories. The AOT format is built on the Flexible Image Transport System (FITS) and aims to provide a clear and consistent means of accessing data across multiple systems and configurations, including classical natural and single/multiple laser guide-star AO systems.

Methods: AOT was designed with two main use-cases in mind 1) atmospheric turbulence parameters estimation and 2) Point-spread function reconstruction (PSF-R). To support this format, a Python package that enables data conversion, reading, writing and exploration of AOT files was developed.

Results: The AOT format has a well-defined file structure, including data fields, descriptions, data types, units, and expected data dimensions. A supporting Python package has been made publicly available. To demonstrate the format's versatility, we packaged data from four different 8-meter class telescopes of vastly different configurations.


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