Presentation + Paper
29 August 2022 Towards virtual access of adaptive optics telemetry data
Author Affiliations +
Abstract
Large amounts of Adaptive-Optics (AO) control loop data and telemetry are currently inaccessible to end-users. Broadening access to those data has the potential to change the AO landscape on many fronts, addressing several use-cases such as derivation of the system’s PSF, turbulence characterization and optimization of system control. We address one of the biggest obstacles to sharing these data: the lack of standardization, which hinders access. We propose an object-oriented Python package for AO telemetry, whose data model abstracts the user from an underlining archive-ready data exchange standard based on the Flexible Image Transport System (FITS). Its design supports data from a wide range of existing and future AO systems, either in raw format or abstracted from actual instrument details. We exemplify its usage with data from active AO systems on 10m-class observatories, of which two are currently supported (AOF and Keck), with plans for more.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tiago Gomes, Carlos Correia, Lisa Bardou, Olivier Beltramo-Martin, Thierry Fusco, Caroline Kulcsár, Timothy Morris, Nuno Morujão, Benoît Neichel, James Osborn, and Paulo Garcia "Towards virtual access of adaptive optics telemetry data", Proc. SPIE 12185, Adaptive Optics Systems VIII, 121850H (29 August 2022); https://doi.org/10.1117/12.2630214
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KEYWORDS
Adaptive optics

Data modeling

Telescopes

Wavefront sensors

Real-time computing

Sensors

Wavefronts

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