Poster + Paper
27 August 2024 Women measuring stars: a comprehensive strategy for the exploitation of adaptive optics data
Laura Schreiber, Emiliano Diolaiti, Giuliana Fiorentino, Carmela Lardo, Claudia Mignone, Davide Ricci, Maria Tantalo, Antonino Nunnari
Author Affiliations +
Conference Poster
Abstract
In the last decades, all the main existing telescopes have been equipped with Adaptive Optics (AO) facilities, and AO is considered an enabling technology for future giant telescopes. A significant limitation to the scientific exploitation of AO data is represented by uncertainties in the knowledge of the Point Spread Function, strongly linked to the need for optimised software tools for AO image analysis. We aim to develop a software package designed and optimised to analyse AO images with complex and spatially variable PSF to maximise the exploitation of high-precision quantitative science from past, present and future AO observations. The new software will address two problems: 1) extracting and modelling the AO PSF across the field of view directly from the AO imaging and spectro-imaging data and 2) extracting quantitative information from data featuring blended sources. The new methods will be validated on simulated images and available data from existing and upcoming AO facilities. The new FAIR software, written in Python™, will be based on a version of the Starfinder software optimised to handle large-format images with variable and structured PSF.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Laura Schreiber, Emiliano Diolaiti, Giuliana Fiorentino, Carmela Lardo, Claudia Mignone, Davide Ricci, Maria Tantalo, and Antonino Nunnari "Women measuring stars: a comprehensive strategy for the exploitation of adaptive optics data", Proc. SPIE 13097, Adaptive Optics Systems IX, 130977J (27 August 2024); https://doi.org/10.1117/12.3019771
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KEYWORDS
Adaptive optics

Point spread functions

Stars

Data modeling

Analytic models

Telescopes

Imaging systems

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