Detecting stars, galaxies, and asteroids with Gaia
J.H.J. de Bruijne, M. Allen, S. Azaz, A. Krone-Martins, T. Prod'homme,, D. Hestroffer (Scientific Support Office, Directorate of Science, Robotic, Exploration, European Space Research, Technology Centre (ESA/ESTEC),, Noordwijk, The Netherlands)

TL;DR
This paper optimizes Gaia's detection software parameters to improve star, galaxy, and asteroid detection accuracy while reducing false positives from cosmic rays and solar protons, enhancing overall astronomical object identification.
Contribution
The study develops an emulation of Gaia's detection software and identifies optimal rejection parameters that improve detection and rejection performance for various celestial and spurious objects.
Findings
Enhanced detection of single and double stars.
Improved rejection of cosmic rays and solar protons.
Better detection of faint asteroids and near-Earth objects.
Abstract
(Abridged) Gaia aims to make a 3-dimensional map of 1,000 million stars in our Milky Way to unravel its kinematical, dynamical, and chemical structure and evolution. Gaia's on-board detection software discriminates stars from spurious objects like cosmic rays and Solar protons. For this, parametrised point-spread-function-shape criteria are used. This study aims to provide an optimum set of parameters for these filters. We developed an emulation of the on-board detection software, which has 20 free, so-called rejection parameters which govern the boundaries between stars on the one hand and sharp or extended events on the other hand. We evaluate the detection and rejection performance of the algorithm using catalogues of simulated single stars, double stars, cosmic rays, Solar protons, unresolved galaxies, and asteroids. We optimised the rejection parameters, improving - with respect to…
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