Issue |
A&A
Volume 687, July 2024
|
|
---|---|---|
Article Number | A258 | |
Number of page(s) | 24 | |
Section | Numerical methods and codes | |
DOI | https://doi.org/10.1051/0004-6361/202449654 | |
Published online | 22 July 2024 |
Improved source classification and performance analysis using Gaia DR3
Max-Planck Institute für Astronomy,
Königstuhl 17,
69117
Heidelberg,
Germany
e-mail: jamal@mpia.de
Received:
19
February
2024
Accepted:
26
April
2024
The Discrete Source Classifier (DSC) provides probabilistic classification of sources in Gaia Data Release 3 (GDR3) using a Bayesian framework and a global prior. The DSC Combmod classifier in GDR3 achieved for the extragalactic classes (quasars and galaxies) a high completeness of 92%, but a low purity of 22% (all sky, all magnitudes) due to contamination from the far larger star class. However, these single metrics mask significant variation in performance with magnitude and sky position. Furthermore, a better combination of the individual classifiers that comprise Combmod is possible. Here we compute two-dimensional (2D) representations of the completeness and the purity as a function of Galactic latitude and source brightness, and also exclude the Magellanic Clouds where stellar contamination significantly reduces the purity. Reevaluated on a cleaner validation set and without introducing changes to the published GDR3 DSC probabilities themselves, we here achieve for Combmod average 2D completenesses of 92% and 95% and average 2D purities of 55% and 89% for the quasar and galaxy classes, respectively. Since the relative proportions of extragalactic objects to stars in Gaia is expected to vary significantly with brightness and latitude, we then introduce a new prior that is a continuous function of brightness and latitude, and compute new class probabilities from the GDR3 DSC component classifiers, Specmod and Allosmod. Contrary to expectations, this variable prior only improves the performance by a few percentage points, mostly at the faint end. Significant improvement, however, is obtained by a new additive combination of Specmod and Allosmod. This classifier, Combmod-α, achieves average 2D completenesses of 82% and 93% and average 2D purities of 79% and 93% for the quasar and galaxy classes, respectively, when using the global prior. Thus, we achieve a significant improvement in purity for a small loss of completeness. The improvement is most significant for faint quasars (G≥20) where the purity rises from 20% to 62%.
Key words: methods: data analysis / methods: statistical / surveys / stars: general / galaxies: general / quasars: general
© The Authors 2024
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Open Access funding provided by Max Planck Society.
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