Asteroid characterization using Gaia Data Release 3

II. Taxonomic classification

¹ Department of Physics, PO Box 64, 00014 University of Helsinki, Finland
² Astronomical Observatory Institute, Faculty of Physics, A. Mickiewicz University, Słoneczna 36, 60-286 Poznań, Poland
³ INAF – Osservatorio Astrofisico di Torino, 10025 Pino Torinese, Italy
⁴ Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, France
⁵ Yunnan Observatories, Chinese Academy of Sciences, Kunming, China
⁶ Karman+, 11365 Main St, Broomfield, CO 80020, USA

^★ Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 27 June 2025
Accepted: 27 November 2025

Abstract

Context. We study the taxonomic classification of asteroids observed by Gaia as a continuation of the lightcurve inversion work presented in Paper I.

Aims. We examine the taxonomic classification of asteroids by using both Gaia Data Release 3 (DR3) photometric and spectroscopic data. Particular focus is placed on Ch-class asteroids, as their potentially hydrated nature makes them promising candidates for sample-return missions and the asteroid mining industry.

Methods. We utilized the photometric slopes and geometric albedos (via absolute magnitudes) derived from lightcurve inversion, and the Gaia DR3 spectra (from 418 nm to 770 nm) as classification parameters. We also considered how different parameter sets affect classification accuracies for separate asteroid classes. We classified the asteroids with a combination of linear discriminant analysis and a nearest neighbor classifier.

Results. We achieve a classification accuracy of 92% for known S-class asteroids and an accuracy of 85% for Ch-class asteroids with a known set of 328 asteroids. Given the three classification parameters, tentative class designations for 1668 previously unclassified asteroids are provided in the Mahlke taxonomy. We also show that the photometric slope values vary significantly within asteroid classes, with a standard deviation three to four times the mean slope uncertainties.

Conclusions. We show that the combination of photometry and spectroscopy can be useful in the taxonomic classification of asteroids observed by Gaia. Further studies of the surface roughness at different scales could help clarify the potential of the photometric slope in classification efforts.