Photometric metallicities of 0.8 million KiDS stars

TL;DR

This paper introduces a data-driven photometric method to estimate metallicities, temperatures, and absolute magnitudes for 0.8 million stars in the Milky Way using KiDS and VIKING survey data, validated against spectroscopic data.

Contribution

The study develops and validates a new algorithm that derives stellar parameters from photometry, enabling large-scale metallicity estimation with quantified uncertainties.

Findings

Photometric metallicities have ~0.28 dex uncertainty compared to spectroscopic data.

Effective temperatures estimated with ~149 K uncertainty.

The catalog covers stars with metallicities down to -2 dex, aiding Galactic studies.

Abstract

Accurate determinations of metallicity for large, complete stellar samples are essential for advancing various studies of the Milky Way. In this paper, we present a data-driven algorithm that leverages photometric data from the KiDS and the VIKING surveys to estimate stellar absolute magnitude, effective temperature and metallicities. The algorithm is trained and validated using spectroscopic data from LAMOST, SEGUE, APOGEE, and GALAH, as well as a catalog of very metal-poor stars from the literature, and Gaia EDR3 data. This approach enables us to estimate metallicities, effective temperatures, and g-band absolute magnitudes for approximately 0.8 million stars in the KiDS dataset. The photometric metallicity estimates exhibit an uncertainty of around 0.28 dex when compared to spectroscopic studies, within the metallicity range of -2 dex to 0.5 dex. The photometric effective temperature estimates have an uncertainty of around 149 K, while the uncertainty in the absolute magnitude is approximately 0.36 mag. The metallicity estimates are reliable for values down to about -2 dex. This catalog represents a valuable resource for studying the structure and chemical properties of the Milky Way, offering an extensive dataset for future investigations into Galactic formation and evolution.