The Gaia EDR3 view of Johnson-Kron-Cousins standard stars: the curated Landolt and Stetson collections

TL;DR

This paper refines and characterizes the Landolt and Stetson collections of standard stars using Gaia DR3 data, improving calibration accuracy across multiple photometric systems with new classifications, parameters, and transformation formulas.

Contribution

It presents a curated, well-characterized set of over 200,000 secondary standards with improved parameters and transformations, enhancing calibration reliability in astronomical photometry.

Findings

Better agreement of atmospheric parameters with spectroscopic data.

Comprehensive cross-matching with major photometric surveys.

Provision of polynomial transformations for photometric conversions.

Abstract

(Shortened). In the era of large surveys and space missions, it is necessary to rely on large samples of well-characterized stars for inter-calibrating and comparing measurements from different sources. Among the most employed photometric systems, the Johnson-Kron-Cousins has been used for decades and for a large amount of important datasets. Using Gaia DR3 as a reference, as well as data from reddening maps, spectroscopic surveys, and variable stars monitoring surveys, we curated and characterized the widely used Landolt and Stetson collections of more than 200 000 secondary standards, removing binaries, blends, and variable stars, and we classified and parametrized them, employing classical as well as machine learning techniques. In particular, our atmospheric parameters agree significantly better with spectroscopic ones, compared to other catalogues obtained by means of machine learning. We also cross-matched the collections with the major photometric surveys to provide a comprehensive table with the magnitudes of the secondary standards in the most widely used photometric systems (ugriz, grizy, Gaia, Hipparcos, Tycho, 2MASS). We finally provide a set of 167 polynomial transformations, valid for dwarfs and giants, metal-poor and metal-rich stars, to transform UBVRI magnitudes into the above photometric systems and vice-versa.