GaiaEarly Data Release 3

Abstract

Context. Gaia Early Data Release 3 (Gaia EDR3) contains astrometry and photometry results for about 1.8 billion sources based on observations collected by the European Space Agency Gaia satellite during the first 34 months of its operational phase. Aims. In this paper, we focus on the photometric content, describing the input data, the algorithms, the processing, and the validation of the results. Particular attention is given to the quality of the data and to a number of features that users may need to take into account to make the best use of the Gaia EDR3 catalogue. Methods. The processing broadly followed the same procedure as for Gaia DR2, but with significant improvements in several aspects of the blue and red photometer (BP and RP) preprocessing and in the photometric calibration process. In particular, the treatment of the BP and RP background has been updated to include a better estimation of the local background, and the detection of crowding effects has been used to exclude affected data from the calibrations. The photometric calibration models have also been updated to account for flux loss over the whole magnitude range. Significant improvements in the modelling and calibration of the Gaia point and line spread functions have also helped to reduce a number of instrumental effects that were still present in DR2. Results. Gaia EDR3 contains 1.806 billion sources with G-band photometry and 1.540 billion sources with GBP and GRP photometry. The median uncertainty in the G-band photometry, as measured from the standard deviation of the internally calibrated mean photometry for a given source, is 0.2 mmag at magnitude G = 10–14, 0.8 mmag at G ≈ 17, and 2.6 mmag at G ≈ 19. The significant magnitude term found in the Gaia DR2 photometry is no longer visible, and overall there are no trends larger than 1 mmag mag−1. Using one passband over the whole colour and magnitude range leaves no systematics above the 1% level in magnitude in any of the bands, and a larger systematic is present for a very small sample of bright and blue sources. A detailed description of the residual systematic effects is provided. Overall the quality of the calibrated mean photometry in Gaia EDR3 is superior with respect to DR2 for all bands.

Revisiting the Cygnus OB associations

“…We use photometry and astrometry from IGAPS (INT Galactic Plane Survey, providing g-, r-, i-band photometry, Drew et al 2005, Monguió et al 2020, 2MASS (Two-Micron All-Sky Survey, providing J-, H-, and K s -band photometry, Cutri et al 2003), UKIDSS (United Kingdom Infrared Deep Sky Survey, providing deeper J-, H-and K-band photometry, Lucas et al 2008), and Gaia EDR3 (Gaia Collaboration 2016Riello et al 2020), providing G-, G BP -and G RP -band photometry. In addition, we use parallaxes and proper motions from Gaia EDR3 (Fabricius et al 2021), and the probabilistic distances derived from these parallaxes provided by Bailer-Jones et al (2020).…”

“…For IGAPS, photometry is reliable if saturation is avoided and if its associated class indicates a star or probable star (Monguió et al 2020). For Gaia, the requirement summarizes as |C * | < 3 σ C * where C * stands for the corrected excess flux factor in the G RP and G BP bands and σ C * is a power law on the G band with a chosen 3σ level (Riello et al 2020). For 2MASS, a goodquality flag on each photometric band is required (Cutri et al 2003).…”

The GALAH survey: effective temperature calibration from the InfraRed Flux Method in the Gaia system

“…In all instances, calibrations have been applied within the validity ranges of Table 2. effects following Riello et al (2021). G magnitude correction for bright blue sources is not applied since none of our target is bluer than BP − RP ∼ 0, but we correct G magnitudes for sources with two-or six-parameter astrometric solutions.…”

Testing for Dark Matter in the Outskirts of Globular Clusters

“…Figure 1 compares our sample of stars for NGC 6752 to the 90% probability cluster stars as found in a kinematically based Gaussian mixture model (Vasiliev & Baumgardt 2021) for stars between projected radii of 5 and 100 pc of the cluster center. Stellar crowding in the inner 5 pc increases the photometric errors and reduces the limiting magnitude (Pancino et al 2017;Riello et al 2021), but these innermost stars are largely irrelevant to the goals of this paper. The horizontal branch stars cannot be sufficiently narrowly defined to be usefully included in the photometric model of the cluster, but their numbers are sufficiently small that little is lost.…”