Characterising the Gaia Radial Velocity sample selection function in its native photometry

TL;DR

This paper characterizes the Gaia DR2 radial velocity sample's selection function by analyzing its dependence on magnitude, color, and sky position, providing tools for accurate modeling of the sample's completeness.

Contribution

It presents a detailed, quantitative model of the Gaia DR2 radial velocity sample's selection function, including a practical implementation with code and queries.

Findings

Selection function depends on magnitude, color, and sky position.

Identifies high-completeness region in magnitude and color.

Provides tools and code for custom selection function queries.

Abstract

The Gaia DR2 radial velocity sample (GDR2RVS), which provides six-dimensional phase-space information on 7.2 million stars, is of great value for inferring properties of the Milky Way. Yet a quantitative and accurate modelling of this sample is hindered without knowledge and inclusion of a well-characterized selection function. Here we derive the selection function through estimates of the internal completeness, i.e. the ratio of GDR2RVS sources compared to all Gaia DR2 sources (GDR2all). We show that this selection function or "completeness" depends on basic observables, in particular the apparent magnitude GRVS and colour G-GRP, but also on the surrounding source density and on sky position, where the completeness exhibits distinct small-scale structure. We identify a region of magnitude and colour that has high completeness, providing an approximate but simple way of implementing the selection function. For a more rigorous and detailed description we provide python code to query our selection function, as well as tools and ADQL queries that produce custom selection functions with additional quality cuts.