A selection function toolbox for subsets of astronomical catalogues

TL;DR

This paper introduces a flexible, statistically rigorous framework and open-source tool for estimating the selection function of astronomical catalog samples, accounting for correlations across multiple parameters, demonstrated on APOGEE and Gaia data.

Contribution

The authors present a novel framework using Gaussian processes and spherical harmonics to estimate selection functions, implemented in an open-source Python package, applicable to various astronomical surveys.

Findings

Successfully estimated APOGEE DR16 selection function with multiple methods

Demonstrated the framework's application to Gaia EDR3 data

Provided an accessible tool for astrophysicists to determine sample selection functions

Abstract

Large catalogues are ubiquitous throughout astronomy, but most scientific analyses are carried out on smaller samples selected from these catalogues by chosen cuts on catalogued quantities. The selection function of that scientific sample - the probability that a star in the catalogue will satisfy these cuts and so make it into the sample - is thus unique to each scientific analysis. We have created a general framework that can flexibly estimate the selection function of a sample drawn from a catalogue in terms of position, magnitude and colour. Our method is unique in using the binomial likelihood and accounting for correlations in the selection function across position, magnitude and colour using Gaussian processes and spherical harmonics. We have created a new open-source Python package selectionfunctiontoolbox that implements this framework and used it to make three different estimates of the APOGEE DR16 red giant sample selection function, as a subset of 2MASS, with each estimate using an increasing amount of technical knowledge of the APOGEE targeting. In a companion paper we applied our methodology to derive estimates of the astrometric and spectroscopic selection functions of Gaia EDR3. Our framework will make it trivial for astrophysicists to estimate the selection function that they should be using with the custom sample of stars that they have chosen to answer their scientific question.