TY - JOUR
T1 - Estimating the selection function of Gaia DR3 subsamples
AU - Castro-Ginard, Alfred
AU - Brown, Anthony G.A.
AU - Kostrzewa-Rutkowska, Zuzanna
AU - Cantat-Gaudin, Tristan
AU - Drimmel, Ronald
AU - Oh, Semyeong
AU - Belokurov, Vasily
AU - Casey, Andrew R.
AU - Fouesneau, Morgan
AU - Khanna, Shourya
AU - Price-Whelan, Adrian M.
AU - Rix, Hans Walter
N1 - Funding Information:
We thank David W. Hogg for his contributions to the GaiaUnlimited project. This work is a result of the GaiaUnlimited project, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101004110. The GaiaUnlim-ited project was started at the 2019 Santa Barbara Gaia Sprint, hosted by the Kavli Institute for Theoretical Physics at the University of California, Santa Barbara. This work has made use of results from the European Space Agency (ESA) space mission Gaia, the data from which were processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC has been provided by national institutions, in particular, the institutions participating in the Gaia Multilateral Agreement. The Gaia mission website is http://www.cosmos.esa.int/gaia . The authors are current or past members of the ESA Gaia mission team and of the Gaia DPAC.
Publisher Copyright:
© 2023 The Authors.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - Understanding the intricacies behind the presence and absence of sources in an astronomical catalogue is crucial for the accurate interpretation of astronomical data. In particular, for the multi-dimensional Gaia data, filters and cuts on different parameters or measurements introduce a selection function that may unintentionally alter scientific conclusions in subtle ways. Aims. We aim to develop a methodology to estimate the selection function for different subsamples of stars in the Gaia catalogue. Methods. Comparing the number of stars in a given subsample to that in the overall Gaia catalogue provides an estimate of the subsample membership probability as a function of sky position, magnitude, and colour. The method used to make this estimate must differentiate the stochastic absence of subsample stars from selection effects. When multiplied with the overall Gaia catalogue selection function, this provides the total selection function of the subsample. Results. We present our new method for estimating the selection function by applying it to the sources in Gaia DR3 with heliocentric radial velocity measurements. We also compute the selection function for the stars in the Gaia-Sausage/Enceladus sample, confirming that the apparent asymmetry of its debris across the sky is merely caused by selection effects. Conclusions. The method we have developed estimates the selection function of the stars present in a subsample of Gaia data, given that the subsample is completely contained in the Gaia parent catalogue (for which the selection function is known). This tool is made available in a GaiaUnlimited Python package.
AB - Understanding the intricacies behind the presence and absence of sources in an astronomical catalogue is crucial for the accurate interpretation of astronomical data. In particular, for the multi-dimensional Gaia data, filters and cuts on different parameters or measurements introduce a selection function that may unintentionally alter scientific conclusions in subtle ways. Aims. We aim to develop a methodology to estimate the selection function for different subsamples of stars in the Gaia catalogue. Methods. Comparing the number of stars in a given subsample to that in the overall Gaia catalogue provides an estimate of the subsample membership probability as a function of sky position, magnitude, and colour. The method used to make this estimate must differentiate the stochastic absence of subsample stars from selection effects. When multiplied with the overall Gaia catalogue selection function, this provides the total selection function of the subsample. Results. We present our new method for estimating the selection function by applying it to the sources in Gaia DR3 with heliocentric radial velocity measurements. We also compute the selection function for the stars in the Gaia-Sausage/Enceladus sample, confirming that the apparent asymmetry of its debris across the sky is merely caused by selection effects. Conclusions. The method we have developed estimates the selection function of the stars present in a subsample of Gaia data, given that the subsample is completely contained in the Gaia parent catalogue (for which the selection function is known). This tool is made available in a GaiaUnlimited Python package.
KW - Catalogs
KW - Galaxy: general
KW - Methods: statistical
UR - http://www.scopus.com/inward/record.url?scp=85170820195&partnerID=8YFLogxK
U2 - 10.1051/0004-6361/202346547
DO - 10.1051/0004-6361/202346547
M3 - Article
AN - SCOPUS:85170820195
SN - 0004-6361
VL - 677
JO - Astronomy & Astrophysics
JF - Astronomy & Astrophysics
M1 - A37
ER -