The Gaia DR2 parallax zero-point: hierarchical modelling of red clump stars
Abstract
ABSTRACT The systematic offset of Gaia parallaxes has been widely reported with Gaia’s second data release, and it is expected to persist in future Gaia data. In order to use Gaia parallaxes to infer distances to high precision, we develop a hierarchical probabilistic model to determine the Gaia parallax zero-point offset along with the calibration of an empirical model for luminosity of red clump stars by combining astrometric and photometric measurements. Using a cross-matched sample of red clump stars from the Apache Point Observatory Galactic Evolution Experiment and Gaia Data Release 2 (DR2), we report the parallax zero-point offset in DR2 to be $$\varpi _0 = -48 \pm 1\,\mu \text{as}$$. We infer the red clump absolute magnitude to be −1.622 ± 0.004 in Ks, 0.435 ± 0.004 in G, −1.019 ± 0.004 in J, and −1.516 ± 0.004 in H. The intrinsic scatter of the red clump is ∼0.09 mag in J, H, and Ks, or ∼ 0.12 mag in G. We tailor our models to accommodate more complex analyses such as investigating the variations of the parallax zero-point with each source’s observed magnitude, observed colour, and sky position. In particular, we find fluctuations of the zero-point across the sky to be of order or less than a few 10s of $$\mu \text{as}$$.
- Authors:
-
- David A. Dunlap Department of Astronomy and Astrophysics, University of Toronto, 50 St George Street, Toronto, ON M5S 3H4, Canada
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1605035
- Resource Type:
- Published Article
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Additional Journal Information:
- Journal Name: Monthly Notices of the Royal Astronomical Society Journal Volume: 493 Journal Issue: 3; Journal ID: ISSN 0035-8711
- Publisher:
- Oxford University Press
- Country of Publication:
- United Kingdom
- Language:
- English
Citation Formats
Chan, Victor C., and Bovy, Jo. The Gaia DR2 parallax zero-point: hierarchical modelling of red clump stars. United Kingdom: N. p., 2020.
Web. doi:10.1093/mnras/staa571.
Chan, Victor C., & Bovy, Jo. The Gaia DR2 parallax zero-point: hierarchical modelling of red clump stars. United Kingdom. https://doi.org/10.1093/mnras/staa571
Chan, Victor C., and Bovy, Jo. Thu .
"The Gaia DR2 parallax zero-point: hierarchical modelling of red clump stars". United Kingdom. https://doi.org/10.1093/mnras/staa571.
@article{osti_1605035,
title = {The Gaia DR2 parallax zero-point: hierarchical modelling of red clump stars},
author = {Chan, Victor C. and Bovy, Jo},
abstractNote = {ABSTRACT The systematic offset of Gaia parallaxes has been widely reported with Gaia’s second data release, and it is expected to persist in future Gaia data. In order to use Gaia parallaxes to infer distances to high precision, we develop a hierarchical probabilistic model to determine the Gaia parallax zero-point offset along with the calibration of an empirical model for luminosity of red clump stars by combining astrometric and photometric measurements. Using a cross-matched sample of red clump stars from the Apache Point Observatory Galactic Evolution Experiment and Gaia Data Release 2 (DR2), we report the parallax zero-point offset in DR2 to be $\varpi _0 = -48 \pm 1\,\mu \text{as}$. We infer the red clump absolute magnitude to be −1.622 ± 0.004 in Ks, 0.435 ± 0.004 in G, −1.019 ± 0.004 in J, and −1.516 ± 0.004 in H. The intrinsic scatter of the red clump is ∼0.09 mag in J, H, and Ks, or ∼ 0.12 mag in G. We tailor our models to accommodate more complex analyses such as investigating the variations of the parallax zero-point with each source’s observed magnitude, observed colour, and sky position. In particular, we find fluctuations of the zero-point across the sky to be of order or less than a few 10s of $\mu \text{as}$.},
doi = {10.1093/mnras/staa571},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 3,
volume = 493,
place = {United Kingdom},
year = {Thu Feb 27 00:00:00 EST 2020},
month = {Thu Feb 27 00:00:00 EST 2020}
}
https://doi.org/10.1093/mnras/staa571
Web of Science
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