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Everall, A, Wyn Evans, N, Belokurov, V, Boubert, D and Grand, RJJ (2021) The Photo-Astrometric vertical tracer density of the Milky Way-I. the method. Monthly Notices of the Royal Astronomical Society, 511 (2). pp. 2390-2404. ISSN 0035-8711
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Abstract
We introduce a method to infer the vertical distribution of stars in the Milky Way using a Poisson likelihood function, with a view to applying our method to the Gaia catalogue. We show how to account for the sample selection function and for parallax measurement uncertainties. Our method is validated against a simulated sample drawn from a model with two exponential discs and a power-law halo profile. A mock Gaia sample is generated using the Gaia astrometry selection function, whilst realistic parallax uncertainties are drawn from the Gaia Astrometric Spread Function. The model is fit to the mock in order to rediscover the input parameters used to generate the sample. We recover posterior distributions that accurately fit the input parameters within statistical uncertainties, demonstrating the efficacy of our method. Using the GUMS synthetic Milky Way catalogue, we find that our halo parameter fits can be heavily biased by our overly simplistic model; however, the fits to the thin and thick discs are not significantly impacted. We apply this method to Gaia Early Data Release 3 in a companion paper where we also quantify the systematic uncertainties introduced by oversimplifications in our model.
| Item Type: | Article |
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| Additional Information: | This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2021 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved. |
| Uncontrolled Keywords: | 0201 Astronomical and Space Sciences; Astronomy & Astrophysics |
| Subjects: | Q Science > QB Astronomy Q Science > QC Physics |
| Divisions: | Astrophysics Research Institute |
| Publisher: | Oxford University Press (OUP) |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 20 Apr 2023 11:41 |
| Last Modified: | 20 Apr 2023 11:41 |
| DOI or ID number: | 10.1093/mnras/stab3325 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/19280 |
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