Climbing the cosmic ladder with stellar twins in RAVE with Gaia

P. Jofré*, G. Traven, K. Hawkins, G. Gilmore, J. L. Sanders, T. Mädler, M. Steinmetz, A. Kunder, G. Kordopatis, P. McMillan, O. Bienaymé, J. Bland-Hawthorn, B. K. Gibson, E. K. Grebel, U. Munari, J. Navarro, Q. Parker, W. Reid, G. Seabroke, T. Zwitter

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
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Abstract

We apply the twin method to determine parallaxes to 232 545 stars of the RAVE survey using the parallaxes of Gaia DR1 as a reference. To search for twins in this large data set, we apply the t-student stochastic neighbour embedding projection that distributes the data according to their spectral morphology on a two-dimensional map. From this map, we choose the twin candidates for which we calculate a χ2 to select the best sets of twins. Our results show a competitive performance when compared to other model-dependent methods relying on stellar parameters and isochrones. The power of the method is shown by finding that the accuracy of our results is not significantly affected if the stars are normal or peculiar since the method is model free. We find twins for 60 per cent of the RAVE sample that are not contained in Tycho-Gaia Astrometric Solution (TGAS) or that have TGAS uncertainties that are larger than 20 per cent. We could determine parallaxes with typical errors of 28 per cent. We provide a complementary data set for the RAVE stars not covered by TGAS, or that have TGAS uncertainties which are larger than 20 per cent, with model-free parallaxes scaled to the Gaia measurements.

Original languageEnglish
Pages (from-to)2517-2533
Number of pages17
JournalMonthly Notices of the Royal Astronomical Society
Volume472
Issue number3
DOIs
Publication statusPublished - 2017

Bibliographical note

Copyright 2017 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. First published in Monthly Notices of the Royal Astronomical Society, 472(3), pp.2517-2533. The original publication is available at https://doi.org/10.1093/mnras/stx1877. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • methods: statistical
  • techniques: spectroscopic
  • stars: distances

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