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Climbing the cosmic ladder with stellar twins in RAVE with Gaia

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


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

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Professor Brad Gibson
Head of Dept, Physics & Maths; Director, E.A. Milne Centre for Astrophysics

E. K. Grebel

U. Munari

J. Navarro

Q. Parker

W. Reid

G. Seabroke

T. Zwitter


© 2017 The Author. 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 χ2to 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.


Jofré, P., Traven, G., Hawkins, K., Gilmore, G., Sanders, J. L., Mädler, T., …Zwitter, T. (2017). Climbing the cosmic ladder with stellar twins in RAVE with Gaia. Monthly notices of the Royal Astronomical Society, 472(3), 2517-2533.

Journal Article Type Article
Acceptance Date Jul 20, 2017
Online Publication Date Aug 14, 2017
Publication Date 2017-12
Deposit Date Jun 28, 2018
Publicly Available Date Jul 12, 2018
Journal Monthly Notices of the Royal Astronomical Society
Print ISSN 0035-8711
Electronic ISSN 1365-2966
Publisher Oxford University Press
Peer Reviewed Peer Reviewed
Volume 472
Issue 3
Pages 2517-2533
Keywords Stars : distances; Techniques : spectroscopic; Methods : statistical
Public URL
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