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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. and McMillan, P. LU orcid , et al. (2017) In Monthly Notices of the Royal Astronomical Society 472(3). p.2517-2533
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... (More)

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.

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publishing date
type
Contribution to journal
publication status
published
subject
keywords
Methods:statistical, Stars:distances, Techniques:spectroscopic
in
Monthly Notices of the Royal Astronomical Society
volume
472
issue
3
pages
17 pages
publisher
Oxford University Press
external identifiers
  • wos:000413088400001
  • scopus:85030550869
ISSN
0035-8711
DOI
10.1093/mnras/stx1877
language
English
LU publication?
yes
id
23376ea9-89c1-492e-b9ef-1ef32abbd1cc
date added to LUP
2017-10-17 08:15:32
date last changed
2024-02-13 09:06:39
@article{23376ea9-89c1-492e-b9ef-1ef32abbd1cc,
  abstract     = {{<p>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 χ<sup>2</sup> 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.</p>}},
  author       = {{Jofré, P. and Traven, G. and Hawkins, K. and Gilmore, G. and Sanders, J. L. and Mädler, T. and Steinmetz, M. and Kunder, A. and Kordopatis, G. and McMillan, P. and Bienaymé, O. and Bland-Hawthorn, J. and Gibson, B. K. and Grebel, E. K. and Munari, U. and Navarro, J. E. J. Garcia and Parker, Q. A. and Reid, W. A. and Seabroke, G. and Zwitter, T.}},
  issn         = {{0035-8711}},
  keywords     = {{Methods:statistical; Stars:distances; Techniques:spectroscopic}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{2517--2533}},
  publisher    = {{Oxford University Press}},
  series       = {{Monthly Notices of the Royal Astronomical Society}},
  title        = {{Climbing the cosmic ladder with stellar twins in RAVE with Gaia}},
  url          = {{http://dx.doi.org/10.1093/mnras/stx1877}},
  doi          = {{10.1093/mnras/stx1877}},
  volume       = {{472}},
  year         = {{2017}},
}