Climbing the cosmic ladder with stellar twins in RAVE with Gaia

• Verfasst von: Jofré Pfeil, Paula [VerfasserIn]
• Verfasst von: Grebel, Eva K. [VerfasserIn]
• Titel: Climbing the cosmic ladder with stellar twins in RAVE with Gaia
• Verf.angabe: P. Jofre, G. Traven, K. Hawkins, G. Gilmore, J.L. Sanders, T. Maedler, M. Steinmetz, A. Kunder, G. Kordopatis, P. McMillan, O. Biename, J. Bland-Hawthorn, B.K. Gibson, E.K. Grebel, U. Munari, J. Navarro, Q. Parker, W. Reid, G. Seabroke, T. Zwitter
• Fussnoten: Gesehen am 17.10.2017
• Titel Quelle: Enthalten in: De.arxiv.org
• Jahr Quelle: 2017
• Band/Heft Quelle: (2017) Artikel-Nummer 1705.11049, 18 Seiten
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1564469867

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 dataset, we apply the t-stochastic neighbour embedding t-SNE projection which 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 chi^2 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% of the RAVE sample which is not contained in TGAS or that have TGAS uncertainties which are larger than 20%. We could determine parallaxes with typical errors of 28%. We provide a complementary dataset for the RAVE stars not covered by TGAS, or that have TGAS uncertainties which are larger than 20%, with model-free parallaxes scaled to the Gaia measurements.