Testing the chemical tagging technique with open clusters ^⋆

¹ CNRS/Univ. Bordeaux, LAB, UMR 5804, 33270 Floirac, France
² Observatoire de Genève, Université de Genève, 1290 Versoix, Switzerland
e-mail: Sergi.Blanco@unige.ch
³ Department of Physics and Astronomy, Uppsala University, Box 516, 75120 Uppsala, Sweden
⁴ Research School of Astronomy and Astrophysics, Australian National University, ACT 2601, Australia
⁵ ESO, Alonso de Cordova 3107, Casilla 19001, Santiago de Chile, Chile
⁶ Instituto de Astrofísica de Andalucía-CSIC, Apdo. 3004, 18080 Granada, Spain
⁷ Lund Observatory, Department of Astronomy and Theoretical Physics, Box 43, 221 00 Lund, Sweden
⁸ Dpto. Astrofísica, Facultad de CC. Físicas, Universidad Complutense de Madrid, 28040 Madrid, Spain
⁹ Instituto de Astrofísica de Canarias, 38205 La Laguna, Tenerife, Spain
¹⁰ Universidad de La Laguna, Dept. Astrofísica, 38206 La Laguna, Tenerife, Spain
¹¹ Centro de Astrobiología (INTA-CSIC), Dpto. de Astrofísica, PO Box 78, 28691 Villanueva de la Cañada, Madrid, Spain
¹² Suffolk University, Madrid Campus, C/ Valle de la Viña 3, 28003 Madrid, Spain
¹³ Centro de Estudios de Física del Cosmos de Aragon, Plaza San Juan 1, Planta-2, 44001 Teruel, Spain
¹⁴ Institute of Theoretical Physics and Astronomy, Vilnius University, Gostauto 12, 01108 Vilnius, Lithuania

Received: 28 October 2014
Accepted: 20 February 2015

Abstract

Context. Stars are born together from giant molecular clouds and, if we assume that the priors were chemically homogeneous and well-mixed, we expect them to share the same chemical composition. Most of the stellar aggregates are disrupted while orbiting the Galaxy and most of the dynamic information is lost, thus the only possibility of reconstructing the stellar formation history is to analyze the chemical abundances that we observe today.

Aims. The chemical tagging technique aims to recover disrupted stellar clusters based merely on their chemical composition. We evaluate the viability of this technique to recover co-natal stars that are no longer gravitationally bound.

Methods. Open clusters are co-natal aggregates that have managed to survive together. We compiled stellar spectra from 31 old and intermediate-age open clusters, homogeneously derived atmospheric parameters, and 17 abundance species, and applied machine learning algorithms to group the stars based on their chemical composition. This approach allows us to evaluate the viability and efficiency of the chemical tagging technique.

Results. We found that stars at different evolutionary stages have distinct chemical patterns that may be due to NLTE effects, atomic diffusion, mixing, and biases. When separating stars into dwarfs and giants, we observed that a few open clusters show distinct chemical signatures while the majority show a high degree of overlap. This limits the recovery of co-natal aggregates by applying the chemical tagging technique. Nevertheless, there is room for improvement if more elements are included and models are improved.