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arXiv · 1409.2275

New Observational Constraints to Milky Way Chemodynamical models

Cristina Chiappini·Ivan Minchev·Friedrich Anders·Dorothee Brauer·Corrado Boeche·Marie Martig
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Abstract

Galactic Archaeology, i.e. the use of chemo-dynamical information for stellar samples covering large portions of the Milky Way to infer the dominant processes involved in its formation and evolution, is now a powerful method thanks to the large recently completed and ongoing spectroscopic surveys. It is now important to ask the right questions when analyzing and interpreting the information contained in these rich datasets. To this aim, we have developed a chemodynamical model for the Milky Way that provides quantitative predictions to be compared with the chemo-kinematical properties extracted from the stellar spectra. Three key parameters are needed to make the comparison between data and model predictions useful in order to advance in the field, namely: precise proper-motions, distances and ages. The uncertainties involved in the estimate of ages and distances for field stars are currently the main obstacles in the Galactic Archaeology method. Two important developments might change this situation in the near future: asteroseismology and the now launched Gaia. When combined with the large datasets from surveys like RAVE, SEGUE, LAMOST, Gaia-ESO, APOGEE , HERMES and the future 4MOST we will have the basic ingredients for the reconstruction of the MW history in hands. In the light of these observational advances, the development of detailed chemo-dynamical models tailored to the Milky Way is urgently needed in the field. Here we show the steps we have taken, both in terms of data analysis and modelling. The examples shown here illustrate how powerful can the Galactic Archaeology method become once ages and distances are known with better precision than what is currently feasible.

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Cristina Chiappini, Ivan Minchev, Friedrich Anders, Dorothee Brauer, Corrado Boeche, Marie Martig. 2014-09-08. New Observational Constraints to Milky Way Chemodynamical models. https://doi.org/10.1007/978-3-319-10993-0_13

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