Phylogenetic signal in spectroscopic surveys.
One of the main motivations to generate large spectroscopic surveys of Milky Way stars is to study the structure, formation and evolution of the Milky Way. There are several spectroscopic surveys available to the community today. We are very curious to analyze trees from such datasets and discover the past events that shaped the Milky Way as it is. We are applying phylogenetic techniques developed for other fossil records into stars, and are finding that the precision quoted by surveys is not sufficient for obtaining a robust phylogenetic signal. This finding is opposite to our previous works, in which we used high-precision stellar abundances to build phylogenetic trees. By applying a Machine Learning approach we’re improving the precision of spectroscopic surveys such that we can extract the phylogenetic signal across the Galactic disk. We’re furtherleading an observing campaign to follow-up survey data and provide high-precision abundances for building a training set.