Assembling a high-precision abundance catalogue of solar twins in GALAH for phylogenetic studies

TL;DR

This study creates a high-precision chemical abundance catalogue of solar twins from GALAH data, applying machine learning and phylogenetics to uncover Milky Way evolutionary history.

Contribution

It introduces a new catalogue of 40,000 solar twins with high-precision abundances and demonstrates the use of phylogenetic analysis for galactic archaeology.

Findings

Identified a star group with circular orbits and old stars with eccentric orbits.

Confirmed age-[Y/Mg] relation consistent with previous chemical clocks.

Showed the effectiveness of combining survey data, machine learning, and phylogenetics.

Abstract

Stellar chemical abundances have proved themselves a key source of information for understanding the evolution of the Milky Way, and the scale of major stellar surveys such as GALAH have massively increased the amount of chemical data available. However, progress is hampered by the level of precision in chemical abundance data as well as the visualization methods for comparing the multidimensional outputs of chemical evolution models to stellar abundance data. Machine learning methods have greatly improved the former; while the application of tree-building or phylogenetic methods borrowed from biology are beginning to show promise with the latter. Here we analyse a sample of GALAH solar twins to address these issues. We apply The Cannon algorithm to generate a catalogue of about 40,000 solar twins with 14 high precision abundances which we use to perform a phylogenetic analysis on a selection of stars that have two different ranges of eccentricities. From our analyses we are able to find a group with mostly stars on circular orbits and some old stars with eccentric orbits whose age-[Y/Mg] relation agrees remarkably well with the chemical clocks published by previous high precision abundance studies. Our results show the power of combining survey data with machine learning and phylogenetics to reconstruct the history of the Milky Way.