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

Kurt Walsen, Paula Jofré, Sven Buder, Keaghan Yaxley, Payel Das, Robert M Yates, Xia Hua, Theosamuele Signor, Camilla Eldridge, Alvaro Rojas-Arriagada, Patricia B Tissera, Evelyn Johnston, Claudia Aguilera-Gómez, Manuela Zoccali, Gerry Gilmore, Robert Foley

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Article numberstae280
Pages (from-to)2946-2966
Number of pages21
JournalMonthly Notices of the Royal Astronomical Society
Issue number3
Early online date27 Jan 2024
Publication statusPublished - 15 Apr 2024


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