The GALAH survey: Improving chemical abundances using star clusters

¹ Faculty of mathematics and physics, University of Ljubljana, Jadranska 19, 1000 Ljubljana, Slovenia
² Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611, Australia
³ ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Australia
⁴ ACCESS-NRI, Australian National University, Canberra, ACT2601, Australia
⁵ Sydney Institute for Astronomy, School of Physics, A28, The University of Sydney, NSW 2006, Australia
⁶ Australian Astronomical Optics, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2113, Australia
⁷ Department of Physics, University of Rome Tor Vergata, via della ricerca scientifica 1, 00133, Rome, Italy
⁸ Homer L. Dodge Department of Physics & Astronomy, University of Oklahoma, 440 W. Brooks St., Norman, OK 73019, USA
⁹ School of Physics, University of New South Wales, Sydney, NSW 2052, Australia
¹⁰ Department of Astronomy, Stockholm University, AlbaNova University Centre, 106 91 Stockholm, Sweden
¹¹ Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD, 21218, USA
¹² School of Mathematical and Physical Sciences, Macquarie University, Balaclava Road, Sydney, NSW 2109, Australia
¹³ Astrophysics and Space Technologies Research Centre, Macquarie University, Balaclava Road, Sydney, NSW 2109, Australia
¹⁴ International Space Science Institute Beijing, 1 Nanertiao, Zhongguancun, Beijing 100190, China
¹⁵ School of Physics and Astronomy, Monash University, Clayton, VIC 3800, Australia
¹⁶ Theoretical Astrophysics, Department of Physics and Astronomy, Uppsala University, Box 516, 751 20 Uppsala, Sweden
¹⁷ Stellar Astrophysics Centre, Aarhus University, Ny Munkegade 120, 8000 Aarhus C, Denmark

^★ Corresponding author: janez.kos@fmf.uni-lj.si

Received: 12 February 2025
Accepted: 16 August 2025

Abstract

Large spectroscopic surveys aim to consistently compute stellar parameters of very diverse stars, while minimizing systematic errors. We explore the use of stellar clusters as benchmarks to verify the precision of spectroscopic parameters in the fourth data release (DR4) of the GALAH survey. We examine 58 open and globular clusters and associations to validate measurements of temperature, gravity, chemical abundances, and stellar ages. We focus on identifying systematic errors and understanding trends between stellar parameters, particularly temperature and chemical abundances. We identify trends by stacking measurements of chemical abundances against effective temperature and modelling them with splines. We also re-fit spectra in three clusters with the Spectroscopy Made Easy and Korg packages to reproduce the trends in DR4 and to search for their origin by varying temperature and gravity priors, linelists, and the spectral continuum. Trends are consistent between clusters of different ages and metallicities, can reach amplitudes of ~0.5 dex, and differ for dwarfs and giants. We use the derived trends to correct the DR4 abundances of 24 and 31 chemical elements for dwarfs and giants, respectively, and publish a detrended catalogue. While the origin of the trends could not be pinpointed, we found that: (i) photometric priors affect derived abundances, (ii) temperature, metallicity, and continuum levels are degenerate in spectral fitting, and it is hard to break the degeneracy even by using independent measurements, (iii) the completeness of the linelist used in spectral synthesis is essential for cool stars, and (iv) different spectral fitting codes produce significantly different iron abundances for stars of all temperatures. We conclude that clusters can be used to characterise the systematic errors of parameters produced in large surveys, but further research is needed to explain the origin of the trends.