The GALAH Survey: Stellar parameters and abundances for 800 000 Gaia RVS spectra using GALAH DR4 and The Cannon

Pradosh Barun Das; Daniel B. Zucker; Gayandhi M. De Silva; Nicholas W. Borsato; Aldo Andres Mura Guzmán; Sven Buder; Melissa Ness; Thomas Nordlander; Andrew R. Casey; Sarah L. Martell; Joss Bland-Hawthorn; Richard de Grijs; Ken C. Freeman; Janez Kos; Dennis Stello; Geraint F. Lewis; Michael R. Hayden; Sanjib Sharma

doi:10.1093/mnras/staf169

The GALAH Survey: Stellar parameters and abundances for 800 000 Gaia RVS spectra using GALAH DR4 and The Cannon

Pradosh Barun Das, Daniel B. Zucker, Gayandhi M. De Silva, Nicholas W. Borsato, Aldo Andres Mura Guzmán, Sven Buder, Melissa Ness, Thomas Nordlander, Andrew R. Casey, Sarah L. Martell, Joss Bland-Hawthorn, Richard de Grijs, Ken C. Freeman, Janez Kos, Dennis Stello, Geraint F. Lewis, Michael R. Hayden, Sanjib Sharma

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Abstract

Analysing stellar parameters and abundances from nearly one million Gaia Data Release 3 (DR3) Radial Velocity Spectrometer (RVS) spectra poses challenges due to the limited spectral coverage (restricted to the infrared Ca II triplet) and variable signal-to-noise ratios of the data. To address this, we use The Cannon, a data-driven method, to transfer stellar parameters and abundances from the GALAH (GALactic Archaeology with HERMES) DR4 (R ∼ 28 000) catalogue to the lower resolution Gaia DR3 RVS spectra (R ∼ 11 500). Our model, trained on 14 484 common targets, predicts parameters such as Teff , log g, and [Fe/H],
along with several other elements across approximately 800 000 Gaia RVS spectra. We utilize stars from open and globular clusters present in the Gaia RVS catalogue to validate our predicted mean [Fe/H] with high precision (∼ 0.02−0.10 dex). Additionally, we recover the bimodal distribution of [Ti/Fe] versus [Fe/H], reflecting the high and low α-components of Milky Way disc stars, demonstrating The Cannon’s capability for accurate stellar abundance determination from medium-resolution Gaia RVS spectra. The methodologies and resultant catalogue presented in this work highlight the remarkable potential of the RVS data set, which by the end of the Gaia mission will comprise spectra of over 200 million stars.

Original language	English
Pages (from-to)	605-621
Number of pages	17
Journal	Monthly Notices of the Royal Astronomical Society
Volume	538
Issue number	2
DOIs	https://doi.org/10.1093/mnras/staf169
Publication status	Published - Apr 2025

Bibliographical note

© 2025 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

methods: data analysis
methods: statistical
techniques: spectroscopic
surveys
stars: abundances
stars: fun- damental parameters

Access to Document

10.1093/mnras/staf169Licence: CC BY

Publisher version (open access)Final published version, 22.3 MBLicence: CC BY

Cite this

Das, P. B., Zucker, D. B., De Silva, G. M., Borsato, N. W., Mura Guzmán, A. A., Buder, S., Ness, M., Nordlander, T., Casey, A. R., Martell, S. L., Bland-Hawthorn, J., de Grijs, R., Freeman, K. C., Kos, J., Stello, D., Lewis, G. F., Hayden, M. R., & Sharma, S. (2025). The GALAH Survey: Stellar parameters and abundances for 800 000 Gaia RVS spectra using GALAH DR4 and The Cannon. Monthly Notices of the Royal Astronomical Society, 538(2), 605-621. https://doi.org/10.1093/mnras/staf169

@article{32215992918043d187fcf43dc334e16d,

title = "The GALAH Survey: Stellar parameters and abundances for 800 000 Gaia RVS spectra using GALAH DR4 and The Cannon",

abstract = "Analysing stellar parameters and abundances from nearly one million Gaia Data Release 3 (DR3) Radial Velocity Spectrometer (RVS) spectra poses challenges due to the limited spectral coverage (restricted to the infrared Ca II triplet) and variable signal-to-noise ratios of the data. To address this, we use The Cannon, a data-driven method, to transfer stellar parameters and abundances from the GALAH (GALactic Archaeology with HERMES) DR4 (R ∼ 28 000) catalogue to the lower resolution Gaia DR3 RVS spectra (R ∼ 11 500). Our model, trained on 14 484 common targets, predicts parameters such as Teff , log g, and [Fe/H], along with several other elements across approximately 800 000 Gaia RVS spectra. We utilize stars from open and globular clusters present in the Gaia RVS catalogue to validate our predicted mean [Fe/H] with high precision (∼ 0.02−0.10 dex). Additionally, we recover the bimodal distribution of [Ti/Fe] versus [Fe/H], reflecting the high and low α-components of Milky Way disc stars, demonstrating The Cannon{\textquoteright}s capability for accurate stellar abundance determination from medium-resolution Gaia RVS spectra. The methodologies and resultant catalogue presented in this work highlight the remarkable potential of the RVS data set, which by the end of the Gaia mission will comprise spectra of over 200 million stars.",

keywords = "methods: data analysis, methods: statistical, techniques: spectroscopic, surveys, stars: abundances, stars: fun- damental parameters",

author = "Das, {Pradosh Barun} and Zucker, {Daniel B.} and {De Silva}, {Gayandhi M.} and Borsato, {Nicholas W.} and {Mura Guzm{\'a}n}, {Aldo Andres} and Sven Buder and Melissa Ness and Thomas Nordlander and Casey, {Andrew R.} and Martell, {Sarah L.} and Joss Bland-Hawthorn and {de Grijs}, Richard and Freeman, {Ken C.} and Janez Kos and Dennis Stello and Lewis, {Geraint F.} and Hayden, {Michael R.} and Sanjib Sharma",

note = "{\textcopyright} 2025 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",

year = "2025",

month = apr,

doi = "10.1093/mnras/staf169",

language = "English",

volume = "538",

pages = "605--621",

journal = "Monthly Notices of the Royal Astronomical Society",

issn = "1365-2966",

publisher = "Oxford University Press",

number = "2",

}

Das, PB , Zucker, DB , De Silva, GM , Borsato, NW , Mura Guzmán, AA, Buder, S, Ness, M, Nordlander, T, Casey, AR, Martell, SL, Bland-Hawthorn, J, de Grijs, R, Freeman, KC, Kos, J, Stello, D, Lewis, GF, Hayden, MR & Sharma, S 2025, 'The GALAH Survey: Stellar parameters and abundances for 800 000 Gaia RVS spectra using GALAH DR4 and The Cannon', Monthly Notices of the Royal Astronomical Society, vol. 538, no. 2, pp. 605-621. https://doi.org/10.1093/mnras/staf169

TY - JOUR

T1 - The GALAH Survey

T2 - Stellar parameters and abundances for 800 000 Gaia RVS spectra using GALAH DR4 and The Cannon

AU - Das, Pradosh Barun

AU - Zucker, Daniel B.

AU - De Silva, Gayandhi M.

AU - Borsato, Nicholas W.

AU - Mura Guzmán, Aldo Andres

AU - Buder, Sven

AU - Ness, Melissa

AU - Nordlander, Thomas

AU - Casey, Andrew R.

AU - Martell, Sarah L.

AU - Bland-Hawthorn, Joss

AU - de Grijs, Richard

AU - Freeman, Ken C.

AU - Kos, Janez

AU - Stello, Dennis

AU - Lewis, Geraint F.

AU - Hayden, Michael R.

AU - Sharma, Sanjib

N1 - © 2025 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2025/4

Y1 - 2025/4

N2 - Analysing stellar parameters and abundances from nearly one million Gaia Data Release 3 (DR3) Radial Velocity Spectrometer (RVS) spectra poses challenges due to the limited spectral coverage (restricted to the infrared Ca II triplet) and variable signal-to-noise ratios of the data. To address this, we use The Cannon, a data-driven method, to transfer stellar parameters and abundances from the GALAH (GALactic Archaeology with HERMES) DR4 (R ∼ 28 000) catalogue to the lower resolution Gaia DR3 RVS spectra (R ∼ 11 500). Our model, trained on 14 484 common targets, predicts parameters such as Teff , log g, and [Fe/H], along with several other elements across approximately 800 000 Gaia RVS spectra. We utilize stars from open and globular clusters present in the Gaia RVS catalogue to validate our predicted mean [Fe/H] with high precision (∼ 0.02−0.10 dex). Additionally, we recover the bimodal distribution of [Ti/Fe] versus [Fe/H], reflecting the high and low α-components of Milky Way disc stars, demonstrating The Cannon’s capability for accurate stellar abundance determination from medium-resolution Gaia RVS spectra. The methodologies and resultant catalogue presented in this work highlight the remarkable potential of the RVS data set, which by the end of the Gaia mission will comprise spectra of over 200 million stars.

AB - Analysing stellar parameters and abundances from nearly one million Gaia Data Release 3 (DR3) Radial Velocity Spectrometer (RVS) spectra poses challenges due to the limited spectral coverage (restricted to the infrared Ca II triplet) and variable signal-to-noise ratios of the data. To address this, we use The Cannon, a data-driven method, to transfer stellar parameters and abundances from the GALAH (GALactic Archaeology with HERMES) DR4 (R ∼ 28 000) catalogue to the lower resolution Gaia DR3 RVS spectra (R ∼ 11 500). Our model, trained on 14 484 common targets, predicts parameters such as Teff , log g, and [Fe/H], along with several other elements across approximately 800 000 Gaia RVS spectra. We utilize stars from open and globular clusters present in the Gaia RVS catalogue to validate our predicted mean [Fe/H] with high precision (∼ 0.02−0.10 dex). Additionally, we recover the bimodal distribution of [Ti/Fe] versus [Fe/H], reflecting the high and low α-components of Milky Way disc stars, demonstrating The Cannon’s capability for accurate stellar abundance determination from medium-resolution Gaia RVS spectra. The methodologies and resultant catalogue presented in this work highlight the remarkable potential of the RVS data set, which by the end of the Gaia mission will comprise spectra of over 200 million stars.

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KW - methods: statistical

KW - techniques: spectroscopic

KW - surveys

KW - stars: abundances

KW - stars: fun- damental parameters

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