NGC 1856: Using Machine Learning Techniques to Uncover Detailed Stellar Abundances from MUSE Data

Randa Asa’d; S. Hernandez; J. M John; M. Alfaro-Cuello; Z. Wang; A. As’ad; A. Vasini; F. Matteucci

doi:10.3847/1538-3881/ad3f1b

The Astronomical Journal (Jan 2024)

NGC 1856: Using Machine Learning Techniques to Uncover Detailed Stellar Abundances from MUSE Data

Randa Asa’d,
S. Hernandez,
J. M John,
M. Alfaro-Cuello,
Z. Wang,
A. As’ad,
A. Vasini,
F. Matteucci

Affiliations

Randa Asa’d: ORCiD; American University of Sharjah , Physics Department, P.O. Box 26666, Sharjah, UAE ; [email protected]
S. Hernandez: AURA for ESA, Space Telescope Science Institute , 3700 San Martin Drive, Baltimore, MD 21218, USA
J. M John: American University of Sharjah , Physics Department, P.O. Box 26666, Sharjah, UAE ; [email protected]
M. Alfaro-Cuello: Facultad de Ingeniería y Arquitectura, Universidad Central de Chile , Av. Francisco de Aguirre 0405, La Serena, Coquimbo, Chile; Space Telescope Science Institute , 3700 San Martin Drive, Baltimore, MD 21218, USA
Z. Wang: Sydney Institute for Astronomy, School of Physics, A28, The University of Sydney , NSW, 2006, Australia; ARC Centre of Excellence for All Sky Astrophysics in Three Dimensions (ASTRO-3D) , Australia
A. As’ad: College of Wooster , Department of Mathematical and Computational Sciences, 1189 Beall Avenue, Wooster, OH 44691, USA
A. Vasini: Dipartimento di Fisica, Sezione di Astronomia, Università degli studi di Trieste , Via G.B. Tiepolo 11, I-34143 Trieste, Italy
F. Matteucci: ORCiD; Dipartimento di Fisica, Sezione di Astronomia, Università degli studi di Trieste , Via G.B. Tiepolo 11, I-34143 Trieste, Italy; INAF, Osservatorio Astronomico di Trieste , Via Tiepolo 11, I-34131 Trieste, Italy; INFN, Sezione di Trieste , Via Valerio 2, I.34127 Trieste, Italy

DOI: https://doi.org/10.3847/1538-3881/ad3f1b
Journal volume & issue: Vol. 167, no. 6
p. 265

Abstract

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We present the first application of the novel approach based on data-driven machine learning methods applied to Multi-Unit Spectroscopic Explorer (MUSE) field data to derive stellar abundances of star clusters. MUSE has been used to target more than 10,000 fields, and it is unique in its ability to study dense stellar fields such as stellar clusters providing spectra for each individual star. We use MUSE data of the extragalactic young stellar cluster NGC 1856, located in the Large Magellanic Cloud (LMC). We present the individual stellar [Fe/H] abundance of 327 cluster members in addition to [Mg/Fe], [Si/Fe], [Ti/Fe], [C/Fe], [Ni/Fe], and [Cr/Fe] abundances of subsample sets. Our results match the LMC abundances obtained in the literature for [Mg/Fe], [Ti/Fe], [Ni/Fe], and [Cr/Fe]. This study is the first to derive [Si/Fe] and [C/Fe] abundances for this cluster. The revolutionary combination of integral-field spectroscopy and data-driven modeling will allow us to understand the chemical enrichment of star clusters and their host galaxies in greater detail expanding our understanding of galaxy evolution.

Published in The Astronomical Journal

ISSN: 0004-6256 (Print); 1538-3881 (Online)
Publisher: IOP Publishing
Country of publisher: United Kingdom
LCC subjects: Science: Astronomy
Website: https://iopscience.iop.org/journal/1538-3881

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