Stellar atmospheric parameters and chemical abundances of ∼5 million stars from S-PLUS multiband photometry

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Ferreira Lopes, C. E. ; Gutierrez-Soto, L. A. ; S. Ferreira Alberice, V. ; Monsalves, N. ; Hazarika, D. ; Catelan, M. ; Placco, V. M. ; Limberg, G. ; Almeida-Fernandes, F. ; Perottoni, H. D. ; Smith Castelli, A. V. ; Akras, S. ; Alonso-Garcia, J. ; Cordeiro, V. ; Jaque Arancibia, M. ; Daflon, S. ; Dias, B. ; Goncalves, D. R. ; Machado-Pereira, E. ; Lopes, A. R. ; Bom, C. R. ; Thom de Souza, R. C. ; de Isidio, N. G. ; Alvarez-Candal, A. ; De Rossi, M. E. ; Bonatto, C. J. ; Cubillos Palma, B. ; Borges Fernandes, M. ; Humire, P. K. ; Oliveira Schwarz, G. B. ; Schoenell, W. ; Kanaan, A. ; Mendes de Oliveira, C.

• Tipo de documento: Artigo Científico
• Fonte: Astronomy & Astrophysics; v. 693, p. 23-pg., 2025-01-28.

Resumo

Context. The APOGEE, GALAH, and LAMOST spectroscopic surveys have substantially contributed to our understanding of the Milky Way by providing a wide range of stellar parameters and chemical abundances. Complementing these efforts, photometric surveys that include narrowband and medium-band filters, such as Southern Photometric Local Universe Survey (S-PLUS), provide a unique opportunity to estimate the atmospheric parameters and elemental abundances for a much larger number of sources, compared to spectroscopic surveys. Aims. Our aim is to establish methodologies for extracting stellar atmospheric parameters and selected chemical abundances from S-PLUS photometric data, which cover approximately 3000 square degrees, by applying seven narrowband and five broadband filters. Methods. We used all 66 S-PLUS colors to estimate parameters based on three different training samples from the LAMOST, APOGEE, and GALAH surveys, applying cost-sensitive neural network (NN) and random forest (RF) algorithms. We kept the stellar abundances that lacked corresponding absorption features in the S-PLUS filters to test for spurious correlations in our method. Furthermore, we evaluated the effectiveness of the NN and RF algorithms by using estimated T-eff and log g values as the input features to determine other stellar parameters and abundances. The NN approach consistently outperforms the RF technique on all parameters tested. Moreover, incorporating T-eff and log g leads to an improvement in the estimation accuracy by approximately 3%. We kept only parameters with a goodness-of-fit higher than 50%. Results. Our methodology allowed us to obtain reliable estimates for fundamental stellar parameters (T-eff, log g, and [Fe/H]) and elemental abundance ratios such as [alpha/Fe], [Al/Fe], [C/Fe], [Li/Fe], and [Mg/Fe] for approximately five million stars across the Milky Way, with a goodness-of-fit above 60%. We also obtained additional abundance ratios, including [Cu/Fe], [O/Fe], and [Si/Fe]. However, these ratios should be used cautiously due to their low accuracy or lack of a clear relationship with the S-PLUS filters. Validation of our estimations and methods was performed using star clusters, Transiting Exoplanet Survey Satellite (TESS) data and Javalambre Photometric Local Universe Survey (J-PLUS) photometry, further demonstrating the robustness and accuracy of our approach. Conclusions. By leveraging S-PLUS photometric data and advanced machine learning techniques, we have established a robust framework for extracting fundamental stellar parameters and chemical abundances from medium-band and narrowband photometric observations. This approach offers a cost-effective alternative to high-resolution spectroscopy. The estimated parameters hold significant potential for future studies, particularly when classifying objects within our Milky Way or gaining insights into its various stellar populations. (AU)

• Processo FAPESP: 21/10429-0 - A estrutura quimiodinâmica do halo galáctico
• Beneficiário: Guilherme Limberg
• Modalidade de apoio: Bolsas no Brasil - Doutorado Direto
• Processo FAPESP: 18/20977-2 - Identificação de estrelas gigantes para mapeamento da Galáxia no levantamento S-PLUS
• Beneficiário: Felipe de Almeida Fernandes
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 23/14272-4 - Distribuição de energia espectral da galáxia NGC253, uma abordagem de alta resolução com vários comprimentos de onda
• Beneficiário: Pedro Kurmi Humire Rodríguez
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado