Photometric segregation of dwarf and giant FGK stars using the SVO Filter Profile Service and photometric tools

¹ Centro de Astrobiología (CAB), CSIC-INTA, Camino Bajo del Castillo s/n, 28692 Villanueva de la Cañada, Madrid, Spain
e-mail: pcruz@cab.inta-csic.es;esm@cab.inta-csic.es
² Departamento de Matemáticas, Universidad Militar Nueva Granada, kilómetro 2 vía Cajicá – Zipaquirá, 110111, Colombia
³ PhD Programme in Astrophysics, Doctoral School, Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049 Madrid, Spain
⁴ Observatorio Astronómico Nacional (OAN), Alfonso XII 3, 28014 Madrid, Spain
⁵ European Southern Observatory, Karl-Schwarzschild-Strasse 2, 85748 Garching bei München, Germany
⁶ Departamento de Física de la Tierra y Astrofísica, Facultad de Ciencias Físicas, e IPARCOS-UCM (Instituto de Física de Partículas y del Cosmos de la UCM), Universidad Complutense de Madrid, 28040 Madrid, Spain
⁷ Donostia International Physics Center (DIPC), Manuel Lardizabal Ibilbidea, 4, San Sebastián, Spain
⁸ Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Plaza San Juan, 1, E-44001, Teruel, Spain
⁹ Observatório Nacional, Rua General José Cristino, 77, São Cristóvão, 20921-400, Rio de Janeiro, RJ, Brazil
¹⁰ Departamento de Astronomia, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
¹¹ Instruments4, 4121 Pembury Place, La Canada Flintridge, CA 91011, U.S.A.

Received: 15 March 2024
Accepted: 20 May 2024

Abstract

Aims. This paper is focused on the segregation of FGK dwarf and giant stars through narrow-band photometric data using the Spanish Virtual Observatory (SVO) Filter Profile Service and associated photometric tools.

Methods. We selected spectra from the MILES, STELIB, and ELODIE stellar libraries, and used SVO photometric tools to derive the synthetic photometry in 15 J-PAS narrow filters, which were especially selected to cover spectral features sensitive to gravity changes. Using machine-learning techniques as the Gaussian mixture model and the support vector machine, we defined several criteria based on J-PAS colours to discriminate between dwarf and giant stars.

Results. We selected five colour-colour diagrams that presented the most promising separation between both samples. Our results show an overall accuracy in the studied sample of ~0.97 for FGK stars, although a dependence on the luminosity type and the stellar effective temperature was found. We also defined a colour-temperature relation for dwarf stars with effective temperatures between 4 000 and 7 000 K, which allows one to estimate the stellar effective temperature from four J-PAS filters (J0450, J0510, J0550, and J0620). Additionally, we extended the study to M-type giant and dwarf stars, achieving a similar accuracy to that for FGK stars.