Optimised use of interferometry, spectroscopy, and stellar atmosphere models for determining the fundamental parameters of stars

¹ Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, France
² Max Plank Institute for Astronomy, 69117 Heidelberg, Germany
³ Niels Bohr International Academy, NBI, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen, Denmark
⁴ Space Sciences, Technologies and Astrophysics Research (STAR) Institute, Université de Liège, Quartier Agora, Allée du 6 Août 19c, Bât. B5C, 4000 Liège, Belgium
⁵ Instituto de Astrofísica de Andalucía (IAA-CSIC), Glorieta de la Astronomía s/n, 18008 Granada, Spain
⁶ INAF- Palermo Astronomical Observatory, Piazza del Parlamento, 1, 90134 Palermo, Italy
⁷ LUPM, Univ Montpellier, CNRS, Montpellier, France
⁸ Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse, CNRS, IRAP/UMR 5277, 14 Avenue Édouard Belin, 31400 Toulouse, France

^★ Corresponding author; nayeem.ebrahimkutty@oca.eu

Received: 23 March 2024
Accepted: 27 September 2024

Abstract

Context. Thanks to recent progress in the field of optical interferometry, instrument sensitivities have now reached the level achieved in the domain of new space missions dedicated to exoplanet and stellar studies. Combining interferometry with other observational approaches enables the determination of stellar parameters and helps improve our understanding of stellar physics.

Aims. In this paper, we aim to demonstrate a new way of using stellar atmosphere models for a joint interpretation of spectroscopic and interferometric observations.

Methods. Starting from a discrete grid of one-dimensional (1D) stellar atmosphere models, we developed a training algorithm, based on an artificial neural network, capable of estimating the spectrum and intensity profile of a star over a range of wavelengths and viewing angles. A minimisation algorithm based on the trained function allowed for the simultaneous fitting of the observational spectrum and interferometric complex visibilities. As a result, coherent and precise stellar parameters can be extracted.

Results. We show the ability of the trained function to match the modelled intensity profiles of stars in the effective temperature range of 4500–7000 K and surface gravity range of 3 to 5 dex, with a relative precision to the model that is better than 0.05%. Using simulated interferometric data and actual spectroscopic measurements, we demonstrated the performance of our algorithm on a sample of five benchmark stars. Using this method, we achieved an accuracy within 0.5% for the angular diameter, radius, and surface gravity, and within 20 K for the effective temperature.

Conclusions. This paper demonstrates a new method of using interferometric data combined with spectroscopic observations. This approach offers an improved determination of the radius, effective temperature, and surface gravity of stars.