Massive star population in the Sextans A dwarf galaxy from HST UV photometry
Year: 2026
Type: article
Abstract: ABSTRACT We build a catalogue of massive (M > 8 M$_\odot$) main-sequence stars in the metal-poor (${\sim} 0.1$ Z$_\odot$) dwarf irregular galaxy Sextans A. HST (Hubble Space Telescope) WFC3 (Wide Field Camera 3) ultraviolet (UV) photometry in the 275 and 336 nm wideband filters is arranged in a colour–magnitude diagram (CMD), and overlaid on top of stellar evolutionary tracks from the mist (mesa Isochrones and Stellar Tracks) library. The star properties (mass, age, etc.) are computed with a finite element (FE) interpolation of the stellar tracks. The FE method, originally developed to solve structural analysis problems, provides a general framework for interpolating fields inside domains of complex geometry. Besides the interpolated properties, the algorithm computes their gradients with respect to the photometry. These sensitivities yield a direct and efficient estimate of the associated uncertainties. Our catalogue contains 655 stars, with the most massive one estimated at $58\pm 11$ M$_\odot$. A comparison with a ground-based spectroscopic census of OB stars yields only eight matches, evidencing the minimal overlap between both data sets. The mass estimates derived from the UV CMD and the spectral classification are in good agreement for the majority of O-type stars found in both data sets. Our catalogue provides an extensive list of candidates for follow-up spectroscopic observation to improve our understanding of the early evolutionary stages of massive low-metallicity stars.
Authors: Roberto Flores, E Fantino, G Battaglia, A Aparicio
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,046
Funders: National Aeronautics and Space Administration, Albert Ellis Institute, University of Kansas, Ministerio de Ciencia, Innovación y Universidades, Khalifa University of Science, Technology and Research, Ministerio de Ciencia e Innovación, European Regional Development Fund, Agencia Estatal de Investigación
OpenAlex ID: W7148408631
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