Semiresolved Stellar Populations as Distance Indicators
arXiv:2609.01400 · doi:10.3847/2041-8213/ae8d10
Abstract
Galaxy distances are central to our understanding of the Universe. Despite the success of existing approaches, independent and complementary methods remain valuable for testing systematic effects and extending the applicability range of different distance metrics. Here we demonstrate that the spectrum of an individual semi-resolved stellar population encodes direct information about its distance and that valuable distance constraints can, in principle, be obtained by combining multiple independent measurements. When applied to optical spectra of bulge of the Andromeda galaxy (M\,31), we derive a stellar population-based distance of 75657 kpc (), in agreement with state-of-the-art measurements. Crucially, semi-resolved stellar population distances does not require secondary calibrations, although its absolute scale remains conditional on the adopted stellar population models. Our findings provide a first assessment of the feasibility of deriving stellar population-based distance estimates from simple stellar population models, motivating further tests of the broader applicability and precision of the method.
5 pages, 4 figures. Accepted for publication in ApJL
References in corpus (9)
- Estimating distances from parallaxes. V: Geometric and photogeometric distances to 1.47 billion stars in Gaia Early Data Release 3
- The propagation of uncertainties in stellar population synthesis modeling I: The relevance of uncertain aspects of stellar evolution and the IMF to the derived physical properties of galaxies
- Measurements of the Hubble Constant: Tensions in Perspective
- Radial variations in the stellar initial mass function of early-type galaxies
- The Hubble Constant from Infrared Surface Brightness Fluctuation Distances
- A sub-2% Distance to M31 from Photometrically Homogeneous Near-Infrared Cepheid Period-Luminosity Relations Measured with the Hubble Space Telescope
- Deriving the star formation histories of galaxies from spectra with simulation-based inference
- ERGO-ML: Towards a robust machine learning model for inferring the fraction of accreted stars in galaxies from integral-field spectroscopic maps
- Looking beyond lambda