StarHorse: A Bayesian tool for determining stellar masses, ages, distances, and extinctions for field stars
Anna B. A. Queiroz, Friedrich Anders, Bas\'ilio X. Santiago, Cristina, Chiappini, Matthias Steinmetz, Marina Dal Ponte, Keivan G. Stassun, Luiz N., da Costa, Marcio A. G. Maia, Timothy C. Beers, Juliana Crestani, J. G., Fern\'andez-Trincado, Domingo An\'ibal Garc\'ia-Hern\'andez

TL;DR
StarHorse is a Bayesian tool that estimates stellar distances, ages, masses, and extinctions for field stars using spectro-photometric data, validated with simulations and real star measurements, enhancing Galactic evolution studies.
Contribution
The paper introduces updates to the StarHorse code, enabling simultaneous estimation of multiple stellar parameters with flexible data integration and validation against various datasets.
Findings
Achieves ~8% distance precision for simulated stars.
Provides age estimates with ~20% accuracy.
Offers distances and extinctions for major stellar surveys.
Abstract
Understanding the formation and evolution of our Galaxy requires accurate distances, ages and chemistry for large populations of field stars. Here we present several updates to our spectro-photometric distance code, that can now also be used to estimate ages, masses, and extinctions for individual stars. Given a set of measured spectro-photometric parameters, we calculate the posterior probability distribution over a given grid of stellar evolutionary models, using flexible Galactic stellar-population priors. The code (called {\tt StarHorse}) can acommodate different observational datasets, prior options, partially missing data, and the inclusion of parallax information into the estimated probabilities. We validate the code using a variety of simulated stars as well as real stars with parameters determined from asteroseismology, eclipsing binaries, and isochrone fits to star clusters.…
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