Parameter estimation for scarce stellar populations

Abstract

We present a Bayesian method to determine simultaneously the age, metallicity, distance modulus, and interstellar reddening by dust of any resolved stellar population, by comparing the observed and synthetic color magnitude diagrams on a star by star basis, with no need to bin the data into a carefully selected magnitude grid. We test the method with mock stellar populations, and show that it works correctly even for scarce stellar populations with only one or two hundred stars above the main sequence turn off. If the population is the result of two star formation bursts, we can infer the contribution of each event to the total stellar population. The code works automatically and has already been used to study massive amounts of Magellanic clouds photometric data. In this paper we analyze in detail three Large Magellanic Cloud star clusters and 6 Ultra Faint Dwarf Galaxies. For these galaxies we recover physical parameters in agreement with those quoted in the literature, age ∼ 13.7 Gyr and a very low metallicity log Z ∼ −4. Searching for multiple populations in these galaxies, we find, at a very low significance level, signs of a double stellar population for Ursa Major I: a dominant old population and a younger one which contributes ∼ 25% of the stars, in agreement with independent results from other authors.

Star cluster survival in dark matter halos: An old cluster in Eridanus II?

“…The case of galaxies with several bursts of star formation but poorly populated CMDs is particularly challenging since the number of free parameters is large enough to make binning methods unappealing (Ramírez-Siordia et al 2019).…”

“…The variety of age estimates for the stars in this galaxy motivates our study. To characterize the SFH of Eri II we avoid the isochrone fitting to the CMD and other data binning techniques, especially unappealing for sparse populations, that have been used frequently in the literature (Ramírez-Siordia et al 2019). We opt for Bayesian inference, which allows us to estimate not only the physical parameters describing a stellar population but also their uncertainties.…”

Self-consistent Analysis of Stellar Clusters: An Application to HST Data of the Halo Globular Cluster NGC 6752

“…There are no differences between the isochrones in the databases employed in SIRIUS for the faintest stars (∼ 2 magnitudes below the TO), therefore the fit does not depend on the faintest stars. Ramírez-Siordia et al (2019) presented an analysis considering the faintest stars. They concluded that the effect of faintest stars only increases the uncertain-ties without changing the mode of distribution, since the isochrones do not seem to be different for the faintest stars, as shown in Figure 2 (third panel).…”

“…The total likelihood ln P(M|D) is a linear combination of the priors and the likelihood of each stellar population with influence of SSP parameters: where f [i]G represents the fraction of stars that belong to the i-th population. A similar likelihood based on MPs and weighted by the fraction of stars is applied in Ramírez-Siordia et al (2019).…”

“…Recent examples of isochrone fitting codes using Bayesian inference are ASteCA (Perren et al 2015) and BASE-9 (Stenning et al 2016), where the latter allows analysis of MPs to derive their difference on the helium content (Y). Ramírez-Siordia et al (2019) also applied the Bayes' theorem to a Monte Carlo method to get the posterior distributions of the same parameters as BASE-9, neglecting helium enhancements. They applied their software to the scarce stellar populations of ultra-faint dwarf galaxies and LMC star clusters.…”