Estimating the age-metallicity distribution of a stellar sample from the probability distributions of the individual stars
Christian L. Sahlholdt, Lennart Lindegren

TL;DR
This paper introduces a novel algorithm that estimates the age-metallicity distribution of stellar populations using full probability density functions, improving accuracy over traditional methods and applicable to various parameter spaces.
Contribution
The paper presents a new algorithm that utilizes full PDFs of individual stars to accurately recover the age-metallicity distribution without assuming its shape.
Findings
The method outperforms traditional estimates in synthetic tests.
Application to the Geneva-Copenhagen survey reveals a potential minimum in star formation at 10 Gyr.
The algorithm is versatile and applicable to different parameter spaces and measurement techniques.
Abstract
Estimating age distributions, or star formation histories, of stellar populations in the Milky Way is important in order to study the evolution of trends in elemental abundances and kinematics. We build on previous work to develop an algorithm for estimating the age-metallicity distribution which uses the full age-metallicity probability density functions (PDFs) of individual stars. No assumptions are made about the shape of the underlying distribution, and the only free parameter of the algorithm is used to ensure a smooth solution. In this work we use individual age-metallicity PDFs from isochrone fitting of stars with known metallicities. The method is tested with synthetic samples and is found to recover the input age-metallicity distribution more accurately than the distribution of individually estimated ages and metallicities. The recovered sample age distribution is always more…
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