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تسجيل مستخدم جديدA transdimensional Bayesian method to infer the star formation history of resolved stellar populations
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We propose a new method to infer the star formation histories of resolved stellar populations. With photometry one may plot observed stars on a colour-magnitude diagram (CMD) and then compare with synthetic CMDs representing different star formation histories. This has been accomplished hitherto by parametrising the model star formation history as a histogram, usually with the bin widths set by fixed increases in the logarithm of time. A best fit is then found with maximum likelihood methods and we consider the different means by which a likelihood can be calculated. We then apply Bayesian methods by parametrising the star formation history as an unknown number of Gaussian bursts with unknown parameters. This parametrisation automatically provides a smooth function of time. A Reversal Jump Markov Chain Monte Carlo method is then used to find both the most appropriate number of Gaussians, thus avoiding avoid overfitting, and the posterior probability distribution of the star formation rate. We apply our method to artificial populations and to observed data. We discuss the other advantages of the method: direct comparison of different parametrisations and the ability to calculate the probability that a given star is from a given Gaussian. This allows the investigation of possible sub-populations.
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We present a new method to determine the star formation and metal enrichment histories of any resolved stellar system. This method is based on the fact that any observed star in a colour-magnitude diagram will have a certain probability of being asso
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Eric E. Martinez-Garcia
, Gustavo Bruzual
, Gladis Magris C. andn Rosa A. Gonzalez-Lopezlira
2017
We have obtained the time and space-resolved star formation history (SFH) of M51a (NGC 5194) by fitting GALEX, SDSS, and near infrared pixel-by-pixel photometry to a comprehensive library of stellar population synthesis models drawn from the Syntheti
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A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are > $10^9$ photometrically cataloged sources, yet modern spectroscopic surveys are limited to ~few x $10^6$ targets. As we approach the
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