Accurate parameter estimation for star formation history in galaxies using SDSS spectra

• Published in: Monthly notices of the Royal Astronomical Society Vol. 399; no. 2; pp. 1044 - 1057
• Main Authors: Richards, Joseph W., Freeman, Peter E., Lee, Ann B., Schafer, Chad M.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 21.10.2009; Wiley-Blackwell; Oxford University Press
• Subjects: Astronomy; Data analysis; Earth, ocean, space; Exact sciences and technology; galaxies: evolution; galaxies: formation; galaxies: stellar content; methods: data analysis; methods: numerical; Parameter estimation; Star & galaxy formation; Stars & galaxies; galaxies: formation; methods: data analysis; methods: numerical; galaxies: evolution; galaxies: stellar content; Galaxy evolution; Star light; Stellar spectra; Data analysis; Parameter estimation; Galaxies; Stellar content; Random walk; Numerical method; Star formation; Galaxy formation; Metallicity; Stellar population; Physical parameter; Degeneration; Diffusion; Sky surveys; Age
• ISSN: 0035-8711; 1365-2966
• DOI: 10.1111/j.1365-2966.2009.15349.x

To further our knowledge of the complex physical process of galaxy formation, it is essential that we characterize the formation and evolution of large data bases of galaxies. The spectral synthesis starlight code of Cid Fernandes et al. was designed for this purpose. Results of starlight are highly dependent on the choice of input basis of simple stellar population (SSP) spectra. Speed of the code, which uses random walks through the parameter space, scales as the square of the number of the basis spectra, making it computationally necessary to choose a small number of SSPs that are coarsely sampled in age and metallicity. In this paper, we develop methods based on a diffusion map that, for the first time, choose appropriate bases of prototype SSP spectra from a large set of SSP spectra designed to approximate the continuous grid of age and metallicity of SSPs of which galaxies are truly composed. We show that our techniques achieve better accuracy of physical parameter estimation for simulated galaxies. Specifically, we show that our methods significantly decrease the age–metallicity degeneracy that is common in galaxy population synthesis methods. We analyse a sample of 3046 galaxies in Sloan Digital Sky Survey Data Release 6 and compare the parameter estimates obtained from different basis choices.