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Title: BayeSED: A GENERAL APPROACH TO FITTING THE SPECTRAL ENERGY DISTRIBUTION OF GALAXIES

Journal Article · · Astrophysical Journal, Supplement Series
;  [1]
  1. Yunnan Observatories, Chinese Academy of Sciences, Kunming, 650011 (China)

We present a newly developed version of BayeSED, a general Bayesian approach to the spectral energy distribution (SED) fitting of galaxies. The new BayeSED code has been systematically tested on a mock sample of galaxies. The comparison between the estimated and input values of the parameters shows that BayeSED can recover the physical parameters of galaxies reasonably well. We then applied BayeSED to interpret the SEDs of a large K{sub s} -selected sample of galaxies in the COSMOS/UltraVISTA field with stellar population synthesis models. Using the new BayeSED code, a Bayesian model comparison of stellar population synthesis models has been performed for the first time. We found that the 2003 model by Bruzual and Charlot, statistically speaking, has greater Bayesian evidence than the 2005 model by Maraston for the K{sub s} -selected sample. In addition, while setting the stellar metallicity as a free parameter obviously increases the Bayesian evidence of both models, varying the initial mass function has a notable effect only on the Maraston model. Meanwhile, the physical parameters estimated with BayeSED are found to be generally consistent with those obtained using the popular grid-based FAST code, while the former parameters exhibit more natural distributions. Based on the estimated physical parameters of the galaxies in the sample, we qualitatively classified the galaxies in the sample into five populations that may represent galaxies at different evolution stages or in different environments. We conclude that BayeSED could be a reliable and powerful tool for investigating the formation and evolution of galaxies from the rich multi-wavelength observations currently available. A binary version of the BayeSED code parallelized with Message Passing Interface is publicly available at https://bitbucket.org/hanyk/bayesed.

OSTI ID:
22340147
Journal Information:
Astrophysical Journal, Supplement Series, Vol. 215, Issue 1; Other Information: Country of input: International Atomic Energy Agency (IAEA); ISSN 0067-0049
Country of Publication:
United States
Language:
English