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A Bayesian Method for the Extinction

Published online by Cambridge University Press:  01 July 2015

Hai-Jun Tian ,
Chao Liu ,
Jing-Yao Hu ,
Yang Xu  and
Xue-Lei Chen
Hai-Jun Tian
Affiliation:
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 China Three Gorges University, Yichang, 443002. Email: [email protected]
Chao Liu
Affiliation:
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012
Jing-Yao Hu
Affiliation:
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012
Yang Xu
Affiliation:
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012
Xue-Lei Chen
Affiliation:
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012
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Abstract

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We propose a Bayesian method to measure the total Galactic extinction parameters, RV and AV. Validation tests based on the simulated data indicate that the method can achieve the accuracy of around 0.01 mag. We apply this method to the SDSS BHB stars in the northern Galactic cap and find that the derived extinctions are highly consistent with those from Schlegel et al. (1998). It suggests that the Bayesian method is promising for the extinction estimation, even the reddening values are close to the observational errors.

Keywords

dustextinction stars: horizontal-branch methods: statistical
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 10 , Symposium S306: Statistical Challenges in 21st Century Cosmology , May 2014 , pp. 22 - 24
Copyright
Copyright © International Astronomical Union 2015 

References

Arce, H. G. & Goodman, A. A. 1999, ApJ, 512, L135CrossRefGoogle Scholar
Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245Google Scholar
Draine, B. T. 2003, ARA&A, 41, 241Google Scholar
Guy, J., Sullivan, M., Conley, , et al. 2010, A&A, 537, A7Google Scholar
Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525CrossRefGoogle Scholar
Smith, K. W., Bailer-Jones, C. A. L., Klement, R. J., & Xue, X. X., 2010, A&A, 522, A88Google Scholar
Tian, H. J., Neyrinck, M. C., Budavári, T., & Szalay, A. S., 2011, ApJ, 728, 34TGoogle Scholar