We present the Bayesian Extinction And Stellar Tool (BEAST), a probabilistic approach to modeling the dust extinguished photometric spectral energy distribution of an individual star while accounting for observational uncertainties common to large resolved star surveys. Given a set of photometric measurements and an observational uncertainty model, the BEAST infers the physical properties of the stellar source using stellar evolution and atmosphere models and constrains the line of sight extinction using a newly developed mixture model that encompasses the full range of dust extinction curves seen in the Local Group. The BEAST is specifically formulated for use with large multi-band surveys of resolved stellar populations. Our approach accounts for measurement uncertainties and any covariance between them due to stellar crowding (both systematic biases and uncertainties in the bias) and absolute flux calibration, thereby incorporating the full information content of the measurement. We illustrate the accuracy and precision possible with the BEAST using data from the Panchromatic Hubble Andromeda Treasury. While the BEAST has been developed for this survey, it can be easily applied to similar existing and planned resolved star surveys.
Bibliographical noteFunding Information:
We thank the referee for insightful comments that motivated us to significantly improve the content and presentation of this paper. Support for program # 12055 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. Support for DRW is provided by NASA through Hubble Fellowship grants HST-HF-51331.01 awarded by the Space Telescope Science Institute. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1053575.
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- Analysis - methods: statistical
- Galaxies: individual (M31)
- Methods: data
- Stars: fundamental parameters