Wednesday, June 20, 2012 - 4:15pm
"Dust Spectral Energy Distributions in the Era of Herschel and Planck: A Hierarchical Bayesian-fitting Technique"
Abstract. Recent infrared observatories, including Herschel and Planck, provide unprecedented views into the nature of astrophysical dust across a range of environments. Determing the dust properties is critical to access physical conditions, such as temperatures and column densities, in star-forming regions. However, under commonly employed methods, the dust SED, as represented by a power--law modified black body, is subject to a strong degeneracy between the derived temperature and spectral index. This degeneracy can lead to a spurious anti-correlation between temperature and the spectral index when one fits these parameters independently for each source or pixel. I will discuss a novel hierarchical Bayesian method for fitting dust infrared spectral energy distributions to observed fluxes. I will discuss how our method is able to overcome the degeneracy between temperature and the spectral index by fitting both the distribution of the SED parameters simultaneously with the parameters for individual data points. Tests using simple models show that our method is capable of recovering the source parameters and correlations, indicating that this approach is substantially more accurate than traditional methods. Finally, I will discuss the application of our method to the star-forming Bok Globule CB244, and contrast the results with those obtained using traditional methods.