Journal
ASTROPHYSICAL JOURNAL
Volume 752, Issue 1, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/0004-637X/752/1/55
Keywords
infrared: ISM; ISM: structure; methods: data analysis; methods: statistical; stars: formation
Categories
Funding
- National Science Foundation [AST-0908159]
- NASA through Space Telescope Science Institute [HF-01220.01, HF-51243.01]
- Southern California Center for Galaxy Evolution
- University of California Office of Research
- German Bundesministerium fur Bildung und Forschung via the ASTRONET project STAR FORMAT [05A09VHA]
- NASA [NAS 5-26555]
- The Milky Way System [SFB 881]
- Direct For Mathematical & Physical Scien
- Division Of Astronomical Sciences [0908159] Funding Source: National Science Foundation
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We present a hierarchical Bayesian method for fitting infrared spectral energy distributions (SEDs) of dust emission to observed fluxes. Under the standard assumption of optically thin single temperature (T) sources, the dust SED as represented by a power-law-modified blackbody is subject to a strong degeneracy between T and the spectral index beta. The traditional non-hierarchical approaches, typically based on chi(2) minimization, are severely limited by this degeneracy, as it produces an artificial anti-correlation between T and beta even with modest levels of observational noise. The hierarchical Bayesian method rigorously and self-consistently treats measurement uncertainties, including calibration and noise, resulting in more precise SED fits. As a result, the Bayesian fits do not produce any spurious anti-correlations between the SED parameters due to measurement uncertainty. We demonstrate that the Bayesian method is substantially more accurate than the chi(2) fit in recovering the SED parameters, as well as the correlations between them. As an illustration, we apply our method to Herschel and submillimeter ground-based observations of the star-forming Bok globule CB244. This source is a small, nearby molecular cloud containing a single low-mass protostar and a starless core. We find that T and beta are weakly positively correlated-in contradiction with the chi(2) fits, which indicate a T-beta anti-correlation from the same data set. Additionally, in comparison to the chi(2) fits the Bayesian SED parameter estimates exhibit a reduced range in values.
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