Modeling dust emission in the Magellanic Clouds with Spitzer and Herschel

Chastenet, Jérémy, Bot, Caroline, Gordon, Karl D., Bocchio, Marco, Roman-Duval, Julia, Jones, Anthony P., & Ysard, Nathalie
2017, Astronomy & Astrophysics, 601, A55


Context. Dust modeling is crucial to infer dust properties and budget for galaxy studies. However, there are systematic disparities between dust grain models that result in corresponding systematic differences in the inferred dust properties of galaxies. Quantifying these systematics requires a consistent fitting analysis. Aims: We compare the output dust parameters and assess the differences between two dust grain models, the DustEM model and THEMIS. In this study, we use a single fitting method applied to all the models to extract a coherent and unique statistical analysis. Methods: We fit the models to the dust emission seen by Spitzer and Herschel in the Small and Large Magellanic Clouds (SMC and LMC). The observations cover the infrared (IR) spectrum from a few microns to the sub-millimeter range. For each fitted pixel, we calculate the full n-D likelihood based on a previously described method. The free parameters are both environmental (U, the interstellar radiation field strength; αISRF, power-law coefficient for a multi-U environment; Ω∗, the starlight strength) and intrinsic to the model (Yi: abundances of the grain species i; αsCM20, coefficient in the small carbon grain size distribution). Results: Fractional residuals of five different sets of parameters show that fitting THEMIS brings a more accurate reproduction of the observations than the DustEM model. However, independent variations of the dust species show strong model-dependencies. We find that the abundance of silicates can only be constrained to an upper-limit and that the silicate/carbon ratio is different than that seen in our Galaxy. In the LMC, our fits result in dust masses slightly lower than those found in the literature, by a factor lower than 2. In the SMC, we find dust masses in agreement with previous studies.

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