Modeling dust emission in the Magellanic Clouds with Spitzer and Herschel

Jeremy Chastenet, Caroline Bot, Karl D. Gordon, Marco Bocchio, Anthony Jones, Julia Roman-Duval, and Natalie Ysard 2017, A&A, in press

We derived dust maps in the Magellanic Clouds (MCs) following the work of Gordon et al. (2014). We used data from the SAGE-LMC and SAGE-SMC Spitzer Legacies and the HERITAGE Herschel Key Project as measurements for dust emission, covering 11 bands from 3.6 to 500 µm. Each image was processed through the same pipeline, to the final resolution of SPIRE 500 µm.

Please reference Chastenet et. al. 2017, A&A, in press if you use these results in a paper, talk, poster, etc. Thanks.

Dust Parameter Maps

Two dust grain models were fit to the data: Compiegne et al. (2011) and THEMIS (Jones et al. 2013, Koehler et al. 2014, Ysard et al. 2016). The dust emission was determined in different environment scenarios, with varying interstellar radiation field (ISRF) mixtures: a single ISRF, 2-ISRFs (warm and cold), and a mixture of ISRF set by a power-law (e.g. Dale et al. 2001). In the case of THEMIS, another variation is tested, where we change the size distribution of small carbonaceous grains. In order to have the same systematics, we used the same fitting scheme in all cases. This allows us to get rid of possible discrepencies that may be due to choices of algorithm (e.g. when comparing different studies). We analyzed the intrinsic differences in grain composition and investigated the resulting fitting residuals, showing that THEMIS is better to reproduce the MCs dust emission. For further analysis and dust properties, we rely only on THEMIS. We derive total dust masses of ~3-9 104 M in the SMC and ~3.7-4.3 105 M in the LMC, in the detected pixels (i.e., 3σ detection above the background noise).

Free parameters of THEMIS are: the ISRF intensity U, the independent grain masses (silicates, large carbonaceous and small carbonaceous grains) Yi, and the stellar component intensity (a 5000K blackbody) Ω*. Variations upon the ISRF nature, e.g. the dust heating environment are tried to fit the models to the data. In the paper, we made use of:

  1. Compiegne, with a single ISRF;
  2. THEMIS, with a single ISRF;
  3. THEMIS, with 2 ISRFs: the resulting spectrum is a combination of warm dust, and cold dust;
  4. THEMIS, with a multi-ISRFs approach: the resulting spectrum is a combination of dust spectra heated with different ISRF (e.g Dale et al. 2001)

We also used a variation of THEMIS in which we allow the grain size distribution of small grains to change.

The "best fit" parameters are presented in 3 flavors.

  1. 'max' method: the classical best fit where the fit parameters are given by the model the best fits the data
  2. 'exp' method: the expectation value of the full likelihood function for each parameter (includes the non-symmetries in the likelihood functions)
  3. 'realize' method: a single realization of the likelihood function for each pixel (best for analyses looking at the ensemble behavior of the pixels)
    only 1 'realization' provided, more are available upon request (the number of pixels in each galaxy is such that the ensemble behavior does not change much between realizations)

The files are FITS files with extensions. Each extension has a different fit parameter and is identified by the 'extname' keyword in the extension header. The links are to .tar.gz files containing the spearate files.

Compiegne Model Fits

THEMIS Model Fits

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