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SOFIA Community Science I: HAWC+ Polarimetry of 30 Doradus
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Gordon, et al, 2018, arXiv:1811.03100.
Data for an unprecedented infrared polarimetric analysis of the 30 Doradus star-forming region in the Large Magellanic Cloud were taken by HAWC+ in Cycle 6 during SOFIA's annual Southern Deployment in Christchurch, New Zealand. At the center is a cluster of O-type and Wolf-Rayet stars that heat the surrounding dust, allowing for in-depth total intensity and polarimetry analysis of star formation in the infrared. In addition, 30 Doradus is in a low-metalicity galaxy, so researchers can study the star-formation phenomenon as it was in the past when the metal content of the universe was much lower.
SOFIA compiled polarization maps taken at 53, 89, 154, and 214 microns, revealing dust emission between 10-100 K and allowing for an inferred morphology study of the magnetic field.
Shorter wavelengths reveal hotter dust and yield information critical for studying magnetic field disturbances in dense, compact regions. At 53 microns, HAWC+ has an angular resolution of 4.9” Full width at half maximum (FWHM), a total intensity field of view of 2.8 x 1.7 arcmin 2, and a polarization field of view of 1.4 x 1.7 arcmin 2.
Longer wavelengths comparatively indicate cooler dust and provide information about the magnetic field on large scales. At 214 microns, HAWC+ has an angular resolution of 18.2” FWHM, a total intensity field of view of 10.0 x 6.3 arcmin 2, and a polarization field of view of 5.0 x 6.3 arcmin 2.
The data are available publicly available in the archive under project ID 76_0001 for further research.
Accessing the 30 Dor Data
- Visit the SOFIA Data Archive at IPAC
- Under "Spatial Constraints", select "All-Sky"
- Under “Proposal Constraints”, enter “76_0001” into PlanID field
- Under “Data Product Constraints”, ensure that only “Level 4” is checked
- Select Search
Resources
HAWC+ Data Handbook - Describes HAWC+ data products, processing steps, calibration procedures, and known issues.
HAWC+ 30 Doradus Data Recipe - Guides users through Python analysis techniques using the 30 Doradus dataset, teaching readers how to probe HAWC+ data cubes and learn basic analysis techniques—such as plotting Stokes parameters, error maps, and polarization vectors—to jump-start their own research.
