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ToolsDAVIES, J.I., BAES, M., BIANCHI, S., JONES, A., MADDEN, S., XILOURIS, M., BOCCHIO, M., CASASOLA, V., CASSARA, L., CLARK, C., LOOZE, I. De, EVANS, R., FRITZ, J., GALAMETZ, M., GALLIANO, F., LIANOU, S., MOSENKOV, A.V., SMITH, M., VERSTOCKEN, S., VIAENE, S, VIKA, M., WAGLE, G. and YSARD, N. (2017). DustPedia: A Definitive Study of Cosmic Dust in the Local Universe. Publications of the Astronomical Society of the Pacific, 129 (974), 044102-044102. [Article]
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Abstract
The European Space Agency has invested heavily in two cornerstones missions: Herschel and Planck. The legacy
data from these missions provides an unprecedented opportunity to study cosmic dust in galaxies so that we can,
for example, answer fundamental questions about the origin of the chemical elements, physical processes in the
interstellar medium (ISM), its effect on stellar radiation, its relation to star formation and how this relates to the
cosmic far-infrared background. In this paper we describe the DustPedia project, which enables us to develop tools
and computer models that will help us relate observed cosmic dust emission to its physical properties (chemical
composition, size distribution, and temperature), its origins (evolved stars, supernovae, and growth in the ISM),
and the processes that destroy it (high-energy collisions and shock heated gas). To carry out this research, we
combine the Herschel/Planck data with that from other sources of data, and provide observations at numerous
wavelengths (41) across the spectral energy distribution, thus creating the DustPedia database. To maximize our
spatial resolution and sensitivity to cosmic dust, we limit our analysis to 4231 local galaxies (v < 3000 km s−1
)
selected via their near-infrared luminosity (stellar mass). To help us interpret this data, we developed a new
physical model for dust (THEMIS), a new Bayesian method of fitting and interpreting spectral energy distributions
(HerBIE) and a state-of-the-art Monte Carlo photon-tracing radiative transfer model (SKIRT). In this, the first of
the DustPedia papers, we describe the project objectives, data sets used, and provide an insight into the new
scientific methods we plan to implement.
More Information
Identification Number:
ORCID for M. Baes:
orcid.org/0000-0002-3930-2757
orcid.org/0000-0002-3930-2757
ORCID for R. Evans:
orcid.org/0000-0001-5991-354X
orcid.org/0000-0001-5991-354X
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