DustPedia: A Definitive Study of Cosmic Dust in the Local Universe
Date Issued
2017
Author(s)
Davies, J. I.
•
Baes, M.
•
•
Jones, A.
•
Madden, S.
•
Xilouris, M.
•
Bocchio, M.
•
•
•
Clark, C.
•
De Looze, I.
•
Evans, R.
•
Fritz, J.
•
Galametz, M.
•
Galliano, F.
•
Lianou, S.
•
Mosenkov, A. V.
•
Smith, M.
•
Verstocken, S.
•
Viaene, S.
•
Vika, M.
•
Wagle, G.
•
Ysard, N.
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 (≤slant 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.
Volume
129
Issue
974
Start page
044102
Issn Identifier
0004-6280
Ads BibCode
2017PASP..129d4102D
Rights
open.access
File(s)![Thumbnail Image]()
![Thumbnail Image]()
Loading...
Name
96-DaviesPASP2017.pdf
Description
[Administrators only]
Size
4.86 MB
Format
Adobe PDF
Checksum (MD5)
88acfac76d5f4943d2ef2f33c5c3f72a
Loading...
Name
1609.06138.pdf
Description
postprint
Size
7.91 MB
Format
Adobe PDF
Checksum (MD5)
4e35a31418323eb685ad77fb749578e5