pith. the verified trust layer for science. sign in

arxiv: 1609.06138 · v1 · pith:YIXAEW4Enew · submitted 2016-09-20 · 🌌 astro-ph.GA · astro-ph.CO

DustPedia - A Definitive Study of Cosmic Dust in the Local Universe

classification 🌌 astro-ph.GA astro-ph.CO
keywords cosmicdatadustdustpediaenergyphysicalchemicaldescribe
0
0 comments X p. Extension
Add this Pith Number to your LaTeX paper What is a Pith Number?
\usepackage{pith}
\pithnumber{YIXAEW4E}

Prints a linked pith:YIXAEW4E badge after your title and writes the identifier into PDF metadata. Compiles on arXiv with no extra files. Learn more

read the original abstract

The European Space Agency has invested heavily in two cornerstones missions; Herschel and Planck. The legacy data from these missions provides us with an unprecedented opportunity to study cosmic dust in galaxies so that we can answer fundamental questions about, for example: 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 is enabling us to develop tools and computer models that will help us relate observed cosmic dust emission to its physical properties (chemical composition, size distribution, temperature), to its origins (evolved stars, super novae, growth in the ISM) and the processes that destroy it (high energy collisions and shock heated gas). To carry out this research we will combine the Herschel/Planck data with that from other sources of data, providing observations at numerous wavelengths (< 41) across the spectral energy distribution, thus creating the DustPedia database. To maximise our spatial resolution and sensitivity to cosmic dust we limit our analysis to 4231 local galaxies (v < 3000 km/s) selected via their near infrared luminosity (stellar mass). To help us interpret the data we have 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.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.