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

TL;DR

DustPedia leverages Herschel and Planck data to develop models and tools for understanding cosmic dust properties, origins, and destruction processes in local galaxies, advancing knowledge of the interstellar medium and galaxy evolution.

Contribution

Introduction of the DustPedia project with new models, methods, and a comprehensive database to analyze cosmic dust in local galaxies.

Findings

Development of the DustPedia database with multi-wavelength data

Creation of the THEMIS dust model and HerBIE Bayesian fitting method

Implementation of the SKIRT radiative transfer model

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.