DustPedia: Multiwavelength photometry and imagery of 875 nearby galaxies in 42 ultraviolet-microwave bands

Abstract

Aims. The DustPedia project is capitalising on the legacy of the Herschel Space Observatory, using cutting-edge modelling techniques to study dust in the 875 DustPedia galaxies -representing the vast majority of extended galaxies within 3000 km s −1 that were observed by Herschel. This work requires a database of multiwavelength imagery and photometry that greatly exceeds the scope (in terms of wavelength coverage and number of galaxies) of any previous local-Universe survey. Methods. We constructed a database containing our own custom Herschel reductions, along with standardised archival observations from GALEX, SDSS, DSS, 2MASS, WISE, Spitzer, and Planck. Using these data, we performed consistent aperture-matched photometry, which we combined with external supplementary photometry from IRAS and Planck. Results. We present our multiwavelength imagery and photometry across 42 UV-microwave bands for the 875 DustPedia galaxies. Our aperture-matched photometry, combined with the external supplementary photometry, represents a total of 21 857 photometric measurements. A typical DustPedia galaxy has multiwavelength photometry spanning 25 bands. We also present the Comprehensive & Adaptable Aperture Photometry Routine (CAAPR), the pipeline we developed to carry out our aperture-matched photometry. CAAPR is designed to produce consistent photometry for the enormous range of galaxy and observation types in our data. In particular, CAAPR is able to determine robust cross-compatible uncertainties, thanks to a novel method for reliably extrapolating the aperture noise for observations that cover a very limited amount of background. Our rich database of imagery and photometry is being made available to the community.

SKIRT 9: Redesigning an advanced dust radiative transfer code to allow kinematics, line transfer and polarization by aligned dust grains

“…The Python Toolkit for SKIRT (PTS) was originally developed as a set of Python modules offering functionality for working with SKIRT 7 and SKIRT 8. Over the years, it has far outgrown its original scope, now including subpackages related to specific projects, often with a limited SKIRT 9 and PTS 9 docs + project pages Current development or no connection to SKIRT (e.g., Clark et al 2018;Decleir et al 2019;Verstocken et al in-prep;Nersesian et al inprep). The size of the code base raises significant concerns about maintenance and support.…”

Reproducing the Universe: a comparison between the EAGLE simulations and the nearby DustPedia galaxy sample

“…We discuss in later sections how these differences affect our comparison. We chose not to change the IMF, the dust model or any other parameter in the SED modelling, for the consistency, and easier comparison with the previous studies of the DustPedia galaxies (Bianchi et al 2018;Clark et al 2018;De Vis et al 2019;Nersesian et al 2019;Dobbels et al 2020;Casasola et al 2020, etc.). Additionally, the same cigale fitting procedure for the EAGLE galaxies is already published in Baes et al (2019).…”

A panchromatic spatially resolved analysis of nearby galaxies – I. Sub-kpc-scale main sequence in grand-design spirals

“…In the following paragraphs we briefly report information on the different data sets used in this work. For a more systematic and complete reference about data reduction and processing (implemented by the DustPedia collaboration) we refer the reader to Clark et al (2018).…”

“…Near-infrared (NIR) imaging comes from 2MASS in three bands, J-band (1.25 µm), H-band (1.65 µm) and K s -band (2.16 µm), with FWHMs between ∼ 2.5 and 2.7 . As noted in Appendix D of Clark et al (2018), 2MASS-H band photometry might be affected by a particular offset with respect to J and K s band photometry, translating as a "bump" or "dip" in the SED of the object. We find this problem only NGC0628 photometry, for which we exclude the H-band data-point from the SED fitting.…”

“…Foreground stars removal is performed exploiting the Comprehensive & Adaptable Aperture Photometry Routine (CAAPR) routine presented in Clark et al (2018). The routine uses the PTS toolkit for SKIRT (Camps & Baes 2015) to detect and remove/patch foreground star emission, thus creating a star subtracted version of the map.…”