Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-30T20:35:12.621Z Has data issue: false hasContentIssue false
  • English
  • Français

Far-IR to Submm SEDs for local galaxies: Herschel, Planck and the HRS

Published online by Cambridge University Press:  17 August 2012

David L Clements
David L Clements
Affiliation:
Astrophysics Group, Imperial College, Blackett Laboratory, Prince Consort Road, London, SW7 2AZ, UK. email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The Herschel Space Observatory and the Planck satellite are providing radical improvements to our knowledge of the spectral energy distributions of galaxies in the far-IR and submm. We here present the results of the first combination of Herschel and Planck fluxes of local galaxies from the Herschel Reference Sample (HRS) survey, covering galaxies at distances between 15 and 25 Mpc. This combination provides information on SEDs in eight bands from 60μm, using IRAS, to 1.4mm using Planck. We apply a similar fitting procedure to this data as applied to the Planck ERCSC-detected nearby galaxies and confirm the result that dust significantly colder than 20K is common in local galaxies. It is early days for this kind of study, but it is clear that the new generation of satellites are already adding considerably to our knowledge of the far-IR/submm properties of galaxies.

Keywords

galaxies:dustHerschel Space ObservatoryPlanckgalaxies:infraredgalaxies:submm
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 7 , Symposium S284: The Spectral Energy Distribution of Galaxies , September 2011 , pp. 279 - 282
Copyright
Copyright © International Astronomical Union 2012

References

Boselli, A. et al. 2010, PASP, 122, 261CrossRefGoogle Scholar
Clements, D. L., Andreani, P., & Chase, S. T. 1993, MNRAS, 261, 299CrossRefGoogle Scholar
Clements, D. L., Dunne, L., & Eales, S. 2010, MNRAS, 403, 274CrossRefGoogle Scholar
Dunne, L. & Eales, S. A. 2001, MNRAS, 327, 697CrossRefGoogle Scholar
Dunne, L. et al. 2000, MNRAS, 315, 115CrossRefGoogle Scholar
Griffin, M. J. et al. 2010, A&A, 518, L3.Google Scholar
Jaffe, A. 1996, ApJ, 471, 24CrossRefGoogle Scholar
Jaynes, E. 2003, Probability Theory: the Logic of Science ed. Bretthorst, L. (Cambridge University Press)CrossRefGoogle Scholar
Peel, M. W. et al. 2011, MNRAS, 416, L99.CrossRefGoogle Scholar
Pilbratt, G. L. et al. 2010, A&A, 518, L1.Google Scholar
Planck Collaboration 2011a, A&A 536, A1Google Scholar
Planck Collaboration 2011b, A&A, 536, A16.Google Scholar
Planck Collaboration 2011c, A&A, 536, A17.Google Scholar
Planck Collaboration 2011d, A&A, 536, A7.Google Scholar