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Panchromatic star formation rate indicators and their uncertainties

Published online by Cambridge University Press:  27 October 2016

Elisabete da Cunha
Elisabete da Cunha*
Affiliation:
Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Hawthorn, VIC 3122, Australia email: [email protected]
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Abstract

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The star formation rate (SFR) is a fundamental property of galaxies and it is crucial to understand the build-up of their stellar content, their chemical evolution, and energetic feedback. The SFR of galaxies is typically obtained by observing the emission by young stellar populations directly in the ultraviolet, the optical nebular line emission from gas ionized by newly-formed massive stars, the reprocessed emission by dust in the infrared range, or by combining observations at different wavelengths and fitting the full spectral energy distributions of galaxies. In this brief review we describe the assumptions, advantages and limitations of different SFR indicators, and we discuss the most promising SFR indicators for high-redshift studies.

Keywords

galaxies: fundamental parametersgalaxies: evolution
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 11 , General Assembly A29B: Astronomy in Focus , August 2015 , pp. 184 - 185
Copyright
Copyright © International Astronomical Union 2016 

References

Bendo, G. J., Wilson, C. D., Pohlen, M., et al. 2010, A&A, 518, L65 Google Scholar
Calzetti, D., Kennicutt, R. C., Engelbracht, C. W., et al. 2007, ApJ, 666, 870 CrossRefGoogle Scholar
Calzetti, D. 2013, Secular Evolution of Galaxies, 419CrossRefGoogle Scholar
Carilli, C. L. & Walter, F. 2013, ARA&A, 51, 105 Google Scholar
da Cunha, E., Charlot, S., & Elbaz, D. 2008, MNRAS, 388, 1595 CrossRefGoogle Scholar
Dale, D. A., Cohen, S. A., Johnson, L. C., et al. 2009, ApJ, 703, 517 CrossRefGoogle Scholar
Groves, B., Krause, O., Sandstrom, K., et al. 2012, MNRAS, 426, 892 CrossRefGoogle Scholar
Hao, C.-N., Kennicutt, R. C., Johnson, B. D., et al. 2011, ApJ, 741, 124 CrossRefGoogle Scholar
Herrera-Camus, R., Bolatto, A. D., Wolfire, M. G., et al. 2015, ApJ, 800, 1 CrossRefGoogle Scholar
Kennicutt, R. C. Jr. 1998, ARA&A, 36, 189 Google Scholar
Kennicutt, R. C. Jr., Hao, C.-N., Calzetti, D., et al. 2009, ApJ, 703, 1672 CrossRefGoogle Scholar
Kennicutt, R. C. & Evans, N. J. 2012, ARA&A, 50, 531 Google Scholar
Kong, X., Charlot, S., Brinchmann, J., & Fall, S. M. 2004, MNRAS, 349, 769 CrossRefGoogle Scholar
Madau, P. & Dickinson, M. 2014, ARA&A, 52, 415 Google Scholar
Meurer, G. R., Heckman, T. M., & Calzetti, D. 1999, ApJ, 521, 64 CrossRefGoogle Scholar
Ota, K., Walter, F., Ohta, K., et al. 2014, ApJ, 792, 34 CrossRefGoogle Scholar
Pacifici, C., da Cunha, E., Charlot, S., et al. 2015, MNRAS, 447, 786 CrossRefGoogle Scholar