Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-18T04:42:55.304Z Has data issue: false hasContentIssue false
  • English
  • Français

Modelling Stellar Populations at High Redshift

Published online by Cambridge University Press:  05 December 2011

Claudia Maraston
Claudia Maraston*
Affiliation:
ICG-University of Portsmouth, PO13FX, Portsmouth, United Kingdom email: claudia.maraston@port.ac.uk
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.

Stellar populations carry information about the formation of galaxies and their evolution up to the present epoch. A wealth of observational data are available nowadays, which are analysed with stellar population models in order to obtain key properties such as ages, star formation histories, stellar masses. Differences in the models and/or in the assumptions regarding the star formation history affect the derived properties as much as differences in the data. I shall review the interpretation of high-redshift galaxy data from a model perspective. While data quality dominates galaxy analysis at the highest possible redshifts (z > 5), population modelling effects play the major part at lower redshifts. In particular, I discuss the cases of both star-forming galaxies at the peak of the cosmic star formation history as well as passive galaxies at redshift below 1 that are often used as cosmological probes. Remarks on the bridge between low and high-z massive galaxies conclude the contribution.

Keywords

galaxies: evolutiongalaxies: fundamental parametersgalaxies:high-redshift
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 6 , Symposium S277: Tracing the Ancestry of Galaxies (on the land of our ancestors) , December 2010 , pp. 158 - 165
Copyright
Copyright © International Astronomical Union 2011

References

Chiosi, C. & Maeder, A. 1986, ARA&A, 24, 329Google Scholar
Cool, R. J., Eisenstein, D. J., Fan, X., et al. 2008, ApJ, 682, 919Google Scholar
Daddi, E., Dannerbauer, H., Stern, D., et al. 2009, ApJ, 694, 1517CrossRefGoogle Scholar
Förster-Schreiber, N., Genzel, R., Bouche', N., et al. 2009, ApJ, 706, 1364Google Scholar
Labbé, I., Gonzalez, V., Bouwens, R. J., et al. 2010, ApJ, 716L, 103LCrossRefGoogle Scholar
Leitherer, C., Schaerer, D., Goldader, J. D., et al. 1999, ApJS, 123, 3Google Scholar
Maraston, 2005, MNRAS, 362, 799CrossRefGoogle Scholar
Maraston, C., Daddi, E., & Renzini, A. 2006, ApJ, 652, 85Google Scholar
Maraston, C., Strömbäck, G., & Thomas, D., et al. 2009, MNRAS, 394, L107Google Scholar
Maraston, C., Pforr, J., Daddi, E., et al. 2010, MNRAS, 407, 830Google Scholar
Maraston, C. 2011, “Why galaxies care about AGB stars. Modelling galaxies”, proceedings of the conference “Why Galaxies care about AGB stars. II”, 2011arXiv1104.0022MGoogle Scholar
Marigo, P., Girardi, L., & Bressan, A., 2008, MNRAS, 482, 883Google Scholar
Marchesini, D., vanAAAADokkum, P. G., Förster-Schreiber, N. M., et al. 2009, ApJ, 701, 1765CrossRefGoogle Scholar
Moresco, M., Pozzetti, L., Cimatti, A., et al. 2010, A&A, 524, 67Google Scholar
Renzini, A. 2006, ARA&A, 44, 141Google Scholar
Renzini, A. 2009, MNRAS, 398, L58CrossRefGoogle Scholar
Robertson, B. E., Ellis, R. S., Dunlop, J. S., et al. 2010, Nature, 468, 49Google Scholar
Smôlcìc, V., Capak, P., Ilbert, O., et al. 2011, ApJ, 731, L27Google Scholar
Shapley, A. 2011, ARA&A, 49, 525Google Scholar
Thomas, D., Maraston, C., & Schawinski, K. 2010, MNRAS, 404, 1775Google Scholar
Tiret, O., Salucci, P., & Bernnardi, M 2011, MNRAS, 411, 1435Google Scholar
Wake, D. A., Nichol, R. C., Eisenstein, D. J., et al. 2006, MNRAS, 372, 537Google Scholar