Sign on

SAO/NASA ADS Astronomy Abstract Service

· Find Similar Abstracts (with default settings below)
· Full Printable Article (PDF/Postscript)
· Scanned Article (GIF)
· Table of Contents
· References in the Article
· Reads History
· Translate This Page
Beyond model fitting SEDs
Ferreras, Ignacio
AA( Mullard Space Science Laboratory, University College London Holmbury St Mary, Dorking, Surrey RH5 6NT, UK )
The Spectral Energy Distribution of Galaxies, Proceedings of the International Astronomical Union, IAU Symposium, Volume 284, p. 38-41
Publication Date:
methods: statistical, techniques: spectroscopic, galaxies: stellar content,
Abstract Copyright:
(c) 2012: Copyright © International Astronomical Union 2012
Bibliographic Code:


Extracting star formation histories from spectra is a process plagued by numerous degeneracies among the parameters that contribute to the definition of the underlying stellar populations. Traditional approaches to overcome such degeneracies involve carefully defined line strength or spectral fitting procedures. However, all these methods rely on comparisons with population synthesis models. This paper illustrates alternative approaches based on the statistical properties of the information that can be extracted from uniformly selected samples of observed spectra, without any prior reference to modelling. Such methods are more useful with large datasets, such as surveys, where the information from thousands of spectra can be exploited to classify galaxies. An illustrative example is presented on the classification of early-type galaxies with optical spectra from the Sloan Digital Sky Survey.

Printing Options

Print whole paper
Print Page(s) through

Return 600 dpi PDF to Acrobat/Browser. Different resolutions (200 or 600 dpi), formats (Postscript, PDF, etc), page sizes (US Letter, European A4, etc), and compression (gzip,compress,none) can be set through the Printing Preferences

More Article Retrieval Options

HELP for Article Retrieval

Bibtex entry for this abstract   Preferred format for this abstract (see Preferences)

Find Similar Abstracts:

Use: Authors
Keywords (in text query field)
Abstract Text
Return: Query Results Return    items starting with number
Query Form
Database: Astronomy
arXiv e-prints