Abstract
In the last decade we have seen an enormous increase in the size and duality of spectroscopic galaxy surveys, both at low and high redshift. New statistical techniques to analyse large portions of galaxy spectra are now finding favour over traditional index based methods. Here we will review anew robust and iterative Principal Component Analysis (PCA) algorithm, which solves several common issues with classic PCA. Application to the 4000 angstrom break region of galaxies in the VIMOS VLT Deep Survey (VVDS) and Sloan Digital Sky Survey (SDSS) gives new high signal-to-noise ratio spectral indices easily interpretable in terns of recent star formation history. In particular, we identify a sample of post-starburst galaxies at z similar to 0.7 and z similar to 0.07. We quantify for the first time the importance of post-starburst galaxies, consistent with being descendents of gas-rich major mergers, for building the red sequence. Finally, we present a comparison with new low and high redshift "mock spectroscopic surveys" derived from a Millennium Run semi-analytic model.
Original language | English |
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Title of host publication | CLASSIFICATION AND DISCOVERY IN LARGE ASTRONOMICAL SURVEYS |
Editors | CAL BailerJones |
Place of Publication | MELVILLE |
Publisher | American Institute of Physics |
Pages | 119-125 |
Number of pages | 7 |
ISBN (Print) | 978-0-7354-0613-1 |
Publication status | Published - 2008 |
Event | International Conference on Classification and Discovery in Large Astronomical Surveys - Ringberg Castle Duration: 14 Oct 2008 → 17 Oct 2008 |
Conference
Conference | International Conference on Classification and Discovery in Large Astronomical Surveys |
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City | Ringberg Castle |
Period | 14/10/08 → 17/10/08 |