A&A 389, 1090-1116 (2002)
DOI: 10.1051/0004-6361:20020665
Classification and redshift estimation by principal component analysis
R. A. Cabanac1, 2, V. de Lapparent1 and P. Hickson31 Institut d'Astrophysique de Paris, CNRS / Univ. Pierre et Marie Curie, 98 bis Bd. Arago, 75014 Paris, France
2 European Southern Observatory, Vitacura, Alonso de Cordova, 3107, casilla 19001, Santiago, Chile
3 Dept. of Physics & Astronomy, Univ. British Columbia, 2219 Main Mall, Vancouver, BC V6T1Z4, Canada
(Received 3 April 2001 / Accepted 22 April 2002)
Abstract
We show that the first 10 eigencomponents of the
Karhunen-Loève expansion or Principal Component Analysis (PCA) provide
a robust classification scheme for the identification of stars, galaxies and
quasi-stellar objects from multi-band photometry. To quantify the efficiency
of the method, realistic simulations are performed which match the planned
Large Zenith Telescope survey. This survey is expected to provide spectral
energy distributions with a resolution
for ~
106 galaxies
to
(
),
QSOs, and
stars.
Key words: galaxies: fundamental parameters -- methods: data analysis -- Surveys -- galaxies: general
Offprint request: R. A. Cabanac, rcabanac@eso.org
© ESO 2002

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