WINGS: Deep optical phot. of 77 nearby clusters (Varela+, 2009)

Details WINGS: Deep optical phot. of 77 nearby clusters (Varela+, 2009) WINGS: Deep optical phot. of 77 nearby clusters (Varela+, 2009)

May 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009ycat..34970667v&link_type=abstract

VizieR On-line Data Catalog: J/A+A/497/667. Originally published in: 2009A&A...497..667V

Computer Science

Clusters: Galaxy, Galaxies: Photometry

Scientific paper

This is the second paper of a series devoted to the WIde Field Nearby Galaxy-cluster Survey (WINGS). WINGS is a long term project which is gathering wide-field, multi-band imaging and spectroscopy of galaxies in a complete sample of 77 X-ray selected, nearby clusters (0.04200deg). The main goal of this project is to establish a local reference for evolutionary studies of galaxies and galaxy clusters. This paper presents the optical (B,V) photometric catalogs of the WINGS sample and describes the procedures followed to construct them. We have paid special care to correctly treat the large extended galaxies (which includes the brightest cluster galaxies) and the reduction of the influence of the bright halos of very bright stars. We have constructed photometric catalogs based on wide-field images in B and V bands using SExtractor. Photometry has been performed on images in which large galaxies and halos of bright stars were removed after modeling them with elliptical isophotes. We publish deep optical photometric catalogs (90% complete at V21.7, which translates to ~ MV* + 6 at mean redshift), giving positions, geometrical parameters, and several total and aperture magnitudes for all the objects detected. For each field we have produced three catalogs containing galaxies, stars and objects of "unknown" classification (~16%). From simulations we found that the uncertainty of our photometry is quite dependent of the light profile of the objects with stars having the most robust photometry and de Vaucouleurs profiles showing higher uncertainties and also an additional bias of ~-0.2m. The star/galaxy classification of the bright objects (V<20) was checked visually making negligible the fraction of misclassified objects. For fainter objects, we found that simulations do not provide reliable estimates of the possible misclassification and therefore we have compared our data with that from deep counts of galaxies and star counts from models of our Galaxy. Both sets turned out to be consistent with our data within ~5% (in the ratio galaxies/total) up to V~24. Finally, we remark that the application of our special procedure to remove large halos improves the photometry of the large galaxies in our sample with respect to the use of blind automatic procedures and increases (~16%) the detection rate of objects projected onto them.
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