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Galaxy classification in the UBC/NASA multi-narrowband survey

University of British Columbia

The main goals of this thesis are to classify, catalog and extract a redshift distribution of galaxies in the UBC/NASA Multi-Narrowband Survey (UNMS), conducted at the NASA Orbital Debris Observatory (NODO). We aim to classify sources using a maximum of 39 photometric bands for any source observed. Two independent classification schemes were implemented and compared. One used the photometric information from all the filters available (X² fitting routine) and the other employed a neural network, which based classification on isophotal shape parameters as input (SExtractor). The classification efficiency of galaxies, based on independent confirmations were 80% and 90% for the X² routine and SExtractor stellarity index respectively, even though the comparison between the two methods was poor. The fitted redshifts were compared with spectroscopically determined redshifts from the NASA/IPAC Extra-Galactic Database (NED) for 19 galaxies. More than half of the sources had seriously discrepant photometric redshifts. The spectral energy distributions (SEDs) of the galaxies with redshifts that did match showed a smooth flux distribution (low noise) that contained 1 or 2 emission features. Spectra that showed a somewhat scattered distribution of flux points resulted in uncertain redshift estimates. Failure of the photometric redshift estimation technique prevented us from pursuing more detailed statistical analyses, such as the galaxy luminosity function. We discuss possible interpretations for the apparent photometric/spectroscopic redshift discrepancy.

Thesis/Dissertation

application/pdf

2009-09-28

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http://hdl.handle.net/2429/13246

Astronomy

University of British Columbia

UBCV

DSpace