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Quasar detection in the UBC-NASA multi-narrowband survey Braglia, Katia

Abstract

The goal of this thesis is to select quasars by applying a novel analysis to the UBC - NASA Multi-Narrow band Survey (UNMS1) catalog. The database consists of drift-scan observations taken with the 3-m NASA Liquid Mirror Telescope (LMT) in 1996-1997 and in 1999, using 35 narrow band filters, from 4500 to 9500 Å, and 4 broad bands (B, V, R, I), necessary for calibration purposes. The method presented here is based on the comparison between UNMS1 catalog sources and stellar, galaxy, and quasar templates through a x² minimization procedure combined with Bayesian analysis. The x² parameter is useful to determine which model is the best fit for an observed Spectral Energy Distribution (SED); the odds ratio parameter, from the Bayes' theorem, is necessary in order to know the most likely category the source belongs, and it involves information such as the number of models for each category and the surface densities of stars, galaxies and quasars at a given magnitude. After the method was applied to templates, treated as test-objects, it is concluded that more than 85% of quasar candidates, selected with at least 30 filter measurements, are correctly classified: the misclassification is due mostly to the similarity between stellar models and quasars when important spectral features are missed. Of all the 39040 selected sources, 3056 quasar candidates were identified: most of them have typical redshift (z ~ 0.3 - 4), apparent V magnitude (V ~ 16 - 20) and spectral index ( α ~ -2 - 0.8), but there is also a non-negligible number of objects localized well outside these ranges. Analysing the position of these sources in the redshift - V magnitude plane, redshift - spectral index plane and V magnitude - spectral index plane, it is possible to identify misclassified quasars and remove them away from the sample. The final list of quasar candidates includes 2294 objects, among which 1 is in common with Veron's quasar catalog.

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