Description
We apply a recently developed method for classifying broad absorption line quasars (BALQSOs) to the latest QSO catalogue constructed from Data Release 5 of the Sloan Digital Sky Survey. Our new hybrid classification method combines the power of simple metrics, supervised neural networks and visual inspection. The resulting BALQSO catalogue is both more complete and more robust than all previous BALQSO catalogues, containing 3552 sources selected from a parent sample of 28421 QSOs in the redshift range 1.7<z<4.2. This equates to a raw BAL QSO fraction of 12.5%. In the process of constructing a robust catalogue we shed light on the main problems encountered when dealing with BALQSO classification, in particular when the astronomical objects in question do not yet have a formal definition as is the case for BALQSOs. This introduces some subjectivity on what is meant by BALQSO, and because of this we also provide meta-data of our catalogue, comprising our whole parent sample which can be used to quickly isolate and explore various sub-samples.
|