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arXiv · 0810.4396

Broad Absorption Line Quasar catalogues with Supervised Neural Networks

Simone Scaringi·Christopher E. Cottis·Christian Knigge·Michael R. Goad
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Abstract

We have applied a Learning Vector Quantization (LVQ) algorithm to SDSS DR5 quasar spectra in order to create a large catalogue of broad absorption line quasars (BALQSOs). We first discuss the problems with BALQSO catalogues constructed using the conventional balnicity and/or absorption indices (BI and AI), and then describe the supervised LVQ network we have trained to recognise BALQSOs. The resulting BALQSO catalogue should be substantially more robust and complete than BI- or AI-based ones.

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Simone Scaringi, Christopher E. Cottis, Christian Knigge, Michael R. Goad. 2008-10-24. Broad Absorption Line Quasar catalogues with Supervised Neural Networks. https://doi.org/10.1063/1.3059042

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