The discrimination between star-forming and AGN galaxies in the absence of H α and [N ii]: a machine -learning approach

• DOI: 10.1093/mnras/sty1331
• Publication Date: 2018-05-18T15:14:36Z
• Authors: H Teimoorinia; J Keown
• Keywords: Confusion; Equivalent width; Stellar mass; Star (game theory)

In the absence of two emission lines H α and [N ii] (6584 Å) in a BPT diagram, we show that other spectral information is sufficiently informative to distinguish active galactic nucleus (AGN) galaxies from star-forming galaxies. We use pattern recognition methods sample galaxy spectra Sloan Digital Sky Survey that, this survey, flux equivalent width [O iii] (5007 β, along with 4000 Å break, can be used classify diagram. This method provides higher accuracy predictions than those which stellar mass iii]/H β. First, diagrams various physical parameters re-classify Next, using confusion matrices, determine ‘correctly’ predicted classes as well confused cases. way, investigate effect each parameter matrices rank discrimination different classes. for example, |$\rm {g - r}$| colour provide same predict whether or not hosts an AGN. Finally, information, also involved Seyfert LINER