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Classification of Broad Absorption Line Quasars with a Convolutional Neural Network

Journal Article · · The Astrophysical Journal (Online)
 [1];  [2]
  1. Ohio State Univ., Columbus, OH (United States). Dept. of Astronomy; DOE/OSTI
  2. The Ohio State Univ., Columbus, OH (United States). Dept. of Astronomy and Center for Cosmology and Astro-Particle Physics
+ Show Author Affiliations
Quasars that exhibit blueshifted, broad absorption lines (BAL QSOs) are an important probe of black hole feedback on galaxy evolution. Yet the presence of BALs is also a complication for large spectroscopic surveys that use quasars as cosmological probes because the BAL features can affect redshift measurements and contaminate information about the matter distribution in the Lyα forest. We present a new BAL QSO catalog for quasars in the Sloan Digital Sky Survey (SDSS) Data Release 14 (DR14). As the SDSS DR14 quasar catalog has over 500,000 quasars, we have developed an automated BAL classifier with a Convolutional Neural Network (CNN). We trained our CNN classifier on the C IV λ 1549 region of a sample of quasars with reliable human classifications, and compared the results to both a dedicated test sample and visual classifications from the earlier SDSS DR12 quasar catalog. Our CNN classifier correctly classifies over 98% of the BAL quasars in the DR12 catalog, which demonstrates comparable reliability to human classification. The disagreements are generally for quasars with lower signal-to-noise ratio spectra and/or weaker BAL features. Our new catalog includes the probability that each quasar is a BAL, the strength, blueshifts and velocity widths of the troughs, and similar information for any Si IV λ 1398 BAL troughs that may be present. We find significant BAL features in 16.8% of all quasars with 1.57 < z < 5.56 in the SDSS DR14 quasar catalog.
Research Organization:
The Ohio State Univ., Columbus, OH (United States)
Sponsoring Organization:
Alfred P. Sloan Foundation; National Science Foundation (NSF); USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Grant/Contract Number:
SC0011726
OSTI ID:
1611662
Journal Information:
The Astrophysical Journal (Online), Journal Name: The Astrophysical Journal (Online) Journal Issue: 2 Vol. 879; ISSN 1538-4357
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English

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Cited By (1)

The Ubiquitous Imprint of Radiative Acceleration in the Mean Absorption Spectrum of Quasar Outflows journal December 2019

Figures / Tables (14)

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Related Subjects

79 ASTRONOMY AND ASTROPHYSICS
Astronomy &amp; Astrophysics
catalogs
quasars: absorption lines