Despite the importance of active galactic nuclei (AGNs) in galaxy evolution, accurate AGN identification is often challenging, as common AGN diagnostics can be confused by contributions from star formation and other effects (e.g., Baldwin–Phillips–Terlevich diagrams). However, one promising avenue for identifying AGNs is “coronal emission lines” (“CLs”), which are highly ionized species of gas with ionization potentials ≥100 eV. These CLs may serve as excellent signatures for the strong ionizing continuum of AGNs. To determine if CLs are in fact strong AGN tracers, we assemble and analyze the largest catalog of optical CL galaxies using the Sloan Digital Sky Survey's Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) catalog. We detect CL emission in 71 MaNGA galaxies, out of the 10,010 unique galaxies from the final MaNGA catalog, with ≥5
We present second epoch optical spectra for 30 changing-look (CL) candidates found by searching for Type-1 optical variability in a sample of active galactic nuclei (AGNs) spectroscopically classified as Type 2. We use a random-forest-based light-curve classifier and spectroscopic follow-up, confirming 50 per cent of candidates as turning-on CLs. In order to improve this selection method and to better understand the nature of the not-confirmed CL candidates, we perform a multiwavelength variability analysis including optical, mid-infrared (MIR), and X-ray data, and compare the results from the confirmed and not-confirmed CLs identified in this work. We find that most of the not-confirmed CLs are consistent with weak Type 1s dominated by host-galaxy contributions, showing weaker optical and MIR variability. On the contrary, the confirmed CLs present stronger optical fluctuations and experience a long (from five to ten years) increase in their MIR fluxes and the colour W1–W2 over time. In the 0.2–2.3 keV band, at least four out of 11 CLs with available SRG/eROSITA detections have increased their flux in comparison with archival upper limits. These common features allow us to select the most promising CLs from our list of candidates, leading to nine sources with similar multiwavelength photometric properties to our CL sample. The use of machine learning algorithms with optical and MIR light curves will be very useful to identify CLs in future large-scale surveys.
more » « less- Award ID(s):
- 2108402
- PAR ID:
- 10429336
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 524
- Issue:
- 1
- ISSN:
- 0035-8711
- Format(s):
- Medium: X Size: p. 188-206
- Size(s):
- p. 188-206
- Sponsoring Org:
- National Science Foundation
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