Litcius/Paper detail

CLASS Survey Description: Coronal-line Needles in the SDSS Haystack

Michael Reefe, Remington O. Sexton, Sara Doan, Shobita Satyapal, Nathan J. Secrest, Jenna M. Cann

2023The Astrophysical Journal Supplement Series15 citationsDOIOpen Access PDF

Abstract

Abstract Coronal lines are a powerful, yet poorly understood, tool to identify and characterize active galactic nuclei. There have been few large-scale surveys of coronal lines in the general galaxy population in the literature so far. Using a novel preselection technique with a flux-to-rms ratio <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi mathvariant="italic"></mml:mi> </mml:math> , followed by Markov Chain Monte Carlo fitting, we searched for the full suite of 20 coronal lines in the optical spectra of almost 1 million galaxies from the Sloan Digital Sky Survey Data Release 8. We present a catalog of the emission-line parameters for the resulting 258 galaxies with detections. The Coronal Line Activity Spectroscopic Survey includes line properties, host-galaxy properties, and selection criteria for all galaxies in which at least one line is detected. This comprehensive study reveals that a significant fraction of coronal-line activity is missed in past surveys based on a more limited set of coronal lines; ∼60% of our sample do not display the more widely surveyed [Fe x ] λ 6374. In addition, we discover a strong correlation between coronal-line and Wide-field Infrared Survey Explorer W2 luminosities, suggesting that the mid-infrared flux can be used to predict coronal-line fluxes. For each line we also provide a confidence level that the line is present, generated by a novel neural network, trained on fully simulated data. We find that after training the network to detect individual lines using 100,000 simulated spectra, we achieve an overall true-positive rate of 75.49% and a false-positive rate of only 3.96%.

Topics & Concepts

HaystackCoronal planeClass (philosophy)Line (geometry)AstrophysicsPhysicsAstronomyComputer scienceMedicineArtificial intelligenceMathematicsGeometryAnatomyAstronomical Observations and InstrumentationGamma-ray bursts and supernovaeAstrophysical Phenomena and Observations