X-Ray Coronal Properties of Swift/BAT-selected Seyfert 1 Active Galactic Nuclei

Creators: Kamraj, Nikita; Brightman, Murray; Harrison, Fiona A.; Stern, Daniel; García, Javier A.; Baloković, Mislav; Ricci, Claudio; Koss, Michael J.; Mejía-Restrepo, Julian E.; Oh, Kyuseok; Powell, Meredith C.; Urry, C. Megan

Abstract

The corona is an integral component of active galactic nuclei (AGNs) which produces the bulk of the X-ray emission above 1–2 keV. However, many of its physical properties and the mechanisms powering this emission remain a mystery. In particular, the temperature of the coronal plasma has been difficult to constrain for large samples of AGNs, as constraints require high-quality broadband X-ray spectral coverage extending above 10 keV in order to measure the high-energy cutoff, which provides constraints on the combination of coronal optical depth and temperature. We present constraints on the coronal temperature for a large sample of Seyfert 1 AGNs selected from the Swift/BAT survey using high-quality hard X-ray data from the NuSTAR observatory combined with simultaneous soft X-ray data from Swift/XRT or XMM-Newton. When applying a physically motivated, nonrelativistic disk-reflection model to the X-ray spectra, we find a mean coronal temperature kT_e = 84 ± 9 keV. We find no significant correlation between the coronal cutoff energy and accretion parameters such as the Eddington ratio and black hole mass. We also do not find a statistically significant correlation between the X-ray photon index, Γ, and Eddington ratio. This calls into question the use of such relations to infer properties of supermassive black hole systems.

Additional Information

© 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 2021 July 20; revised 2021 November 2; accepted 2021 November 20; published 2022 March 3. We have made use of data from the NuSTAR mission, a project led by the California Institute of Technology, managed by the Jet Propulsion Laboratory and funded by the National Aeronautics and Space Administration. We thank the NuSTAR Operations, Software and Calibration teams for support with the execution and analysis of these observations. This research has made use of the following resources: NuSTAR Data Analysis Software (NuSTARDAS) jointly developed by the ASI Science Data Center (ASDC, Italy) and the California Institute of Technology (USA); online Swift data processing services provided by the SSDC; the High Energy Astrophysics Science Archive Research Center Online Service, provided by the NASA/Goddard Space Flight Center; NASA's Astrophysics Data System; Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration et al. 2013, 2018). Some of the optical spectra used for determining black hole masses used in this work were taken with the Doublespec (DBSP) instrument at Palomar via Yale (PI: M. Powell, 2017–2019, 16 nights) as well as Caltech (PI: F. Harrison) and JPL (PI: D. Stern) from programs from 2013 to 2020. M. Baloković acknowledges support from the Black Hole Initiative at Harvard University, which is funded in part by the Gordon and Betty Moore Foundation (grant GBMF8273) and in part by the John Templeton Foundation, as well as support from the YCAA Prize Postdoctoral Fellowship. M.K. acknowledges support from NASA through ADAP award NNH16CT03C. K.O. acknowledges support from the National Research Foundation of Korea (NRF-2020R1C1C1005462). C.R. acknowledges support from the CONICYT+PAI Convocatoria Nacional subvencion a instalacion en la academia convocatoria año 2017 PAI77170080. Facilities: NuSTAR - The NuSTAR (Nuclear Spectroscopic Telescope Array) mission, Swift - , XMM-Newton - , Palomar Hale(DBSP). - Software: TBabs (Wilms et al. 2000), pexrav (Magdziarz & Zdziarski 1995), nthComp (Zdziarski et al. 1996), xillverCp (García & Kallman 2010), NuSTARDAS (v2.17.1), HEASOFT (v6.24), XMM SAS (v16.1.0), XSPEC (v12.8.2), Astropy (Astropy Collaboration et al. 2013, 2018), NumPy, Matplotlib (Hunter 2007).

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