X-ray Reverberation Mapping of Ark 564 using Gaussian Process Regression

  • Collin D. Lewin
  • , Erin Kara
  • , Daniel R. Wilkins
  • , Guglielmo Mastroserio
  • , Javier A. García
  • , Rachel Zhang
  • , William Alston
  • , Riley M. Connors
  • , Thomas Dauser
  • , Andy C. Fabian
  • , Adam Ingram
  • , Jiachen Jiang
  • , Anne M. Lohfink
  • , Matteo Lucchini
  • , Christopher S. Reynolds
  • , Francesco Tombesi
  • , Michiel van der Klis
  • , Jingyi Wang

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
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Abstract

Ark 564 is an extreme high-Eddington Narrow-line Seyfert 1 galaxy, known for being one of the brightest, most rapidly variable soft X-ray AGN, and for having one of the lowest temperature coronae. Here we present a 410-ks NuSTAR observation and two 115-ks XMM-Newton observations of this unique source, which reveal a very strong, relativistically broadened iron line. We compute the Fourier-resolved time lags by first using Gaussian processes to interpolate the NuSTAR gaps, implementing the first employment of multi-task learning for application in AGN timing. By fitting simultaneously the time lags and the flux spectra with the relativistic reverberation model RELTRANS, we constrain the mass at $2.3^{+2.6}_{-1.3} \times 10^6M_\odot$, although additional components are required to describe the prominent soft excess in this source. These results motivate future combinations of machine learning, Fourier-resolved timing, and the development of reverberation models.
Original languageUndefined/Unknown
JournalAstrophysical Journal Letters
DOIs
Publication statusPublished - 11 Nov 2022

Keywords

  • astro-ph.HE

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