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X-ray Reverberation Mapping of Ark 564 using Gaussian Process Regression by Lewin, Collin D.; Kara, Erin; Wilkins, Daniel R.; Mastroserio, Guglielmo; García, Javier A.; Zhang, Rachel; Alston, William; Connors, Riley M.; Dauser, Thomas; Fabian, Andy C.; Ingram, Adam; Jiang, Jiachen; Lohfink, Anne M.; Lucchini, Matteo; Reynolds, Christopher S.; Tombesi, Francesco; van der Klis, Michiel; Wang, Jingyi is a scholarly article available to read on EtoBox.

What is X-ray Reverberation Mapping of Ark 564 using Gaussian Process Regression about?

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.

Author

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

Published

2022

Language

EN