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2022ApJ...939..109L - Astrophys. J., 939, 109 (2022/November-2)

X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression.

LEWIN C., KARA E., WILKINS D., MASTROSERIO G., GARCIA J.A., ZHANG R.C., ALSTON W.N., CONNORS R., DAUSER T., FABIAN A., INGRAM A., JIANG J., LOHFINK A., LUCCHINI M., REYNOLDS C.S., TOMBESI F., VAN DER KLIS M. and WANG J.

Abstract (from CDS):

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 active galactic nuclei (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 multitask learning for application in AGN timing. By simultaneously fitting the time lags and the flux spectra with the relativistic reverberation model RELTRANS, we constrain the mass at ${2.3}_{-1.3}^{+2.6}\times {10}^{6}{M}_{\odot }$, 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.

Abstract Copyright: © 2022. The Author(s). Published by the American Astronomical Society.

Journal keyword(s): Accretion - Gaussian Processes regression - Black holes - Astrostatistics techniques - High energy astrophysics - X-ray active galactic nuclei - Model selection - Astrostatistics

Simbad objects: 11

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