X-ray Reverberation Mapping of Ark 564 using Gaussian Process Regression
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 , 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.
Keywords
Cite
@article{arxiv.2210.01810,
title = {X-ray Reverberation Mapping of Ark 564 using Gaussian Process Regression},
author = {Collin D. Lewin and Erin Kara and Daniel R. Wilkins and Guglielmo Mastroserio and Javier A. García and Rachel Zhang and William Alston and Riley M. Connors and Thomas Dauser and Andy C. Fabian and Adam Ingram and Jiachen Jiang and Anne M. Lohfink and Matteo Lucchini and Christopher S. Reynolds and Francesco Tombesi and Michiel van der Klis and Jingyi Wang},
journal= {arXiv preprint arXiv:2210.01810},
year = {2025}
}
Comments
19 pages, 9 figures. Accepted for publication in The Astrophysical Journal