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

Fuente: arXiv
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Autori principali: 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
Natura: Preprint
Pubblicazione: 2022
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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
author_facet 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
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2210_01810
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle X-ray Reverberation Mapping of Ark 564 using Gaussian Process Regression
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
High Energy Astrophysical Phenomena
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.
title X-ray Reverberation Mapping of Ark 564 using Gaussian Process Regression
topic High Energy Astrophysical Phenomena
url https://arxiv.org/abs/2210.01810