X-ray Reverberation Mapping of Ark 564 using Gaussian Process Regression
Abstract
X-ray reverberation mapping is a powerful technique for mapping the innermost accretion flows around supermassive black holes. The central corona irradiates the inner accretion disk, leading to delayed correlated variability. Measuring the time delays due to the corona-to-disk light-travel time unlocks an unprecedented level of spatial information of the disk. A Fourier frequency-resolved approach has been especially fruitful for isolating the time lags due to distinct physical processes. This approach, however, is limited by the length of our longest continuous observation—a limit significant for data collected with instruments in low-Earth orbit. I will show how we overcome this by modeling the observed variability using Gaussian Processes that we best train with the first employment of multi-task learning in AGN timing. In addition, recent model developments, namely in the relativistic reverberation model RELTRANS, allow us to model the time lags simultaneously with the flux-energy spectra, which provides stronger constraints on the physical and geometric parameters of the disk and breaks degeneracies present when fitting the data separately. I will present new XMM-Newton and NuSTAR observations of variable Seyfert I Ark 564, including NuSTAR's longest single exposure to-date, and other AGN, from which we constrain fundamental black hole parameters including mass and spin. These results motivate future combinations of machine-learning, Fourier-resolved timing, and the development of reverberation models.
- Publication:
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44th COSPAR Scientific Assembly. Held 16-24 July
- Pub Date:
- July 2022
- Bibcode:
- 2022cosp...44.2280L