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12 papers · 1 filter
Coronal height constraint in IRAS 13224-3809 and 1H 0707-495 by the random forest regressor
N. Mankatwit, P. Chainakun, W. Luangtip +1
We develop a random forest regressor (RFR) machine learning model to trace the coronal evolution in two highly variable active galactic nuclei (AGNs) IRAS 13224-3809 and 1H 0707-49…
Revealing the intrinsic X-ray reverberation lags in IRAS 13224-3809 through the Granger causality test
P. Chainakun, N. Nakhonthong, W. Luangtip +1
The Granger causality is an econometric test for determining whether one time series is useful for forecasting another one with a certain Granger lag. Here, the light curves in the…
Extended Corona Models of X-ray Reverberation in the AGN 1H~0707-495 and IRAS 13224-3809
S. Hancock, A. J. Young, P. Chainakun
We fit a new vertically extended corona model to previously measured reverberation time lags observed by \emph{XMM-Newton} in two extremely variable Narrow Line Seyfert 1 Active Ga…
Variability In A Low-Mass AGN: Oscillation Or Eruption?
Robbie Webbe, A. J. Young
Following the discovery of a new class of X-ray variability seen in four galaxies, dubbed Quasi-Periodic Eruptions (QPEs), we reconsider the variability seen in the low-mass AGN 2X…
Mapping the X-ray corona evolution of IRAS 13224-3809 with the power spectral density
Poemwai Chainakun, Wasuthep Luangtip, Jiachen Jiang +1
We develop the power spectral density (PSD) model to explain the nature of the X-ray variability in IRAS 13224-3809, including the full effects of the X-ray reverberation due to th…
Predicting the black hole mass and correlations in X-ray reverberating AGN using neural networks
P. Chainakun, I. Fongkaew, S. Hancock +1
We develop neural network models to predict the black hole mass using 22 reverberating AGN samples in the XMM-Newton archive. The model features include the fractional excess varia…