Modelling the Multiwavelength Variability of Mrk 335 using Gaussian Processes
Ryan-Rhys Griffiths, Jiachen Jiang, Douglas J. K. Buisson, Dan R., Wilkins, Luigi C. Gallo, Adam Ingram, Alpha A. Lee, Dirk Grupe, Erin Kara,, Michael L. Parker, William Alston, Anthony Bourached, George Cann, Andrew, Young, S. Komossa

TL;DR
This study employs Gaussian process regression to interpolate gaps in X-ray and UV lightcurves of Mrk 335, revealing potential lag features consistent with reprocessing models of AGN variability.
Contribution
It introduces a novel application of Gaussian process kernels to analyze AGN lightcurves and identifies kernel-dependent lag features in Mrk 335's variability.
Findings
Gaussian process kernels effectively interpolate lightcurve gaps.
Detected UV/X-ray lag features up to 30 days.
Identified a break point at 125 days in UV structure function.
Abstract
The optical and UV variability of the majority of AGN may be related to the reprocessing of rapidly-changing X-ray emission from a more compact region near the central black hole. Such a reprocessing model would be characterised by lags between X-ray and optical/UV emission due to differences in light travel time. Observationally however, such lag features have been difficult to detect due to gaps in the lightcurves introduced through factors such as source visibility or limited telescope time. In this work, Gaussian process regression is employed to interpolate the gaps in the Swift X-ray and UV lightcurves of the narrow-line Seyfert 1 galaxy Mrk 335. In a simulation study of five commonly-employed analytic Gaussian process kernels, we conclude that the Matern 1/2 and rational quadratic kernels yield the most well-specified models for the X-ray and UVW2 bands of Mrk 335. In analysing…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
