AGN Variability: Probing Black Hole Accretion
Abstract
We combine the long temporal baseline of Sloan Digital Sky Survey (SDSS) for quasars in Stripe 82 with the high precision photometry of the Kepler/K2 Satellite to study the physics of optical variability in the accretion disk and supermassive black hole engine. We model the lightcurves directly as Continuous-time Auto Regressive Moving Average processes (C-ARMA) with the Kali analysis package (Kasliwal et al. 2016). These models are extremely robust to irregular sampling and can capture aperiodic variability structure on various timescales. We also estimate the power spectral density and structure function of both the model family and the data. A Green's function kernel may also be estimated for the resulting C-ARMA parameter fit, which may be interpreted as the response to driving impulses such as hotspots in the accretion disk. We also examine available spectra for our AGN sample to relate observed and modelled behavior to spectral properties. The objective of this work is twofold: to explore the proper physical interpretation of different families of C-ARMA models applied to AGN optical flux variability and to relate empirical characteristic timescales of our AGN sample to physical theory or to properties estimated from spectra or simulations like the disk viscosity and temperature. We find that AGN with strong variability features on timescales resolved by K2 are well modelled by a low order C-ARMA family while K2 lightcurves with weak amplitude variability are dominated by outliers and measurement errors which force higher order model fits. This work explores a novel approach to combining SDSS and K2 data sets and presents recovered characteristic timescales of AGN variability.
- Publication:
-
American Astronomical Society Meeting Abstracts #229
- Pub Date:
- January 2017
- Bibcode:
- 2017AAS...22925036M