Modeling the Time Variability of SDSS Stripe 82 Quasars as a Damped Random Walk

TL;DR

This study models quasar brightness variations over 10 years using a damped random walk, confirming its effectiveness and revealing how variability relates to physical properties like wavelength, black hole mass, and Eddington ratio.

Contribution

It demonstrates that the damped random walk model accurately describes quasar light curves and explores correlations between variability parameters and physical quasar properties.

Findings

Tau increases with wavelength following a power law.

Variability amplitude is anti-correlated with Eddington ratio.

Radio-loud quasars show larger variability amplitudes.

Abstract

We model the time variability of ~9,000 spectroscopically confirmed quasars in SDSS Stripe 82 as a damped random walk. Using 2.7 million photometric measurements collected over 10 years, we confirm the results of Kelly et al. (2009) and Koz{\l}owski et al. (2010) that this model can explain quasar light curves at an impressive fidelity level (0.01-0.02 mag). The damped random walk model provides a simple, fast [O(N) for N data points], and powerful statistical description of quasar light curves by a characteristic time scale (tau) and an asymptotic rms variability on long time scales (SF_inf). We searched for correlations between these two variability parameters and physical parameters such as luminosity and black hole mass, and rest-frame wavelength. We find that tau increases with increasing wavelength with a power law index of 0.17, remains nearly constant with redshift and luminosity, and increases with increasing black hole mass with power law index of 0.21+/-0.07. The amplitude of variability is anti-correlated with the Eddington ratio, which suggests a scenario where optical fluctuations are tied to variations in the accretion rate. The radio-loudest quasars have systematically larger variability amplitudes by about 30%, when corrected for the other observed trends, while the distribution of their characteristic time scale is indistinguishable from that of the full sample. We do not detect any statistically robust differences in the characteristic time scale and variability amplitude between the full sample and the small subsample of quasars detected by ROSAT. Our results provide a simple quantitative framework for generating mock quasar light curves, such as currently used in LSST image simulations. (abridged)